From 1c35e5160bc041debf4be0b7c21a1f3a1671dd3c Mon Sep 17 00:00:00 2001 From: Ilia Babanov Date: Wed, 30 Oct 2024 11:29:56 +0100 Subject: [PATCH] Merge bundle-integ into main (#1414) ## Changes Decided to avoid bypassing branch protections by force pushing `bundle-integ` into `main`. Instead: - checkout a new branch from `main` - `git revert` everything until a common ancestor with the `bundle-integ` (based on `git merge-base`), [here's the commit](https://github.com/databricks/databricks-vscode/pull/1414/commits/2b7e82699c859d802f92b16f86d3210cfde7f202) - `git merge bundle-integ` - add [one additional commit to update GH workflows](https://github.com/databricks/databricks-vscode/pull/1414/commits/b802322fcb3830e2b548672fa68bc77e117b5763). ## Tests Built and checked the extension manually. Unit tests pass, will check integ tests in this PR --------- Co-authored-by: kartikgupta-db Co-authored-by: Kartik Gupta <88345179+kartikgupta-db@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: releasebot Co-authored-by: eng-dev-ecosystem-bot Co-authored-by: eng-dev-ecosystem-bot <110475461+eng-dev-ecosystem-bot@users.noreply.github.com> Co-authored-by: Serge Smertin <259697+nfx@users.noreply.github.com> Co-authored-by: Fabian Jakobs Co-authored-by: Julia Crawford (Databricks) Co-authored-by: hectorcast-db --- .eslintrc.json | 2 +- .github/workflows/create-build-artifacts.yml | 1 + .github/workflows/integration-tests.yml | 57 + .github/workflows/nightly-release.yml | 4 +- .github/workflows/publish-to-vscode.yml | 17 +- .github/workflows/push.yml | 24 +- .github/workflows/tests.yml | 89 - README.md | 2 +- databricks-vscode.code-workspace | 4 +- package.json | 16 +- 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packages/databricks-vscode/src/ui/utils/index.ts create mode 100644 packages/databricks-vscode/src/utils/DateUtils.ts create mode 100644 packages/databricks-vscode/src/utils/EventWithErrorHandler.ts create mode 100644 packages/databricks-vscode/src/utils/environmentUtils.ts create mode 100644 packages/databricks-vscode/src/utils/onErrorDecorator.ts create mode 100644 packages/databricks-vscode/src/utils/shellUtils.ts create mode 100644 packages/databricks-vscode/src/utils/terraformUtils.ts create mode 100644 packages/databricks-vscode/src/vscode-objs/WorkspaceFolderManager.ts delete mode 100644 packages/databricks-vscode/src/workspace-fs/WorkspaceFsAccessVerifier.ts diff --git a/.eslintrc.json b/.eslintrc.json index c72111111..58f4d2bbd 100644 --- a/.eslintrc.json +++ b/.eslintrc.json @@ -26,7 +26,7 @@ }, "overrides": [ { - "files": "**/*.test.ts", + "files": ["**/*.test.ts", "**/test/**"], "rules": { "no-console": "off" } diff --git a/.github/workflows/create-build-artifacts.yml b/.github/workflows/create-build-artifacts.yml index 6a91d8d95..13b7b7eff 100644 --- a/.github/workflows/create-build-artifacts.yml +++ b/.github/workflows/create-build-artifacts.yml @@ -25,6 +25,7 @@ jobs: working-directory: packages/databricks-vscode env: GH_TOKEN: ${{ github.token }} + BUILD_PLATFORM_ARCH: linux_amd64 - uses: actions/upload-artifact@v3 with: diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml new file mode 100644 index 000000000..aba6ddaf7 --- /dev/null +++ b/.github/workflows/integration-tests.yml @@ -0,0 +1,57 @@ +name: integration + +on: + pull_request: + types: [opened, synchronize] + + merge_group: + +jobs: + trigger-tests: + if: github.event_name == 'pull_request' + name: Trigger Tests + runs-on: ubuntu-latest + environment: "test-trigger-is" + + steps: + - uses: actions/checkout@v4 + + - name: Generate GitHub App Token + id: generate-token + uses: actions/create-github-app-token@v1 + with: + app-id: ${{ secrets.DECO_WORKFLOW_TRIGGER_APP_ID }} + private-key: ${{ secrets.DECO_WORKFLOW_TRIGGER_PRIVATE_KEY }} + owner: ${{ secrets.ORG_NAME }} + repositories: ${{secrets.REPO_NAME}} + + - name: Trigger Workflow in Another Repo + env: + GH_TOKEN: ${{ steps.generate-token.outputs.token }} + run: | + gh workflow run vscode-isolated-pr.yml -R ${{ secrets.ORG_NAME }}/${{secrets.REPO_NAME}} \ + --ref main \ + -f pull_request_number=${{ github.event.pull_request.number }} \ + -f commit_sha=${{ github.event.pull_request.head.sha }} + + # Statuses and checks apply to specific commits (by hash). + # Enforcement of required checks is done both at the PR level and the merge queue level. + # In case of multiple commits in a single PR, the hash of the squashed commit + # will not match the one for the latest (approved) commit in the PR. + # We auto approve the check for the merge queue for two reasons: + # * Queue times out due to duration of tests. + # * Avoid running integration tests twice, since it was already run at the tip of the branch before squashing. + auto-approve: + if: github.event_name == 'merge_group' + runs-on: ubuntu-latest + steps: + - name: Mark Check + env: + GH_TOKEN: ${{ secrets.GITHUB_TOKEN }} + shell: bash + run: | + gh api -X POST -H "Accept: application/vnd.github+json" \ + -H "X-GitHub-Api-Version: 2022-11-28" \ + /repos/${{ github.repository }}/statuses/${{ github.sha }} \ + -f 'state=success' \ + -f 'context=Integration Tests Check' diff --git a/.github/workflows/nightly-release.yml b/.github/workflows/nightly-release.yml index 9d2e214eb..5bf32c211 100644 --- a/.github/workflows/nightly-release.yml +++ b/.github/workflows/nightly-release.yml @@ -24,8 +24,8 @@ jobs: - name: Update nightly release uses: softprops/action-gh-release@v1 with: - name: Nightly + name: Nightly - ${{ github.ref_name }} prerelease: true - tag_name: nightly + tag_name: nightly-${{ github.ref_name }} token: ${{ secrets.GITHUB_TOKEN }} files: "packages/databricks-vscode/databricks*/*.vsix" diff --git a/.github/workflows/publish-to-vscode.yml b/.github/workflows/publish-to-vscode.yml index b5a164dea..e50e4eba3 100644 --- a/.github/workflows/publish-to-vscode.yml +++ b/.github/workflows/publish-to-vscode.yml @@ -13,7 +13,6 @@ on: jobs: publish-to-vscode: - if: ${{ ! endsWith(github.event.inputs.version, 'preview') || github.event_name == 'workflow_dispatch' }} runs-on: ubuntu-latest environment: Production @@ -54,13 +53,13 @@ jobs: env: VSCE_TOKEN: ${{ secrets.VSCE_TOKEN }} - - name: Install ovsx - run: npm install -g ovsx + # - name: Install ovsx + # run: npm install -g ovsx - - name: Publish to Open VSIX - run: | - ovsx verify-pat databricks - ovsx publish --packagePath databricks-*.vsix + # - name: Publish to Open VSIX + # run: | + # ovsx verify-pat databricks + # ovsx publish --packagePath databricks-*.vsix - env: - OVSX_PAT: ${{ secrets.OVSX_PAT }} + # env: + # OVSX_PAT: ${{ secrets.OVSX_PAT }} diff --git a/.github/workflows/push.yml b/.github/workflows/push.yml index cf292fb67..26b4bdd3f 100644 --- a/.github/workflows/push.yml +++ b/.github/workflows/push.yml @@ -7,28 +7,8 @@ on: branches: [main] jobs: - run-tests: - strategy: - fail-fast: false - matrix: - arch: - [ - { cli_arch: darwin_amd64, os: macos-latest }, - { cli_arch: windows_amd64, os: windows-latest }, - ] - node-version: [18.x] - vscode-version: [stable] - uses: ./.github/workflows/tests.yml - with: - os: ${{ matrix.arch.os }} - node-version: ${{ matrix.node-version }} - vscode-version: ${{ matrix.vscode-version }} - cli_arch: ${{ matrix.arch.cli_arch }} - secrets: inherit - package: - name: Package VSIX - needs: "run-tests" + name: Package Arm64 VSIX runs-on: "macos-latest" steps: - uses: actions/checkout@v3 @@ -53,7 +33,7 @@ jobs: - run: mkdir -p packages/databricks-vscode/artifacts - name: Build VSIX - run: yarn package -o artifacts -t darwin-x64 + run: yarn package -o artifacts -t darwin-arm64 working-directory: packages/databricks-vscode - name: Upload artifacts diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml deleted file mode 100644 index 43634841a..000000000 --- a/.github/workflows/tests.yml +++ /dev/null @@ -1,89 +0,0 @@ -name: VSCode extension Tests - -on: - workflow_call: - inputs: - os: - required: true - type: string - node-version: - required: true - type: string - vscode-version: - required: true - type: string - cli_arch: - required: true - type: string - -jobs: - test-extension: - name: Test VSCode Extension - runs-on: ${{ inputs.os }} - environment: - name: azure-prod-usr - - env: - VSCODE_TEST_VERSION: ${{ inputs.vscode-version }} - DATABRICKS_HOST: ${{ secrets.DATABRICKS_HOST }} - DATABRICKS_TOKEN: ${{ secrets.DATABRICKS_TOKEN }} - TEST_DEFAULT_CLUSTER_ID: ${{ secrets.TEST_VSCODE_CLUSTER_ID }} - CLI_ARCH: ${{ inputs.cli_arch }} - - defaults: - run: - shell: bash - - steps: - - uses: actions/checkout@v3 - - - name: Use Node.js ${{ inputs.node-version }} - uses: actions/setup-node@v3 - with: - node-version: ${{ inputs.node-version }} - cache: "yarn" - - - name: Cache wdio - uses: actions/cache@v3 - with: - path: /tmp/wdio-vscode-service - key: ${{ inputs.cli_arch }}-${{ inputs.vscode-version }}-wdio - - - name: Cache VSCode unit test runner - uses: actions/cache@v3 - with: - path: /tmp/vscode-test-databricks - key: ${{ inputs.cli_arch }}-${{ inputs.vscode-version }}-vscode-test - - - run: yarn install --immutable - - - name: Prettier and Linting - run: yarn run test:lint - working-directory: packages/databricks-vscode - - - name: Fetching Databricks CLI - run: yarn run package:cli:fetch - working-directory: packages/databricks-vscode - env: - GH_TOKEN: ${{ github.token }} - - - name: Building packages - run: yarn run build - - - name: Unit Tests with Coverage - uses: coactions/setup-xvfb@v1 - with: - run: yarn run test:cov - working-directory: packages/databricks-vscode - - - name: Integration Tests - run: yarn run test:integ - working-directory: packages/databricks-vscode - - - name: Upload test logs - if: always() - continue-on-error: true - uses: actions/upload-artifact@v3 - with: - name: test-logs ${{ join(inputs.*, ' - ') }} - ${{ github.event_name }} - path: packages/databricks-vscode/logs diff --git a/README.md b/README.md index 49982aa70..6a7ca464d 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ | System | Status | | ---------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| Build ([main branch](https://github.com/databricks/databricks-vscode/commits/main)) | [![GitHub CI Status](https://github.com/databricks/databricks-vscode/actions/workflows/push.yml/badge.svg?branch=main)](https://github.com/databricks/databricks-vscode/actions/workflows/push.yml) [![codecov](https://codecov.io/gh/databricks/databricks-vscode/branch/main/graph/badge.svg?token=PUN77X0W3Z)](https://codecov.io/gh/databricks/databricks-vscode) [![lines of code](https://tokei.rs/b1/github/databricks/databricks-vscode)]([https://codecov.io/github/databricks/databricks-vscode](https://github.com/databricks/databricks-vscode)) | +| Build ([main branch](https://github.com/databricks/databricks-vscode/commits/main)) | [![GitHub CI Status](https://github.com/databricks/databricks-vscode/actions/workflows/push.yml/badge.svg?branch=main)](https://github.com/databricks/databricks-vscode/actions/workflows/push.yml) [![codecov](https://codecov.io/gh/databricks/databricks-vscode/branch/main/graph/badge.svg?token=PUN77X0W3Z)](https://codecov.io/gh/databricks/databricks-vscode) | | [Marketplace](https://marketplace.visualstudio.com/items?itemName=databricks.databricks) | [![Marketplace Version](https://img.shields.io/vscode-marketplace/v/databricks.databricks.svg) ![Marketplace Downloads](https://img.shields.io/vscode-marketplace/d/databricks.databricks.svg)](https://marketplace.visualstudio.com/items?itemName=databricks.databricks) | ## Introduction diff --git a/databricks-vscode.code-workspace b/databricks-vscode.code-workspace index 3a2047c52..7bbbdc42b 100644 --- a/databricks-vscode.code-workspace +++ b/databricks-vscode.code-workspace @@ -22,6 +22,8 @@ }, "[typescript]": { "editor.defaultFormatter": "esbenp.prettier-vscode" - } + }, + "jupyter.interactiveWindow.cellMarker.codeRegex": "^# COMMAND ----------|^# Databricks notebook source|^(#\\s*%%|#\\s*\\|#\\s*In\\[\\d*?\\]|#\\s*In\\[ \\])", + "jupyter.interactiveWindow.cellMarker.default": "# COMMAND ----------" } } diff --git a/package.json b/package.json index 3a8e389cb..0486347b2 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { "name": "@databricks/databricks-vscode", - "version": "1.4.0", + "version": "2.4.7", "private": true, "workspaces": [ "packages/*" @@ -34,15 +34,15 @@ "homepage": "https://github.com/databricks/databricks-vscode#readme", "packageManager": "yarn@3.2.1", "devDependencies": { - "@types/node": "^20.5.0", - "@typescript-eslint/eslint-plugin": "^6.0.0", - "@typescript-eslint/parser": "^6.0.0", - "conventional-changelog-cli": "^3.0.0", - "eslint": "^8.51.0", - "eslint-config-prettier": "^8.8.0", + "@types/node": "^20.10.4", + "@typescript-eslint/eslint-plugin": "^6.14.0", + "@typescript-eslint/parser": "^6.14.0", + "conventional-changelog-cli": "^4.1.0", + "eslint": "^8.55.0", + "eslint-config-prettier": "^9.1.0", "eslint-plugin-no-only-tests": "^3.1.0", "ts-mockito": "^2.6.1", - "typescript": "5.1.6" + "typescript": "^5.3.3" }, "resolutions": { "json5": "2.2.2" diff --git a/packages/databricks-vscode-types/CHANGELOG.md b/packages/databricks-vscode-types/CHANGELOG.md index 5d9c21545..fde491d57 100644 --- a/packages/databricks-vscode-types/CHANGELOG.md +++ b/packages/databricks-vscode-types/CHANGELOG.md @@ -1,32 +1,144 @@ -# Release: v1.4.0 +# Release: v2.4.7 ## packages/databricks-vscode-types -## 1.4.0 (2024-08-28) +## (2024-10-24) -# Release: v1.3.1 +# Release: v2.4.6 ## packages/databricks-vscode-types -## 1.3.1 (2024-07-03) +## (2024-10-15) -# Release: v1.3.0 +# Release: v2.4.5 ## packages/databricks-vscode-types -## 1.3.0 (2024-03-19) +## (2024-10-10) -# Release: v1.2.7 +# Release: v2.4.4 ## packages/databricks-vscode-types -## 1.2.7 (2024-02-05) +## (2024-09-26) -# Release: v1.2.6 +# Release: v2.4.3 ## packages/databricks-vscode-types -## 1.2.6 (2024-01-31) +## (2024-09-25) + +# Release: v2.4.2 + +## packages/databricks-vscode-types + +## (2024-09-06) + +# Release: v2.4.1 + +## packages/databricks-vscode-types + +## (2024-09-05) + +# Release: v2.4.0-preview + +## packages/databricks-vscode-types + +## (2024-08-26) + +# Release: v2.3.4-preview + +## packages/databricks-vscode-types + +## (2024-08-30) + +# Release: v2.3.3-preview + +## packages/databricks-vscode-types + +## (2024-08-30) + +# Release: v2.3.2-preview + +## packages/databricks-vscode-types + +## (2024-08-22) + +# Release: v2.3.1-preview + +## packages/databricks-vscode-types + +## (2024-08-13) + +# Release: v2.3.0-preview + +## packages/databricks-vscode-types + +## (2024-07-18) + +# Release: v2.2.2-preview + +## packages/databricks-vscode-types + +## (2024-07-03) + +# Release: v2.2.1-preview + +## packages/databricks-vscode-types + +## (2024-06-27) + +# Release: v2.2.0-preview + +## packages/databricks-vscode-types + +## (2024-06-26) + +# Release: v2.1.2-preview + +## packages/databricks-vscode-types + +## (2024-05-06) + +- Bring back `login` public API + +# Release: v2.1.1-preview + +## packages/databricks-vscode-types + +## (2024-05-02) + +# Release: v2.1.0-preview + +## packages/databricks-vscode-types + +## (2024-04-24) + +# Release: v2.0.4-preview + +## packages/databricks-vscode-types + +## (2024-04-09) + +# Release: v2.0.3-preview + +## packages/databricks-vscode-types + +## (2024-04-08) + +# Release: v2.0.2-preview + +## packages/databricks-vscode-types + +## (2024-04-03) + +# Release: v2.0.1-preview + +## packages/databricks-vscode-types + +- We made some breaking changes to the API. Please refer to future changelog updates for more information. + +## (2024-03-07) # Release: v1.2.5 diff --git a/packages/databricks-vscode-types/package.json b/packages/databricks-vscode-types/package.json index 99ec87b34..83c4c3d43 100644 --- a/packages/databricks-vscode-types/package.json +++ b/packages/databricks-vscode-types/package.json @@ -1,6 +1,6 @@ { "name": "@databricks/databricks-vscode-types", - "version": "1.4.0", + "version": "2.4.7", "description": "Package with types and interfaces to develop extensions to the Databricks VSCode plugin", "main": "index.js", "types": "index.d.ts", @@ -23,13 +23,13 @@ "test": "yarn run test:lint && yarn run test:unit" }, "devDependencies": { - "@types/vscode": "^1.69.1", - "eslint": "^8.51.0", - "prettier": "^3.0.0", - "typescript": "5.1.6" + "@types/vscode": "1.86.0", + "eslint": "^8.55.0", + "prettier": "^3.1.1", + "typescript": "^5.3.3" }, "dependencies": { "@databricks/databricks-sdk": "file:../../vendor/databricks-sdk.tgz", - "databricks": "*" + "databricks": "workspace:^" } } diff --git a/packages/databricks-vscode/.eslintrc.json b/packages/databricks-vscode/.eslintrc.json new file mode 100644 index 000000000..4f1ba9b7a --- /dev/null +++ b/packages/databricks-vscode/.eslintrc.json @@ -0,0 +1,6 @@ +{ + "plugins": ["eslint-plugin-local-rules"], + "rules": { + "local-rules/mutex-synchronised-decorator": "error" + } +} diff --git a/packages/databricks-vscode/.gitignore b/packages/databricks-vscode/.gitignore index 08dd10e37..16f09b43d 100644 --- a/packages/databricks-vscode/.gitignore +++ b/packages/databricks-vscode/.gitignore @@ -3,6 +3,9 @@ bin/** .wdio-vscode-service src/test/e2e/workspace/ extension/ +.pytest_cache/ +.build/ +**/tmp/** # Telemetry file, automatically generated by packages/databricks-vscode/scripts/generateTelemetry.ts telemetry.json diff --git a/packages/databricks-vscode/.prettierignore b/packages/databricks-vscode/.prettierignore index 71aa6c3cd..929afb50d 100644 --- a/packages/databricks-vscode/.prettierignore +++ b/packages/databricks-vscode/.prettierignore @@ -6,4 +6,6 @@ package-lock.json .wdio-vscode-service/ src/test/e2e/workspace/.databricks/ extension/ -resources/python/generated/ \ No newline at end of file +resources/python/generated/ +.venv +*.vsix diff --git a/packages/databricks-vscode/.vscode/settings.json b/packages/databricks-vscode/.vscode/settings.json index ae0b473e0..5f22022b8 100644 --- a/packages/databricks-vscode/.vscode/settings.json +++ b/packages/databricks-vscode/.vscode/settings.json @@ -12,5 +12,8 @@ "editor.defaultFormatter": "esbenp.prettier-vscode", "[javascript]": { "editor.defaultFormatter": "esbenp.prettier-vscode" + }, + "[xml]": { + "editor.defaultFormatter": "redhat.vscode-xml" } } diff --git a/packages/databricks-vscode/.vscodeignore b/packages/databricks-vscode/.vscodeignore index 2d5a00b0b..82813923e 100644 --- a/packages/databricks-vscode/.vscodeignore +++ b/packages/databricks-vscode/.vscodeignore @@ -15,4 +15,7 @@ scripts/** coverage/ .nyc_output/ logs/ -extension/ \ No newline at end of file +extension/ +**/*.vsix +.build/ +tmp/** diff --git a/packages/databricks-vscode/CHANGELOG.md b/packages/databricks-vscode/CHANGELOG.md index a0b4fe37f..d11d9c0b3 100644 --- a/packages/databricks-vscode/CHANGELOG.md +++ b/packages/databricks-vscode/CHANGELOG.md @@ -1,50 +1,227 @@ -# Release: v1.4.0 +# Release: v2.4.7 ## packages/databricks-vscode -## 1.4.0 (2024-08-28) +## (2024-10-24) -- Added a notification about the upcoming V2 release: - > **Version 2 of the extension will soon be made the default. With this update it is easier to set up your project, integrate with Databricks Asset Bundles, and run your code remotely. [Learn more](https://docs.databricks.com/dev-tools/vscode-ext/index.html).** +- Don't initialise spark progress widget if it's not supported +- Fix CLI cancellation on windows +- Focus configuration view when users attempt to login or setup Databricks Connect +- Let users install Databricks Connect even if python version doesn't match DBR requirements +- Show login command in the run button conext menu if the extension is logged out +- Don't show error notifications during login process if `.databrickscfg` file doesn't exist +- Prevent welcome view flashes when opening the configuration panel +- Update the CLI to v0.231.0 +- Use `bundle sync` instead of `bundle deploy` for remote run commands -# Release: v1.3.1 +# Release: v2.4.6 ## packages/databricks-vscode -## 1.3.1 (2024-07-03) +## (2024-10-15) -- Fix loading of environment variables for notebook execution -- Update Databricks CLI to v0.218.1 +- Update CLI to 0.230, use verbose deploy command -# Release: v1.3.0 +# Release: v2.4.5 ## packages/databricks-vscode -## 1.3.0 (2024-03-19) +## (2024-10-10) -- Fix: Add exception handlers to bootstrap python code, closes [#1123](https://github.com/databricks/databricks-vscode/issues/1123) -- Update Databricks CLI to v0.215.0 -- Feature: Add support for reading custom CA from system keystore. -- Feature: Add support for disabling SSL from VS Code system configuration. NOTE: We do not recommend disabling SSL. +- Use saved profile from the legacy config -# Release: v1.2.7 +# Release: v2.4.4 ## packages/databricks-vscode -## 1.2.7 (2024-02-05) +## (2024-09-26) -- Fix: Databricks OAuth U2M on GCP. -- Fix: "Fetch failed" issue when using a proxy. This is fixed by using undici instead of native fetch. -- List profiles with all auth methods. +# Release: v2.4.3 -# Release: v1.2.6 +## packages/databricks-vscode + +## (2024-09-25) + +- Update Databricks CLI to 228.1 +- Cancel workflow run if the webview panel is closed before the run even started +- Add DBConnect Progress widget +- Let users cancel `deploy` and `destroy` bundle operations + +# Release: v2.4.2 + +## packages/databricks-vscode + +## (2024-09-06) + +- Remove README note about upcoming release + +# Release: v2.4.1 + +## packages/databricks-vscode + +## (2024-09-05) + +- Bump CLI to 0.228.0 + +# Release: v2.4.0 + +## packages/databricks-vscode + +## (2024-08-26) + +- Remove private preview warning +- Bump CLI to 0.227.1 + +# Release: v2.3.4-preview + +## packages/databricks-vscode + +## (2024-08-30) + +- Fix the marketplace note + +# Release: v2.3.3-preview + +## packages/databricks-vscode + +## (2024-08-30) + +- Update marketplace note + +# Release: v2.3.2-preview + +## packages/databricks-vscode + +## (2024-08-22) + +- Allow cancelling login, fix spaces in path for dbconnect and minor UI fixes +- Bump CLI to 0.227 +- Cleanup redundant commands and fix errors when resetting bundle variables +- Fix deployment tag and README links on Marketplace +- Fix run button visibility logic +- Use Info log level for the CLI stderr + +# Release: v2.3.1-preview + +## packages/databricks-vscode + +## (2024-08-13) + +- Fix: Allow CLI path to have spaces. +- Fix: Show the correct title for Cluster Selector. +- Fix: Check whether local python version matches version required by selected cluster for Databricks Connect v2. +- Update CLI to v0.225.0. + +# Release: v2.3.0-preview + +## packages/databricks-vscode + +## (2024-07-18) + +- Bring back sync functionality. +- Show correct default value for variables in bundle variable UI. +- Update CLI to v0.223.2. + +# Release: v2.2.2-preview + +## packages/databricks-vscode + +## (2024-07-03) + +- Fix CLI output parsing + +# Release: v2.2.1-preview + +## packages/databricks-vscode + +## (2024-06-27) + +- Add exception handlers to bootstrap python code + +# Release: v2.2.0-preview ## packages/databricks-vscode -## 1.2.6 (2024-01-31) +## (2024-06-26) + +- Add cwd and project root to sys.path for dbconnect runner +- Add support for multiple vscode workspaces +- Update CLI to 0.221.0 + +# Release: v2.1.2-preview + +## packages/databricks-vscode + +## (2024-05-06) + +- Bring back `login` public API +- Install dbconnect in a child process + +# Release: v2.1.1-preview + +## packages/databricks-vscode + +## (2024-05-02) + +- Add support for `--force-lock` for deploy and destroy +- Add support for `bundle destroy` command +- Cleanup extension commands +- Export `DATABRICKS_CLI_UPSTREAM` to the terminals +- Update CLI to 0.219.0 + +# Release: v2.1.0-preview + +## packages/databricks-vscode + +## (2024-04-24) + +- Feature: Add a interface for specifying bundle variables. +- Feature: Allow opting out of cluster override and make it more visible in UI. +- Feature: Update databricks CLI to v0.218.0. Databricks Asset Bundles (DABs) are now GA! +- Feature: Add UI and wizard to help manage virtual environments and Databricks Connect v2 versions. + +# Release: v2.0.4-preview + +## packages/databricks-vscode + +## (2024-04-09) + +- Fix: avoid terraform errors on DABs projects with older version of databricks terraform provider + +# Release: v2.0.3-preview + +## packages/databricks-vscode + +## (2024-04-08) + +- Bundle cli dependencies + +# Release: v2.0.2-preview + +## packages/databricks-vscode + +## (2024-04-03) + +- Fix: Add currently selected python environment to path for wheel builds. +- Fix: Add extension name to the private preview terms and conditions popup. +- Bump databricks cli to v0.216.0. +- Revamp the welcome views so that users can see all the critical actions in all scenarios. +- Fix: Ignore stderr for validate and summary commands +- Fix: Use packaged CLI if a cli path is not specified in .databrickscfg profile + +# Release: v2.0.1-preview + +## packages/databricks-vscode + +## v2.0.1-preview (2024-03-07) + +- Databricks Asset Bundles (DABs) are now available in VS Code which allows you to: + - easily set up, author and run Databricks projects from VS Code. + - leverage the DABs Resource Explorer so you can easily see all your Jobs and Pipelines in one place and run them with one click. +- All our run methods are now consolidated into 1 run menu. +- Update databricks cli to v0.215.0. -- Update Databricks SDK to 0.6.0 (#1023) ([14178ab](https://github.com/databricks/databricks-vscode/commit/14178ab)), closes [#1023](https://github.com/databricks/databricks-vscode/issues/1023) -- Update Databricks CLI to v0.212.3 +dabs_demo # Release: v1.2.5 diff --git a/packages/databricks-vscode/DATABRICKS.quickstart.md b/packages/databricks-vscode/DATABRICKS.quickstart.md index cb746fd82..8acc6a306 100644 --- a/packages/databricks-vscode/DATABRICKS.quickstart.md +++ b/packages/databricks-vscode/DATABRICKS.quickstart.md @@ -1,100 +1,134 @@ -# Databricks Extension for Visual Studio Code +# Databricks extension for Visual Studio Code -The Databricks extension for VS Code allows you to develop for the Databricks Lakehouse platform from VS Code. +The Databricks extension for Visual Studio Code enables you to connect to your remote Databricks workspaces from Visual Studio Code. > 📘 **Note**: The [User Guide](https://docs.databricks.com/dev-tools/vscode-ext.html) contains comprehesive documentation about the Databricks extension. # Features -- Synchronize code to a Databricks workspace -- Run Python files on a Databricks cluster -- Run notebooks and Python files as Workflows +- Define, deploy, and run Databricks Asset Bundles to apply CI/CD patterns to your Databricks jobs, Delta Live Tables pipelines, and MLOps Stacks. +- Run local Python code files on Databricks clusters. +- Run notebooks and local Python code files as Databricks jobs. +- Set up and configure your debugging environment and Databricks Connect using a simple checklist that triggers selection dialogs. +- Debug notebooks cell by cell with Databricks Connect. +- Synchronize local code with code in your Databricks workspace. ## Table of Contents - [Getting Started](#setup-steps) - - [Configure Extension](#configure-extension) - - [Running Code](#running-code) - - [Running PySpark Code](#running-pyspark-code) - - [Running PySpark Code and Notebooks as Workflows](#running-code-as-workflows) - - [Advanced: Running using custom run configurations](#run-configurations) -- [Extension Settings](#settings) -- [`Databricks:` Commands](#commands) + - [Create a Databricks project](#create-databricks-project) + - [Run Python code](#running-code) + - [Running Python files](#running-pyspark-code) + - [Running Notebooks as Workflows](#running-code-as-workflows) + - [Debugging and running Notebooks cell-by-cell using Databricks Connect](#running-notebook) + - [Deploying Databricks Asset Bundles](#dabs) + - [What are Databricks Asset Bundles?](#what-is-dab) + - [Deploying Databricks Asset Bundles](#deploy-dab) + - [Run a Job or Pipeline](#deploy-run-job-pipeline) +- [Changes from v1](#changes-from-v1) + - [Migrate a project from Databricks extension v1 to v2](#migrate-from-v1) + - [What is databricks.yml?](#what-is-databricksyml) + - [No environment variables in terminals](#no-env-vars) --- # Getting Started -## Configure Extension +## Create a Databricks project -1. Open the Databricks panel by clicking on the Databricks icon on the left -2. Click the "Configure Databricks" button -3. Follow the wizard to select or configure a CLI profile -4. Click the "gear" icon in the clusters tree item to select an interactive cluster for running code on - 1. You can also select the first entry in the list to create a new cluster. Selecting the item will take you into the Databricks web application. - 2. We recommend creating a Personal Compute Cluster. -5. Click the "gear" icon in the Repo tree item to select a repo to sync code to - 1. You can also select the first entry in the list to create a new Databricks repo +1. Open the Databricks extension panel by clicking on the Databricks icon on the left sidebar. +2. Click on the "Create a new Databricks project" button. +3. Follow the selection dialogs to create a Databricks configuration profile or select an existing one. +4. Select a folder to create your project in. +5. Follow the selection dialogs to create a new Databricks project. +6. Select the newly created project to open it, using the selector that appears. +7. VS Code will reopen with the new project loaded, and the extension will automatically login using the selected profile. + +![create-databricks-project](./images/dabs_vsc.gif) + +If your folder has multiple [Databricks Asset Bundles](#dabs), you can select which one to use by clicking "Open Existing Databricks project" button and selecting the desired project. -![configure](./images/configure.gif) +## Select a cluster + +The extension uses an interactive cluster to run code. To select an interactive cluster: + +1. Open the Databricks panel by clicking on the Databricks icon on the left +2. Click on the "Select Cluster" button. + - If you wish to change the selected cluster, click on the "Configure Cluster" gear icon, next to the name of the selected cluster. -## Running Code +## Run Python code -Once you have your project configured you can sync your local code to the repo and run it on a cluster. You can use the https://github.com/databricks/ide-best-practices repository as an example. +Once you have your project configured you can deploy your local code to the selected Databricks workspace and run it on a cluster. -### Running PySpark code +### Running Python files 1. Create python file 2. Add PySpark code to the python file. -3. Click the "Run" icon in the tab bar and select "Upload and Run File on Databricks" +3. Click the "Databricks Run" icon in the tab bar and select "Upload and Run File on Databricks" -This will start the code synchronization and run the active python file on the configured cluster. The result is printed in the "debug" output panel. +This will deploy the code to the selected Databricks workspace and run it on the cluster. The result is printed in the "debug" output panel. -![run](./images/run.gif) +![run-python-code](./images/cmd-exec-run.gif) -### Running PySpark and notebooks as a Workflow +### Running Notebooks as a Workflow 1. Create a python file or a python based notebook 1. You can create a python based notebook by exporting a notebook from the Databricks web application or use a notebook that is already tracked in git, such as https://github.com/databricks/notebook-best-practices -2. Click the "Run" icon in the tab bar and select "Run File as Workflow on Databricks" +2. Click the "Databricks Run" icon in the tab bar and select "Run File as Workflow on Databricks" This will run the file using the Jobs API on the configured cluster and render the result in a WebView. -### Advanced: Running using custom run configurations +![run-as-workflow](./images/run-as-workflow.gif) + +### Debugging and running Notebooks cell-by-cell using Databricks Connect + +The extension provides easy setup for cell-by-cell running and debugging notebooks locally using Databricks Connect. For more details on how to set up Databricks Connect, refer to the [full docs](https://docs.databricks.com/en/dev-tools/vscode-ext/notebooks.html). + +## Deploying Databricks Asset Bundles + +### What are Databricks Asset Bundles? + +Databricks Asset Bundles make it possible to describe Databricks resources such as jobs, pipelines, and notebooks as source files. These source files provide an end-to-end definition of a project, including how it should be structured, tested, and deployed, which makes it easier to collaborate on projects during active development. For more information, see [Databricks Asset Bundles](https://docs.databricks.com/en/dev-tools/bundles/index.html). + +### Deploying Databricks Asset Bundles? + +1. In the Databricks extension panel, find the "Bundle Resource Explorer" view. +2. Click on the "Deploy" button. +3. You can monitor the deployment status in the log output window. + +![deploy](./images/deploy.gif) + +### Run a Job or Pipeline + +You can run a job or a pipeline managed by Databricks Asset Bundles, from the "Bundle Resource Explorer" view. + +1. In the Databricks extension panel, find the "Bundle Resource Explorer" view. +2. Hover over the job or pipeline that you want to run. +3. Click on the "Run" button. + +This deploys the bundle and runs the job or pipeline. You can monitor the run progress in the output terminal window. You can also open the run, job or pipeline in workspace by clicking on the "Open link externally" button. + +![run-job-pipeline](./images/deploy-and-run.gif) + +#### Use the interactive cluster for running jobs + +By default, a job is run using a jobs cluster. You can change this behavior and use the interactive cluster selected previously ([Select a cluster](#select-cluster)) to run the job. + +1. In the Databricks extension panel, find the "Configuration" view. +2. Check the "Override Jobs cluster in bundle" checkbox. -Both ways of running code on a cluster are also available in custom run configurations. In the "Run and Debug" panel you can click "Add configuration..." and select either "Databricks: Launch" or "Databricks: Launch as Workflow". Using run configuration you can also pass in command line arguments and run your code by simply pressing `F5`. +# Key behavior changes for users of Databricks extension v1 -![configure](./images/custom-runner.gif) +## Migrate a project from Databricks extension v1 to v2 -## Extension Settings +If you are using Databricks extension v1, your project will automatically be migrated a [Databricks Asset Bundle](#what-is-dab) when you open it in v2. The migration process will create a new [`databricks.yml`](#what-is-databricksyml) file in the root of your project and move the configurations from the old `.databricks/project.json` to the new `databricks.yml` file. -This extension contributes the following settings: +> **Note**: This means that you will start seeing a `databricks.yml` file in your project root directory and in your version control system change logs. We recommend comitting this file to your version control system. -- `databricks.logs.maxFieldLength`: The maximum length of each field displayed in logs outputs panel -- `databricks.logs.truncationDepth`: The max depth of logs to show without truncation -- `databricks.logs.maxArrayLength`: The maximum number of items to show for array fields -- `databricks.logs.enabled`: Enable/disable logging. Reload window for changes to take effect -- `databricks.clusters.onlyShowAccessibleClusters`: Only show clusters that the user has access to +## What is databricks.yml? -## `Databricks:` Commands +A `databricks.yml` file is a configuration file that describes a bundle. It contains the configuration such as the workspace host and definitions of resources such as jobs and pipelines. For more information on `databricks.yml`, refer to the [full docs](https://docs.databricks.com/en/dev-tools/bundles/index.html). -The Databricks extension provides commands (prefixed with `Databricks:`) to the VS Code _command -palette_, available by selecting _View > Command Palette_ or by typing -`CTRL-SHIFT-p` (macOS: `CMD-SHIFT-p`). +## No environment variables in terminals -| Databricks Command | Description | -| :----------------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------- | -| `Databricks: Configure workspace` | Configure the Databricks workspace to use for the current project | -| `Databricks: Logout` | Logs you out from your Databricks workspace | -| `Databricks: Configure cluster` | Select an interactive cluster to use for running PySpark code in this project | -| `Databricks: Detach cluster` | Detach configured cluster | -| `Databricks: Configure sync destination` | Configure target directory for synchronizing code to the configured Databricks workspace | -| `Databricks: Detach sync destination` | Detach the configured sync destination | -| `Databricks: Start synchronization` | Start synchronizing local code to the Databricks workspace. This command performs an incremental sync. | -| `Databricks: Start synchronization (full sync)` | Start synchronizing local code to the Databricks workspace. This command performs full sync even if an incremental sync is possible. | -| `Databricks: Stop synchronization` | Stop sync process. | -| `Databricks: Upload and Run File on Databricks` | Runs the selected Python file on the configured Databricks cluster | -| `Databricks: Run File as Workflow on Databricks` | Runs the selected Python file as a Workflow in the configured Databricks cluster | -| `Databricks: Show Quickstart` | Show the Quickstart panel | -| `Databricks: Open Databricks configuration file` | Opens the Databricks configuration file for the current project | -| `Databricks: Open full log` | Opens the log output folder for the current project | +Environment variables in terminals is no longer supported. If you were using environment variables in v1, you will need to manually load the `.databricks/.databricks.env` file in your terminal before running any commands. diff --git a/packages/databricks-vscode/NOTICE.md b/packages/databricks-vscode/NOTICE.md index 8676eb248..f9aa0166f 100644 --- a/packages/databricks-vscode/NOTICE.md +++ b/packages/databricks-vscode/NOTICE.md @@ -6,147 +6,102 @@ This Software includes software developed at Databricks (https://www.databricks. This Software contains code from the following open source projects: -| Name | Installed version | License | Code | -| :----------------------------------------------------------------------------------------------------------------------------- | :---------------- | :----------- | :--------------------------------------------------------------------------------------------------------- | -| [@azure/abort-controller](https://www.npmjs.com/package/@azure/abort-controller) | 1.1.0 | MIT | github:Azure/azure-sdk-for-js | -| [@azure/core-auth](https://www.npmjs.com/package/@azure/core-auth) | 1.5.0 | MIT | github:Azure/azure-sdk-for-js | -| [@azure/core-rest-pipeline](https://www.npmjs.com/package/@azure/core-rest-pipeline) | 1.10.1 | MIT | github:Azure/azure-sdk-for-js | -| [@azure/core-tracing](https://www.npmjs.com/package/@azure/core-tracing) | 1.0.1 | MIT | github:Azure/azure-sdk-for-js | -| [@azure/core-util](https://www.npmjs.com/package/@azure/core-util) | 1.2.0 | MIT | 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a/packages/databricks-vscode/eslint-local-rules/rules/mutexSynchronisedDecorator.ts b/packages/databricks-vscode/eslint-local-rules/rules/mutexSynchronisedDecorator.ts new file mode 100644 index 000000000..dd6739381 --- /dev/null +++ b/packages/databricks-vscode/eslint-local-rules/rules/mutexSynchronisedDecorator.ts @@ -0,0 +1,78 @@ +/* eslint-disable no-console */ +import {ESLintUtils, AST_NODE_TYPES} from "@typescript-eslint/utils"; + +const rule = ESLintUtils.RuleCreator.withoutDocs({ + create(context) { + return { + // eslint-disable-next-line @typescript-eslint/naming-convention + Decorator(node) { + if ( + node.expression.type === "CallExpression" && + node.expression.callee.type === + AST_NODE_TYPES.MemberExpression && + node.expression.callee.object.type === + AST_NODE_TYPES.Identifier && + node.expression.callee.object.name === "Mutex" && + node.expression.callee.property.type === + AST_NODE_TYPES.Identifier && + node.expression.callee.property.name === "synchronise" && + node.expression.arguments.length > 0 + ) { + const mutexName = + node.expression.arguments[0].type === + AST_NODE_TYPES.Literal + ? (node.expression.arguments[0].value as string) + : ""; + + if (node.parent.parent?.type !== AST_NODE_TYPES.ClassBody) { + return context.report({ + node, + messageId: "decoratorNotInClass", + }); + } + + const exists = node.parent.parent.body.some((element) => { + return ( + (element.type === + AST_NODE_TYPES.PropertyDefinition || + element.type === + AST_NODE_TYPES.TSAbstractPropertyDefinition) && + element.key.type === AST_NODE_TYPES.Identifier && + element.key.name === mutexName + ); + }); + + const className = + node.parent.parent.parent?.type === + AST_NODE_TYPES.ClassDeclaration + ? node.parent.parent.parent.id?.name + : undefined; + + if (!exists) { + return context.report({ + node, + messageId: "synchronisedMutexNotInClass", + data: { + mutexName, + className, + }, + }); + } + } + }, + }; + }, + meta: { + type: "problem", + schema: [], + messages: { + decoratorNotInClass: + "Mutex.synchronized() should be used inside a class", + synchronisedMutexNotInClass: + 'Mutex "{{mutexName}}" is not defined in class "{{className}}".', + }, + }, + defaultOptions: [], +}); + +export default rule; diff --git a/packages/databricks-vscode/eslint-local-rules/tsconfig.json b/packages/databricks-vscode/eslint-local-rules/tsconfig.json new file mode 100644 index 000000000..02566e202 --- /dev/null +++ b/packages/databricks-vscode/eslint-local-rules/tsconfig.json @@ -0,0 +1,6 @@ +{ + "transpileOnly": true, + "compilerOptions": { + "module": "Node16" + } +} diff --git a/packages/databricks-vscode/images/cmd-exec-run.gif b/packages/databricks-vscode/images/cmd-exec-run.gif new file mode 100644 index 0000000000000000000000000000000000000000..4ac4941e2fdb56a77cfbe2634a869f8266036ec9 GIT binary patch literal 1642113 zcmW(+hdcvS)~l zkgo3U^ZlJa;5^Q2pV#yCd}(N^%gWh>-jyY~Vh8^JzyJUZ0C)fd03a9uLIWT?00jUj z41l5mC>}rn00IUe&;SAtpa1{`15juHg$FPIfPn!RG=RYaSOCDn04y57;sG20;9vj_ z4dC$qyAptb05k}|gFpZX1OtK4AP^n|1wc?32#N+l@gM{MLcl->GzftQp#TsH2121h zC_D%QfG{u+1`WdCL0ABUg@LeW5Ec)@0U#U0E&e{v1lk3 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"workspaceFolderCount > 0 && !databricks.context.initialized" + }, + { + "view": "configurationView", + "contents": "There are multiple Databricks projects in the folder:\n[Open existing Databricks Project](command:databricks.bundle.openSubProject)", + "when": "workspaceFolderCount > 0 && databricks.context.initialized && databricks.context.subProjectsAvailable" + }, + { + "view": "configurationView", + "contents": "Migrate current folder to a Databricks Project: \n[Migrate current folder to a Databricks Project](command:databricks.bundle.startManualMigration)", + "when": "workspaceFolderCount > 0 && databricks.context.initialized && databricks.context.pendingManualMigration" + }, + { + "view": "configurationView", + "contents": "[Create a new Databricks Project](command:databricks.bundle.initNewProject)", + "when": "workspaceFolderCount > 0 && databricks.context.initialized && !databricks.context.isBundleProject" + }, + { + "view": "configurationView", + "contents": "Loading configuration", + "when": "workspaceFolderCount > 0 && databricks.context.initialized && databricks.context.isBundleProject" }, { "view": "configurationView", - "contents": "Please open a folder to start using Databricks on VSCode.\n[Open Folder](command:vscode.openFolder)", + "contents": "This folder is empty.\n[Create a new Databricks Project](command:databricks.bundle.initNewProject)", "when": "workspaceFolderCount == 0" + }, + { + "view": "configurationView", + "contents": "To learn more about how to use Databricks with VS Code [read our docs](https://docs.databricks.com/dev-tools/vscode-ext.html) or [Quickstart guide](command:databricks.quickstart.open)" } ], "menus": { "view/title": [ { - "command": "databricks.connection.configureWorkspace", - "when": "view == configurationView", - "group": "navigation@3" + "command": "databricks.quickstart.open", + "when": "view == configurationView" }, { - "command": "databricks.quickstart.open", + "command": "databricks.bundle.initNewProject", + "group": "navigation@1", "when": "view == configurationView" }, { @@ -290,6 +457,39 @@ "command": "databricks.wsfs.createFolder", "when": "view == workspaceFsView", "group": "navigation@1" + }, + { + "command": "databricks.bundle.refreshRemoteState", + "when": "view == dabsResourceExplorerView && databricks.context.bundle.deploymentState == idle", + "group": "navigation@1" + }, + { + "command": "databricks.bundle.deploy", + "when": "view == dabsResourceExplorerView && databricks.context.bundle.deploymentState == idle", + "group": "navigation@1" + }, + { + "command": "databricks.bundle.destroy", + "when": "view == dabsResourceExplorerView && databricks.context.bundle.deploymentState == idle", + "group": "navigation@1" + }, + { + "command": "databricks.bundle.forceDeploy", + "when": "view == dabsResourceExplorerView && databricks.context.bundle.deploymentState == idle" + }, + { + "command": "databricks.bundle.forceDestroy", + "when": "view == dabsResourceExplorerView && databricks.context.bundle.deploymentState == idle" + }, + { + "command": "databricks.bundle.variable.openFile", + "when": "view == dabsVariableView && databricks.context.bundle.deploymentState == idle", + "group": "navigation@1" + }, + { + "command": "databricks.bundle.variable.reset", + "when": "view == dabsVariableView && databricks.context.bundle.deploymentState == idle", + "group": "navigation@1" } ], "databricks.cluster.filter": [ @@ -306,70 +506,114 @@ "view/item/context": [ { "command": "databricks.utils.openExternal", - "when": "view == configurationView && viewItem == workspace || view == configurationView && viewItem =~ /^.*cluster.*$/ || view == configurationView && viewItem =~ /^sync.*$/", + "when": "viewItem =~ /^databricks.*\\.(has-url).*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@1" }, { - "command": "databricks.utils.openExternal", - "when": "view == clusterView && viewItem == cluster", - "group": "inline@1" + "command": "databricks.connection.attachCluster", + "when": "view == clusterView && databricks.context.bundle.deploymentState == idle", + "group": "inline@2" }, { - "command": "databricks.connection.attachCluster", - "when": "view == clusterView", + "command": "databricks.connection.bundle.selectTarget", + "when": "view == configurationView && viewItem =~ /^databricks.configuration.target.*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@2" }, { - "command": "databricks.connection.configureWorkspace", - "when": "view == configurationView && viewItem == workspace", + "command": "databricks.connection.configureLogin", + "when": "view == configurationView && viewItem =~ /^databricks.configuration.authType.*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@2" }, { "command": "databricks.connection.attachClusterQuickPick", - "when": "view == configurationView && viewItem == clusterDetached || view == configurationView && viewItem =~ /^databricks.cluster.*$/", + "when": "view == configurationView && viewItem =~ /^databricks.configuration.cluster.*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@2" }, { - "command": "databricks.connection.attachSyncDestination", - "when": "view == configurationView && viewItem == syncDetached", - "group": "inline@2" + "command": "databricks.cluster.stop", + "when": "view == configurationView && viewItem =~ /^databricks.configuration.cluster.*\\.(running|pending).*$/ && databricks.context.bundle.deploymentState == idle", + "group": "inline@0" }, { - "command": "databricks.connection.attachSyncDestination", - "when": "view == configurationView && viewItem == syncStopped || view == configurationView && viewItem == syncRunning", - "group": "inline@2" + "command": "databricks.cluster.start", + "when": "view == configurationView && viewItem =~ /databricks.configuration.cluster.*\\.terminated.*/ && databricks.context.bundle.deploymentState == idle", + "group": "inline@0" }, { - "command": "databricks.sync.start", - "when": "view == configurationView && viewItem == syncStopped", + "command": "databricks.bundle.deployAndRun", + "when": "view == dabsResourceExplorerView && viewItem =~ /^databricks.bundle.*.runnable.*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@0" }, { - "command": "databricks.sync.stop", - "when": "view == configurationView && viewItem == syncRunning", + "command": "databricks.bundle.cancelRun", + "when": "view == dabsResourceExplorerView && viewItem =~ /^databricks.bundle.*.cancellable.*$/ && databricks.context.bundle.deploymentState == idle", "group": "inline@0" }, { - "command": "databricks.cluster.stop", - "when": "view == configurationView && viewItem =~ /^databricks.cluster.(running|pending)$/", + "command": "databricks.utils.copy", + "when": "view == dabsResourceExplorerView || view == configurationView" + }, + { + "command": "databricks.environment.refresh", + "when": "view == configurationView && viewItem =~ /^databricks.environment.root.(success|error)$/", + "group": "inline@0", + "icon": "$(refresh)" + }, + { + "command": "databricks.environment.selectPythonInterpreter", + "when": "view == configurationView && viewItem =~ /^databricks.environment.checkPythonEnvironment.success$/", + "group": "inline@0", + "icon": "$(gear)" + }, + { + "command": "databricks.environment.reinstallDBConnect", + "when": "view == configurationView && viewItem =~ /^databricks.environment.checkEnvironmentDependencies.success$/", + "group": "inline@0", + "icon": "$(gear)" + }, + { + "command": "databricks.sync.start", + "when": "view == configurationView && viewItem =~ /^databricks.*sync.*is-stopped.*$/ && databricks.context.bundle.isDevTarget", "group": "inline@0" }, { - "command": "databricks.cluster.start", - "when": "view == configurationView && viewItem == databricks.cluster.terminated", + "command": "databricks.sync.stop", + "when": "view == configurationView && viewItem =~ /^databricks.*sync.*is-running.*$/ && databricks.context.bundle.isDevTarget", "group": "inline@0" } ], - "editor/title/run": [ + "editor/title": [ + { + "submenu": "databricks.run", + "group": "navigation@0", + "when": "databricks.context.isActiveFileInActiveWorkspace && databricks.context.showRunAsWorkflow || databricks.context.isActiveFileInActiveWorkspace && resourceExtname == .ipynb" + } + ], + "databricks.run": [ + { + "command": "databricks.connection.configureLogin", + "when": "databricks.context.activated && !databricks.context.loggedIn", + "group": "1_login@0" + }, { "command": "databricks.run.runEditorContents", - "when": "resourceLangId == python", - "group": "navigation@1" + "when": "databricks.context.activated && resourceLangId == python", + "group": "2_remote@1" }, { "command": "databricks.run.runEditorContentsAsWorkflow", - "when": "resourceLangId == python || resourceLangId == scala || resourceLangId == r || resourceLangId == sql || resourceExtname == .ipynb", - "group": "navigation@1" + "when": "databricks.context.activated && resourceLangId == python || resourceExtname == .ipynb || databricks.context.showRunAsWorkflow", + "group": "2_remote@2" + }, + { + "command": "databricks.run.dbconnect.debug", + "when": "databricks.context.activated && resourceLangId == python", + "group": "3_local@1" + }, + { + "command": "databricks.run.dbconnect.run", + "when": "databricks.context.activated && resourceLangId == python", + "group": "3_local@2" } ], "commandPalette": [ @@ -379,7 +623,7 @@ }, { "command": "databricks.run.runEditorContentsAsWorkflow", - "when": "resourceLangId == python || resourceExtname == .ipynb" + "when": "resourceLangId == python || resourceExtname == .ipynb || databricks.context.showRunAsWorkflow" }, { "command": "databricks.wsfs.createFolder", @@ -396,16 +640,24 @@ { "command": "databricks.call", "when": "false" + }, + { + "command": "databricks.bundle.deployAndRun", + "when": "false" + }, + { + "command": "databricks.bundle.cancelRun", + "when": "false" + }, + { + "command": "databricks.utils.copy", + "when": "false" } ], "explorer/context": [ { - "command": "databricks.run.runEditorContents", - "when": "resourceLangId == python" - }, - { - "command": "databricks.run.runEditorContentsAsWorkflow", - "when": "resourceLangId == python" + "submenu": "databricks.run", + "when": "resourceLangId == python || resourceExtname == .ipynb || databricks.context.showRunAsWorkflow" } ] }, @@ -414,6 +666,14 @@ "id": "databricks.cluster.filter", "label": "Filter clusters ...", "icon": "$(filter)" + }, + { + "id": "databricks.run", + "label": "Run on Databricks", + "icon": { + "dark": "resources/dark/databricks-run-icon.svg", + "light": "resources/light/databricks-run-icon.svg" + } } ], "taskDefinitions": [ @@ -555,6 +815,19 @@ } } ] + }, + { + "type": "python", + "configurationAttributes": { + "launch": { + "properties": { + "databricks": { + "type": "boolean", + "description": "Setup databricks environment variables and globals." + } + } + } + } } ], "configuration": [ @@ -586,19 +859,6 @@ "default": false, "description": "Enable/disable filtering for only accessible clusters (clusters on which the current user can run code)" }, - "databricks.sync.destinationType": { - "type": "string", - "default": "workspace", - "enum": [ - "workspace", - "repo" - ], - "description": "Use a folder in Workspace or a Databricks Repo as sync destination (Reload for changes to take effect).", - "enumDescriptions": [ - "Use a folder in Workspace as sync destination", - "Use a Repo as sync destination" - ] - }, "databricks.overrideDatabricksConfigFile": { "type": "string", "default": "", @@ -609,12 +869,10 @@ "default": [], "items": { "enum": [ - "notebooks.dbconnect", "views.cluster", "views.workspace" ], "enumDescriptions": [ - "Limited local notebook support using DB Connect v2.", "Show cluster view in the explorer.", "Show workspace browser in the explorer." ], @@ -623,19 +881,24 @@ "uniqueItems": true, "description": "Opt into experimental features." }, - "databricks.python.envFile": { - "type": "string", - "default": "", - "description": "Similar to python.envFile. Absolute path to a file containing environment variable definitions." - }, "databricks.wsfs.rearrangeCells": { "type": "boolean", "default": true, "description": "Enable/disable rearranging cells in wrapper files created when using `workspace` as the sync destination. **Note:** It is recommended to NOT disable this setting. If you do disable it, you will need to manually handle sys.path for local imports in your notebooks." }, + "databricks.connect.progress": { + "type": "boolean", + "default": true, + "markdownDescription": "Show PySpark progress bar when using Databricks Connect. Requires `ipywidgets` package and `pyspark@3.5.0+`." + }, "databricks.ipythonDir": { "type": "string", "description": "Absolute path to a directory for storing IPython files. Defaults to IPYTHONDIR environment variable (if set) or ~/.ipython." + }, + "databricks.bundle.remoteStateRefreshInterval": { + "type": "number", + "default": 5, + "description": "The interval in minutes at which the remote state of the bundle is refreshed." } } } @@ -643,14 +906,15 @@ }, "extensionDependencies": [ "ms-python.python", - "ms-toolsai.jupyter" + "ms-toolsai.jupyter", + "redhat.vscode-yaml" ], "vsce": { "dependencies": false, "useYarn": false }, "cli": { - "version": "0.218.1" + "version": "0.231.0" }, "scripts": { "vscode:prepublish": "rm -rf out && yarn run package:compile && yarn run package:wrappers:write && yarn run package:jupyter-init-script:write && yarn run package:copy-webview-toolkit && yarn run generate-telemetry", @@ -661,23 +925,24 @@ "package:darwin:arm64": "./scripts/package-vsix.sh darwin-arm64", "package:win32:x64": "./scripts/package-vsix.sh win32-x64", "package:win32:arm64": "./scripts/package-vsix.sh win32-arm64", - "package:all": "yarn run package:linux:x64 && yarn run package:linux:arm64 && yarn run package:darwin:x64 && yarn run package:darwin:arm64 && yarn run package:win32:x64 && yarn run package:win32:arm64", + "package:all": "rm -rf ./.build/ && yarn run package:linux:x64 && yarn run package:linux:arm64 && yarn run package:darwin:x64 && yarn run package:darwin:arm64 && yarn run package:win32:x64 && yarn run package:win32:arm64", "package:cli:fetch": "bash ./scripts/fetch-databricks-cli.sh ${CLI_ARCH:-}", "package:cli:link": "rm -f ./bin/databricks && mkdir -p bin && ln -s ../../../../cli/cli bin/databricks", "package:wrappers:write": "ts-node ./scripts/writeIpynbWrapper.ts -s ./resources/python/notebook.workflow-wrapper.py -o ./resources/python/generated/notebook.workflow-wrapper.json", "package:jupyter-init-script:write": "ts-node ./scripts/writeJupyterInitFileWithVersion.ts", + "package:bundle-schema:write": "yarn package:cli:fetch && ts-node ./scripts/writeBundleSchema.ts ./bin/databricks ./src/bundle/BundleSchema.ts", "package:compile": "yarn run esbuild:base", "package:copy-webview-toolkit": "cp ./node_modules/@vscode/webview-ui-toolkit/dist/toolkit.js ./out/toolkit.js", "esbuild:base": "esbuild ./src/extension.ts --bundle --outfile=out/extension.js --external:vscode --format=cjs --platform=node --sourcemap --target=es2019", "build": "yarn run package:wrappers:write && yarn run package:jupyter-init-script:write && tsc --build --force", - "watch": "yarn run package:wrappers:write && yarn run package:jupyter-init-script:write && yarn run package:copy-webview-toolkit && tsc --build --watch --force", + "watch": "yarn run package:wrappers:write && yarn run package:jupyter-init-script:write && yarn run package:copy-webview-toolkit && tsc --build --watch --force --verbose", "fix": "eslint src --ext ts --fix && prettier . --write", "test:lint": "eslint src --ext ts && prettier . -c", "test:unit": "yarn run build && node ./out/test/runTest.js", "test:integ:prepare": "yarn run package", - "test:integ:run": "wdio run src/test/e2e/wdio.conf.ts", + "test:integ:extension": "yarn run test:integ:prepare && wdio run src/test/e2e/wdio.conf.ts", "test:integ:sdk": "ts-mocha --type-check 'src/sdk-extensions/**/*.integ.ts'", - "test:integ": "yarn run test:integ:prepare && yarn run test:integ:run && yarn run test:integ:sdk", + "test:integ": "yarn run test:integ:extension && yarn run test:integ:sdk", "test:cov": "nyc yarn run test:unit", "test": "yarn run test:lint && yarn run test:unit", "clean": "rm -rf node_modules out .vscode-test", @@ -687,56 +952,64 @@ "dependencies": { "@databricks/databricks-sdk": "file:../../vendor/databricks-sdk.tgz", "@databricks/databricks-vscode-types": "workspace:^", - "@vscode/debugadapter": "^1.61.0", - "@vscode/extension-telemetry": "^0.8.1", - "@vscode/webview-ui-toolkit": "^1.2.2", + "@types/lodash": "^4.14.202", + "@types/shell-quote": "^1.7.5", + "@vscode/debugadapter": "^1.64.0", + "@vscode/extension-telemetry": "^0.9.1", + "@vscode/webview-ui-toolkit": "^1.4.0", "add": "^2.0.6", "ansi-to-html": "^0.7.2", "bcryptjs": "^2.4.3", + "lodash": "^4.17.21", + "minimatch": "^10.0.1", + "shell-quote": "^1.8.1", "triple-beam": "^1.4.1", - "winston": "^3.10.0", - "yaml": "^2.3.2" + "winston": "^3.11.0", + "yaml": "^2.3.4" }, "devDependencies": { "@istanbuljs/nyc-config-typescript": "^1.0.2", "@sinonjs/fake-timers": "^11.2.2", - "@types/bcryptjs": "^2.4.2", - "@types/chai": "^4.3.5", - "@types/fs-extra": "^11.0.1", - "@types/mocha": "^10.0.1", - "@types/mock-require": "^2.0.1", - "@types/node": "^20.4.2", - "@types/sinonjs__fake-timers": "^8.1.2", - "@types/tmp": "^0.2.3", - "@types/triple-beam": "^1.3.2", - "@types/vscode": "^1.69.1", - "@types/yargs": "^17.0.24", - "@typescript-eslint/eslint-plugin": "^6.0.0", - "@typescript-eslint/parser": "^6.0.0", + "@types/bcryptjs": "^2.4.6", + "@types/chai": "^4.3.11", + "@types/eslint": "^8.44.9", + "@types/fs-extra": "^11.0.4", + "@types/mocha": "^10.0.6", + "@types/mock-require": "^2.0.3", + "@types/node": "^20.10.4", + "@types/sinonjs__fake-timers": "^8.1.5", + "@types/tmp": "^0.2.6", + "@types/triple-beam": "^1.3.5", + "@types/vscode": "1.86.0", + "@types/yargs": "^17.0.32", + "@typescript-eslint/eslint-plugin": "^6.14.0", + "@typescript-eslint/parser": "^6.14.0", + "@typescript-eslint/utils": "^6.14.0", "@vscode/test-electron": "^2.3.8", - "@wdio/cli": "^8.12.2", - "@wdio/local-runner": "^8.12.1", - "@wdio/mocha-framework": "^8.12.1", - "@wdio/spec-reporter": "^8.12.2", - "@wdio/types": "^8.10.4", - "chai": "^4.3.7", - "esbuild": "^0.19.4", - "eslint": "^8.51.0", - "fs-extra": "^11.1.1", - "glob": "^10.3.3", + "@wdio/cli": "^8.35.1", + "@wdio/local-runner": "^8.35.1", + "@wdio/mocha-framework": "^8.35.0", + "@wdio/spec-reporter": "^8.32.4", + "@wdio/types": "^8.32.4", + "chai": "^4.3.10", + "esbuild": "^0.19.9", + "eslint": "^8.55.0", + "eslint-plugin-local-rules": "^2.0.1", + "fs-extra": "^11.2.0", + "glob": "^10.3.10", "mocha": "^10.2.0", "mock-require": "^3.0.3", "nyc": "^15.1.0", - "prettier": "^3.0.0", + "prettier": "^3.1.1", + "quicktype-core": "^23.0.0", "tmp-promise": "^3.0.3", "ts-mocha": "^10.0.0", "ts-mockito": "^2.6.1", - "ts-node": "^10.9.1", - "typescript": "5.1.6", + "ts-node": "^10.9.2", + "typescript": "^5.3.3", "vsce": "^2.15.0", - "wdio-video-reporter": "^4.0.3", - "wdio-vscode-service": "^5.2.3", - "winston": "^3.10.0", + "wdio-video-reporter": "^5.1.4", + "wdio-vscode-service": "^6.0.2", "yargs": "^17.7.2" }, "nyc": { diff --git a/packages/databricks-vscode/resources/dark/databricks-run-icon.svg b/packages/databricks-vscode/resources/dark/databricks-run-icon.svg new file mode 100644 index 000000000..7c971ca21 --- /dev/null +++ b/packages/databricks-vscode/resources/dark/databricks-run-icon.svg @@ -0,0 +1,18 @@ + + + + + + + + + + + + + + diff --git a/packages/databricks-vscode/resources/dark/logo.svg b/packages/databricks-vscode/resources/dark/logo.svg index b9ac42854..0f2557032 100644 --- a/packages/databricks-vscode/resources/dark/logo.svg +++ b/packages/databricks-vscode/resources/dark/logo.svg @@ -1 +1,21 @@ - \ No newline at end of file + + + + + + + + + + + + + + + diff --git a/packages/databricks-vscode/resources/dark/resource-explorer/fork.svg b/packages/databricks-vscode/resources/dark/resource-explorer/fork.svg new file mode 100644 index 000000000..5e0a73413 --- /dev/null +++ b/packages/databricks-vscode/resources/dark/resource-explorer/fork.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/dark/resource-explorer/jobs.svg b/packages/databricks-vscode/resources/dark/resource-explorer/jobs.svg new file mode 100644 index 000000000..eb820b4cf --- /dev/null +++ b/packages/databricks-vscode/resources/dark/resource-explorer/jobs.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/dark/resource-explorer/pipelines.svg b/packages/databricks-vscode/resources/dark/resource-explorer/pipelines.svg new file mode 100644 index 000000000..85722a171 --- /dev/null +++ b/packages/databricks-vscode/resources/dark/resource-explorer/pipelines.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/dark/resource-explorer/python.svg b/packages/databricks-vscode/resources/dark/resource-explorer/python.svg new file mode 100644 index 000000000..914c67d6b --- /dev/null +++ b/packages/databricks-vscode/resources/dark/resource-explorer/python.svg @@ -0,0 +1,5 @@ + + + diff --git a/packages/databricks-vscode/resources/light/databricks-run-icon.svg b/packages/databricks-vscode/resources/light/databricks-run-icon.svg new file mode 100644 index 000000000..4a76c0f0a --- /dev/null +++ b/packages/databricks-vscode/resources/light/databricks-run-icon.svg @@ -0,0 +1,18 @@ + + + + + + + + + + + + + + diff --git a/packages/databricks-vscode/resources/light/logo.svg b/packages/databricks-vscode/resources/light/logo.svg index 3fd304f7c..6b1398df7 100644 --- a/packages/databricks-vscode/resources/light/logo.svg +++ b/packages/databricks-vscode/resources/light/logo.svg @@ -1 +1,21 @@ - \ No newline at end of file + + + + + + + + + + + + + + + diff --git a/packages/databricks-vscode/resources/light/resource-explorer/fork.svg b/packages/databricks-vscode/resources/light/resource-explorer/fork.svg new file mode 100644 index 000000000..cfa468521 --- /dev/null +++ b/packages/databricks-vscode/resources/light/resource-explorer/fork.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/light/resource-explorer/jobs.svg b/packages/databricks-vscode/resources/light/resource-explorer/jobs.svg new file mode 100644 index 000000000..85553fc26 --- /dev/null +++ b/packages/databricks-vscode/resources/light/resource-explorer/jobs.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/light/resource-explorer/pipelines.svg b/packages/databricks-vscode/resources/light/resource-explorer/pipelines.svg new file mode 100644 index 000000000..e2baf133f --- /dev/null +++ b/packages/databricks-vscode/resources/light/resource-explorer/pipelines.svg @@ -0,0 +1,6 @@ + diff --git a/packages/databricks-vscode/resources/light/resource-explorer/python.svg b/packages/databricks-vscode/resources/light/resource-explorer/python.svg new file mode 100644 index 000000000..a0a16ce88 --- /dev/null +++ b/packages/databricks-vscode/resources/light/resource-explorer/python.svg @@ -0,0 +1,5 @@ + + + diff --git a/packages/databricks-vscode/resources/migration-template/databricks_template_schema.json b/packages/databricks-vscode/resources/migration-template/databricks_template_schema.json new file mode 100644 index 000000000..87afe0234 --- /dev/null +++ b/packages/databricks-vscode/resources/migration-template/databricks_template_schema.json @@ -0,0 +1,26 @@ +{ + "properties": { + "auto_migration": { + "type": "boolean", + "description": "Auto migration", + "order": 1 + }, + "project_name": { + "type": "string", + "description": "Project name", + "order": 1 + }, + "compute_id": { + "type": "string", + "description": "Compute id", + "default": "", + "order": 2 + }, + "root_path": { + "type": "string", + "description": "Root path", + "default": "", + "order": 3 + } + } +} diff --git a/packages/databricks-vscode/resources/migration-template/template/databricks.yml.tmpl b/packages/databricks-vscode/resources/migration-template/template/databricks.yml.tmpl new file mode 100644 index 000000000..efa55e805 --- /dev/null +++ b/packages/databricks-vscode/resources/migration-template/template/databricks.yml.tmpl @@ -0,0 +1,31 @@ +# This is a Databricks asset bundle definition for {{.project_name}}. +{{- if .auto_migration}} +# The file was generated automatically by the Databricks extension. +# It's based on the configuration located in `.databricks/project.json`. +# If you don't want this file to be created automatically, remove the `.databricks/project.json`. +{{- else}} +# The Databricks extension requires databricks.yml configuration file. +{{- end}} +# See https://docs.databricks.com/dev-tools/bundles/index.html for documentation. + +bundle: + name: {{.project_name}} + +targets: + dev: + mode: development + default: true + {{- if .compute_id}} + compute_id: {{.compute_id}} + {{- end}} + workspace: + host: {{workspace_host}} + {{- if .root_path}} + root_path: {{.root_path}} + {{- end}} + + ## Optionally, there could be 'staging' or 'prod' targets here. + # + # prod: + # workspace: + # host: {{workspace_host}} diff --git a/packages/databricks-vscode/resources/python/00-databricks-init.py b/packages/databricks-vscode/resources/python/00-databricks-init.py index 57d9be4e0..2fed64661 100644 --- a/packages/databricks-vscode/resources/python/00-databricks-init.py +++ b/packages/databricks-vscode/resources/python/00-databricks-init.py @@ -3,10 +3,14 @@ import json from typing import Any, Union, List import os +import sys +import time import shlex import warnings import tempfile +# prevent sum from pyskaprk.sql.functions from shadowing the builtin sum +builtinSum = sys.modules['builtins'].sum def logError(function_name: str, e: Union[str, Exception]): import sys @@ -24,6 +28,7 @@ def logError(function_name: str, e: Union[str, Exception]): try: from IPython import get_ipython + from IPython.display import display from IPython.core.magic import magics_class, Magics, line_magic, needs_local_scope except Exception as e: logError("Ipython Imports", e) @@ -101,7 +106,13 @@ def __init__(self, env_name: str, default: any = None, required: bool = False): def __get__(self, instance, owner): if self.env_name in os.environ: - return self.transform(os.environ[self.env_name]) + if self.transform is not bool: + return self.transform(os.environ[self.env_name]) + + if os.environ[self.env_name].lower() == "true" or os.environ[self.env_name] == "1": + return True + elif os.environ[self.env_name].lower() == "false" or os.environ[self.env_name] == "0": + return False if self.required: raise AttributeError( @@ -117,6 +128,7 @@ def __set__(self, instance, value): class LocalDatabricksNotebookConfig: project_root: str = EnvLoader("DATABRICKS_PROJECT_ROOT", required=True) dataframe_display_limit: int = EnvLoader("DATABRICKS_DF_DISPLAY_LIMIT", 20) + show_progress: bool = EnvLoader("SPARK_CONNECT_PROGRESS_BAR_ENABLED", default=False) def __new__(cls): annotations = cls.__dict__['__annotations__'] @@ -357,6 +369,107 @@ def df_html(df): html_formatter.for_type(SparkConnectDataframe, df_html) html_formatter.for_type(DataFrame, df_html) +@logErrorAndContinue +@disposable +def register_spark_progress(spark, show_progress: bool): + try: + import ipywidgets as widgets + except Exception as e: + return + + if not hasattr(spark, "clearProgressHandlers") or not hasattr(spark, "registerProgressHandler"): + return + + class Progress: + SI_BYTE_SIZES = (1 << 60, 1 << 50, 1 << 40, 1 << 30, 1 << 20, 1 << 10, 1) + SI_BYTE_SUFFIXES = ("EiB", "PiB", "TiB", "GiB", "MiB", "KiB", "B") + + def __init__( + self + ) -> None: + self._ticks = None + self._tick = None + self._started = time.time() + self._bytes_read = 0 + self._running = 0 + self.init_ui() + + def init_ui(self): + self.w_progress = widgets.IntProgress( + value=0, + min=0, + max=100, + bar_style='success', + orientation='horizontal' + ) + self.w_status = widgets.Label(value="") + if show_progress: + display(widgets.HBox([self.w_progress, self.w_status])) + + def update_ticks( + self, + stages, + inflight_tasks: int, + done: bool + ) -> None: + total_tasks = builtinSum(map(lambda x: x.num_tasks, stages)) + completed_tasks = builtinSum(map(lambda x: x.num_completed_tasks, stages)) + if total_tasks > 0: + self._ticks = total_tasks + self._tick = completed_tasks + self._bytes_read = builtinSum(map(lambda x: x.num_bytes_read, stages)) + + if done: + self._tick = self._ticks + self._running = 0 + + if self._tick is not None and self._tick >= 0: + self.output() + self._running = inflight_tasks + + def output(self) -> None: + if self._tick is not None and self._ticks is not None: + percent_complete = (self._tick / self._ticks) * 100 + elapsed = int(time.time() - self._started) + scanned = self._bytes_to_string(self._bytes_read) + running = self._running + self.w_progress.value = percent_complete + self.w_status.value = f"{percent_complete:.2f}% Complete ({running} Tasks running, {elapsed}s, Scanned {scanned})" + + @staticmethod + def _bytes_to_string(size: int) -> str: + """Helper method to convert a numeric bytes value into a human-readable representation""" + i = 0 + while i < len(Progress.SI_BYTE_SIZES) - 1 and size < 2 * Progress.SI_BYTE_SIZES[i]: + i += 1 + result = float(size) / Progress.SI_BYTE_SIZES[i] + return f"{result:.1f} {Progress.SI_BYTE_SUFFIXES[i]}" + + class ProgressHandler: + def __init__(self): + self.op_id = "" + + def reset(self): + self.p = Progress() + + def __call__(self, + stages, + inflight_tasks: int, + operation_id, + done: bool + ): + if len(stages) == 0: + return + + if self.op_id != operation_id: + self.op_id = operation_id + self.reset() + + self.p.update_ticks(stages, inflight_tasks, done) + + spark.clearProgressHandlers() + spark.registerProgressHandler(ProgressHandler()) + @logErrorAndContinue @disposable @@ -382,9 +495,16 @@ def make_matplotlib_inline(): if not load_env_from_leaf(os.getcwd()): sys.exit(1) cfg = LocalDatabricksNotebookConfig() + + # disable build-in progress bar + show_progress = cfg.show_progress + if "SPARK_CONNECT_PROGRESS_BAR_ENABLED" in os.environ: + del os.environ["SPARK_CONNECT_PROGRESS_BAR_ENABLED"] + create_and_register_databricks_globals() register_magics(cfg) register_formatters(cfg) + register_spark_progress(globals()["spark"], show_progress) update_sys_path(cfg) make_matplotlib_inline() diff --git a/packages/databricks-vscode/resources/python/dbconnect-bootstrap.py b/packages/databricks-vscode/resources/python/dbconnect-bootstrap.py new file mode 100644 index 000000000..c440b44f4 --- /dev/null +++ b/packages/databricks-vscode/resources/python/dbconnect-bootstrap.py @@ -0,0 +1,71 @@ +import os +import sys +import logging +from runpy import run_path + +# Load environment variables from .databricks/.databricks.env +# We only look for the folder in the current working directory +# since for all commands laucnhed from root workspace +def load_env_file_from_cwd(path: str): + if not os.path.isdir(path): + return + + env_file_path = os.path.join(path, ".databricks", ".databricks.env") + if not os.path.exists(os.path.dirname(env_file_path)): + return + + with open(env_file_path, "r") as f: + for line in f.readlines(): + key, value = line.strip().split("=", 1) + os.environ[key] = value + return + + +script = sys.argv[1] +sys.argv = sys.argv[1:] +logging.debug(f"Running ${script}") +logging.debug(f"args: ${sys.argv[1:]}") + +try: + cur_dir = os.path.dirname(script) +except Exception as e: + logging.error(f"Failed to get current directory: {e}") + cur_dir = os.getcwd() + +root_dir = os.getcwd() +load_env_file_from_cwd(root_dir) + +log_level = os.environ.get("DATABRICKS_VSCODE_LOG_LEVEL") +log_level = log_level if log_level is not None else "WARN" + +logging.basicConfig(level=log_level) + +db_globals = {} + +from databricks.sdk.runtime import dbutils # noqa: E402 +db_globals['dbutils'] = dbutils + +# "table", "sc", "sqlContext" are missing +try: + from pyspark.sql import functions as udf, SparkSession + from databricks.connect import DatabricksSession + spark: SparkSession = DatabricksSession.builder.getOrCreate() + sql = spark.sql + db_globals['spark'] = spark + db_globals['sql'] = sql + db_globals['udf'] = udf +except Exception as e: + logging.debug(f"Failed to create DatabricksSession: {e}") + +# We do this to prevent importing widgets implementation prematurely +# The widget import should prompt users to use the implementation +# which has ipywidget support. +def getArgument(*args, **kwargs): + return dbutils.widgets.getArgument(*args, **kwargs) + +db_globals['getArgument'] = getArgument + +sys.path.insert(0, root_dir) +sys.path.insert(0, cur_dir) + +run_path(script, init_globals=db_globals, run_name="__main__") diff --git a/packages/databricks-vscode/resources/whats-new/2.4.md b/packages/databricks-vscode/resources/whats-new/2.4.md new file mode 100644 index 000000000..152c3ef27 --- /dev/null +++ b/packages/databricks-vscode/resources/whats-new/2.4.md @@ -0,0 +1,35 @@ +databricks-logo + +# Databricks Extension v2.4.0 + +## What's new? + +- [Databricks Asset Bundles support](#dabs) +- [Bundle configuration](#dabs-config) +- [No environment variables in terminals](#no-env) + +### Databricks Asset Bundles support + +The extension now supports [Databricks Asset Bundles](https://docs.databricks.com/en/dev-tools/bundles/index.html)! New features include: + +- Easy authentication and configuration of your Databricks Asset Bundles through the Visual Studio Code UI, including **AuthType** profile selection. +- A **Target** selector in the Databricks extension panel to quickly switch between bundle target environments. +- The **Override Jobs cluster** in bundle option in the extension panel to enable easy cluster override. +- A **Bundles Resource Explorer** view, which allows you to browse your bundle resources using the Visual Studio Code UI, deploy your local Databricks Asset Bundle’s resources to your remote Databricks workspace with a single click, and go directly to your deployed resources in your workspace from Visual Studio Code. +- A **Bundles Variables View**, which enables you to browse and edit your bundle variables using the Visual Studio Code UI. See Bundle Variables View. + +See [our documentation for more information](https://docs..databricks.com/dev-tools/vscode-ext/bundles.html). + +### Bundle configuration + +The extension now requires a bundle configuration to be present in the project. + +If you don't use Databricks Asset Bundles, the extension will ask you to "migrate" your project. This will only create a `databricks.yml` configuration file with your workspace url. + +If you used our extension for a project before, we will migrate it automatically. + +See [our documentation for more information](https://docs.databricks.com/dev-tools/vscode-ext/index.html#migrate-a-project-to-a-databricks-project). + +### No environment variables in terminals + +The extension no longer injects databricks environment variables in VSCode terminals. If you were relying on this feature, you will need to manually load the `.databricks/.databricks.env` file in your terminal before running any commands that require those variables. diff --git a/packages/databricks-vscode/scripts/fetch-databricks-cli.sh b/packages/databricks-vscode/scripts/fetch-databricks-cli.sh index d4f999a94..bbbd5cd88 100755 --- a/packages/databricks-vscode/scripts/fetch-databricks-cli.sh +++ b/packages/databricks-vscode/scripts/fetch-databricks-cli.sh @@ -1,4 +1,4 @@ -#!/bin/bash +#!/bin/bash set -ex CLI_VERSION=$(cat package.json | jq -r .cli.version) @@ -8,6 +8,11 @@ if [ -z "$CLI_ARCH" ]; then CLI_ARCH="$(uname -s | awk '{print tolower($0)}')_$(uname -m)" fi +CLI_DEST=$2 +if [ -z "$CLI_DEST" ]; then + CLI_DEST=./bin +fi + CLI_DIR=$(mktemp -d -t databricks-XXXXXXXXXX) pushd $CLI_DIR gh release download v${CLI_VERSION} --pattern "databricks_cli_${CLI_VERSION}_${CLI_ARCH}.zip" --repo databricks/cli @@ -16,8 +21,8 @@ rm databricks_*_$CLI_ARCH.zip ls popd -mkdir -p bin -cd ./bin +mkdir -p $CLI_DEST +cd $CLI_DEST rm -rf databricks mv $CLI_DIR/databricks* . rm -rf $CLI_DIR diff --git a/packages/databricks-vscode/scripts/list_integration_tests.ts b/packages/databricks-vscode/scripts/list_integration_tests.ts new file mode 100644 index 000000000..fe6138332 --- /dev/null +++ b/packages/databricks-vscode/scripts/list_integration_tests.ts @@ -0,0 +1,28 @@ +import {glob} from "glob"; +import path from "path"; + +function toUnixPath(path: string) { + if (process.platform === "win32") { + return path.replace(/\\/g, "/"); + } + return path; +} + +const integrationTests = glob + .globSync( + toUnixPath( + path.join(process.cwd(), "src", "test", "e2e", "**", "*.e2e.ts") + ), + { + nocase: process.platform === "win32", + } + ) + .map((testPath) => { + return { + path: toUnixPath(path.relative(process.cwd(), testPath)), + baseName: path.basename(testPath, ".e2e.ts"), + }; + }); + +// eslint-disable-next-line no-console +console.log(JSON.stringify(integrationTests)); diff --git a/packages/databricks-vscode/scripts/package-vsix.sh b/packages/databricks-vscode/scripts/package-vsix.sh index 1ef3abe81..5795f9dc8 100755 --- a/packages/databricks-vscode/scripts/package-vsix.sh +++ b/packages/databricks-vscode/scripts/package-vsix.sh @@ -38,9 +38,25 @@ case $ARCH in ;; esac +# Download databricks cli to the .build directory with the correct arch for the environment that runs this script (not the target arch of the vsix) +# This CLI is used to request metadata about CLIs terraform dependencies. +if [ ! -d ./.build ]; then + mkdir ./.build + if [ -z "$BUILD_PLATFORM_ARCH" ]; then + BUILD_PLATFORM_ARCH="$(uname -s | awk '{print tolower($0)}')_$(uname -m)" + fi + ./scripts/fetch-databricks-cli.sh $BUILD_PLATFORM_ARCH ./.build +fi + rm -rf bin ./scripts/fetch-databricks-cli.sh $CLI_ARCH -yarn ts-node ./scripts/set_arch_in_package.ts $VSXI_ARCH -f package.json --cliArch $CLI_ARCH -V $VSXI_ARCH -c $(git rev-parse --short HEAD) +yarn ts-node ./scripts/setArchInPackage.ts $VSXI_ARCH -f package.json --cliArch $CLI_ARCH -V $VSXI_ARCH -c $(git rev-parse --short HEAD) + +# Don't bundle terraform for win32-arm64 as they don't support it yet: https://github.com/hashicorp/terraform/issues/32719 +if [ $ARCH != "win32-arm64" ]; then + yarn ts-node ./scripts/setupCLIDependencies.ts --cli ./.build/databricks --binDir ./bin --package ./package.json --arch $CLI_ARCH +fi + yarn run prettier package.json --write TAG="release-v$(cat package.json | jq -r .version)" yarn run package -t $VSXI_ARCH diff --git a/packages/databricks-vscode/scripts/set_arch_in_package.ts b/packages/databricks-vscode/scripts/setArchInPackage.ts similarity index 100% rename from packages/databricks-vscode/scripts/set_arch_in_package.ts rename to packages/databricks-vscode/scripts/setArchInPackage.ts diff --git a/packages/databricks-vscode/scripts/setupCLIDependencies.ts b/packages/databricks-vscode/scripts/setupCLIDependencies.ts new file mode 100644 index 000000000..0a5103d0f --- /dev/null +++ b/packages/databricks-vscode/scripts/setupCLIDependencies.ts @@ -0,0 +1,135 @@ +import {mkdirp} from "fs-extra"; +import assert from "node:assert"; +import {spawnSync} from "node:child_process"; +import {cp, readFile, writeFile} from "node:fs/promises"; +import {tmpdir} from "node:os"; +import path from "node:path"; +import yargs from "yargs"; +import type { + TerraformMetadata, + TerraformMetadataFromCli, +} from "../src/utils/terraformUtils"; + +async function main() { + const argv = await yargs + .option("cli", { + description: "Path to the Databricks CLI", + type: "string", + requiresArg: true, + }) + .option("binDir", { + description: "Path to the bin directory", + type: "string", + requiresArg: true, + }) + .option("arch", { + description: "Architecture of databricks cli.", + type: "string", + requiresArg: true, + }) + .option("package", { + description: "path/to/package.json", + type: "string", + requiresArg: true, + }).argv; + + const res = spawn(argv.cli!, [ + "bundle", + "debug", + "terraform", + "--output", + "json", + ]); + const dependencies = JSON.parse(res.stdout.toString()); + const terraform = dependencies.terraform as TerraformMetadataFromCli; + assert(terraform, "cli must return terraform dependencies"); + assert(terraform.version, "cli must return terraform version"); + assert(terraform.providerHost, "cli must return provider host"); + assert(terraform.providerSource, "cli must return provider source"); + assert(terraform.providerVersion, "cli must return provider version"); + + const tempDir = path.join(tmpdir(), `terraform_${Date.now()}`); + const depsDir = path.join(argv.binDir!, "dependencies"); + await mkdirp(tempDir); + await mkdirp(depsDir); + + // Download terraform bin for the selected arch + const arch = argv.arch!; + const terraformZip = `terraform_${terraform.version}_${arch}.zip`; + const terraformUrl = `https://releases.hashicorp.com/terraform/${terraform.version}/${terraformZip}`; + spawn("curl", ["-sLO", terraformUrl], {cwd: tempDir}); + // Check sha of the archive + const shasumsFile = `terraform_${terraform.version}_SHA256SUMS`; + const shasumsUrl = `https://releases.hashicorp.com/terraform/${terraform.version}/${shasumsFile}`; + spawn("curl", ["-sLO", shasumsUrl], {cwd: tempDir}); + const shasumRes = spawn( + "shasum", + ["--algorithm", "256", "--check", shasumsFile], + {cwd: tempDir} + ); + assert( + shasumRes.output.toString().includes(`${terraformZip}: OK`), + "sha256sum check failed" + ); + spawn("unzip", ["-q", terraformZip], {cwd: tempDir}); + const fileExt = arch.includes("windows") ? ".exe" : ""; + const terraformBinRelPath = path.join(depsDir, `terraform${fileExt}`); + await cp(`${tempDir}/terraform${fileExt}`, terraformBinRelPath); + // Set the path to the terraform bin, the extension will use it to setup the environment variables + const execRelPath = terraformBinRelPath; + + // Download databricks provider archive for the selected arch + const providerZip = `terraform-provider-databricks_${terraform.providerVersion}_${arch}.zip`; + spawn( + "gh", + [ + "release", + "download", + `v${terraform.providerVersion}`, + "--pattern", + providerZip, + "--repo", + "databricks/terraform-provider-databricks", + ], + {cwd: tempDir} + ); + const providersMirrorRelPath = path.join(depsDir, "providers"); + const databricksProviderDir = path.join( + providersMirrorRelPath, + terraform.providerHost, + terraform.providerSource + ); + await mkdirp(databricksProviderDir); + await cp( + path.join(tempDir, providerZip), + path.join(databricksProviderDir, providerZip) + ); + // Set the path to the providers mirror dir, the extension will use it + // to create the terraform CLI config at runtime. + const terraformCliConfigRelPath = path.join(depsDir, "config.tfrc"); + + // Save the info about all dependencies to the package.json + const terraformMetadata: TerraformMetadata = { + ...terraform, + execRelPath, + providersMirrorRelPath, + terraformCliConfigRelPath, + }; + const rawData = await readFile(argv.package!, {encoding: "utf-8"}); + const jsonData = JSON.parse(rawData); + jsonData["terraformMetadata"] = terraformMetadata; + await writeFile(argv.package!, JSON.stringify(jsonData, null, 4), { + encoding: "utf-8", + }); +} + +function spawn(command: string, args: string[], options: any = {}) { + const child = spawnSync(command, args, options); + if (child.error) { + throw child.error; + } else { + return child; + } +} + +main(); diff --git a/packages/databricks-vscode/scripts/writeBundleSchema.ts b/packages/databricks-vscode/scripts/writeBundleSchema.ts new file mode 100644 index 000000000..7f24ca580 --- /dev/null +++ b/packages/databricks-vscode/scripts/writeBundleSchema.ts @@ -0,0 +1,39 @@ +/** + * This script generates the BundleSchema.ts file from the bundle schema. + * It MUST be run after a yarn package:cli:fetch + */ + +import * as cp from "child_process"; +import * as fs from "fs"; +import { + quicktype, + InputData, + JSONSchemaInput, + FetchingJSONSchemaStore, +} from "quicktype-core"; +import {argv} from "process"; + +const output = cp.execFileSync(argv[2], ["bundle", "schema"]); + +async function quicktypeJSONSchema( + targetLanguage: string, + typeName: string, + jsonSchemaString: string +) { + const schemaInput = new JSONSchemaInput(new FetchingJSONSchemaStore()); + await schemaInput.addSource({name: typeName, schema: jsonSchemaString}); + const inputData = new InputData(); + inputData.addInput(schemaInput); + const result = await quicktype({ + inputData, + lang: targetLanguage, + }); + fs.writeFileSync( + argv[3], + "/* eslint-disable */\n" + result.lines.join("\n") + ); + // eslint-disable-next-line no-console + console.log("BundleSchema.d.ts written to", argv[3]); +} + +quicktypeJSONSchema("typescript", "BundleSchema", output.toString()); diff --git a/packages/databricks-vscode/src/bundle/BundleFileSet.test.ts b/packages/databricks-vscode/src/bundle/BundleFileSet.test.ts new file mode 100644 index 000000000..b1a99a621 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleFileSet.test.ts @@ -0,0 +1,223 @@ +import {Uri, WorkspaceFolder} from "vscode"; +import {BundleFileSet, getAbsoluteGlobPath} from "./BundleFileSet"; +import {expect} from "chai"; +import path from "path"; +import * as tmp from "tmp-promise"; +import * as fs from "fs/promises"; +import {BundleSchema} from "./types"; +import * as yaml from "yaml"; +import {instance, mock, when} from "ts-mockito"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; + +describe(__filename, async function () { + let tmpdir: tmp.DirectoryResult; + + beforeEach(async () => { + tmpdir = await tmp.dir({unsafeCleanup: true}); + }); + + afterEach(async () => { + await tmpdir.cleanup(); + }); + + function getWorkspaceFolderManagerMock() { + const mockWorkspaceFolderManager = mock(); + const mockWorkspaceFolder = mock(); + when(mockWorkspaceFolder.uri).thenReturn(Uri.file(tmpdir.path)); + when(mockWorkspaceFolderManager.activeWorkspaceFolder).thenReturn( + instance(mockWorkspaceFolder) + ); + return instance(mockWorkspaceFolderManager); + } + + it("should return the correct absolute glob path", () => { + const tmpdirUri = Uri.file(tmpdir.path); + let expectedGlob = path.join(tmpdirUri.fsPath, "test.txt"); + if (process.platform === "win32") { + expectedGlob = expectedGlob.replace(/\\/g, "/"); + } + expect(getAbsoluteGlobPath("test.txt", tmpdirUri)).to.equal( + expectedGlob + ); + expect(getAbsoluteGlobPath(Uri.file("test.txt"), tmpdirUri)).to.equal( + expectedGlob + ); + }); + + it("should find the correct root bundle yaml", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + expect(await bundleFileSet.getRootFile()).to.be.undefined; + + await fs.writeFile(path.join(tmpdirUri.fsPath, "bundle.yaml"), ""); + + expect((await bundleFileSet.getRootFile())?.fsPath).to.equal( + path.join(tmpdirUri.fsPath, "bundle.yaml") + ); + }); + + it("should return undefined if more than one root bundle yaml is found", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + await fs.writeFile(path.join(tmpdirUri.fsPath, "bundle.yaml"), ""); + await fs.writeFile(path.join(tmpdirUri.fsPath, "databricks.yaml"), ""); + + expect(await bundleFileSet.getRootFile()).to.be.undefined; + }); + + describe("file listing", async () => { + beforeEach(async () => { + const rootBundleData: BundleSchema = { + include: [ + "included.yaml", + path.join("includes", "**", "*.yaml"), + ], + }; + + await fs.writeFile( + path.join(tmpdir.path, "bundle.yaml"), + yaml.stringify(rootBundleData) + ); + + await fs.writeFile(path.join(tmpdir.path, "included.yaml"), ""); + await fs.writeFile(path.join(tmpdir.path, "notIncluded.yaml"), ""); + await fs.mkdir(path.join(tmpdir.path, "includes")); + await fs.writeFile( + path.join(tmpdir.path, "includes", "included.yaml"), + "" + ); + }); + + it("should return correct included files", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + expect(await bundleFileSet.getIncludedFilesGlob()).to.equal( + `{included.yaml,${path.join("includes", "**", "*.yaml")}}` + ); + + const actual = (await bundleFileSet.getIncludedFiles())?.map( + (v) => v.fsPath + ); + const expected = [ + Uri.file(path.join(tmpdirUri.fsPath, "included.yaml")), + Uri.file( + path.join(tmpdirUri.fsPath, "includes", "included.yaml") + ), + ].map((v) => v.fsPath); + expect(Array.from(new Set(actual).values()).sort()).to.deep.equal( + Array.from(new Set(expected).values()).sort() + ); + }); + + it("should return all bundle files", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + const actual = (await bundleFileSet.allFiles()).map( + (v) => v.fsPath + ); + const expected = [ + Uri.joinPath(tmpdirUri, "bundle.yaml"), + Uri.joinPath(tmpdirUri, "included.yaml"), + Uri.joinPath(tmpdirUri, "includes", "included.yaml"), + ].map((v) => v.fsPath); + expect(actual).to.deep.equal(expected); + }); + + it("isRootBundleFile should return true only for root bundle file", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + const possibleRoots = [ + "bundle.yaml", + "bundle.yml", + "databricks.yaml", + "databricks.yml", + ]; + + for (const root of possibleRoots) { + expect( + bundleFileSet.isRootBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, root)) + ) + ).to.be.true; + } + + expect( + bundleFileSet.isRootBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, "bundle-wrong.yaml")) + ) + ).to.be.false; + }); + + it("isIncludedBundleFile should return true only for included files", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + expect( + await bundleFileSet.isIncludedBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, "included.yaml")) + ) + ).to.be.true; + + expect( + await bundleFileSet.isIncludedBundleFile( + Uri.file( + path.join(tmpdirUri.fsPath, "includes", "included.yaml") + ) + ) + ).to.be.true; + + expect( + await bundleFileSet.isIncludedBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, "notIncluded.yaml")) + ) + ).to.be.false; + }); + + it("isBundleFile should return true only for bundle files", async () => { + const tmpdirUri = Uri.file(tmpdir.path); + const bundleFileSet = new BundleFileSet( + getWorkspaceFolderManagerMock() + ); + + const possibleBundleFiles = [ + "bundle.yaml", + "bundle.yml", + "databricks.yaml", + "databricks.yml", + "included.yaml", + path.join("includes", "included.yaml"), + ]; + + for (const bundleFile of possibleBundleFiles) { + expect( + await bundleFileSet.isBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, bundleFile)) + ) + ).to.be.true; + } + + expect( + await bundleFileSet.isBundleFile( + Uri.file(path.join(tmpdirUri.fsPath, "notIncluded.yaml")) + ) + ).to.be.false; + }); + }); +}); diff --git a/packages/databricks-vscode/src/bundle/BundleFileSet.ts b/packages/databricks-vscode/src/bundle/BundleFileSet.ts new file mode 100644 index 000000000..a2311cde9 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleFileSet.ts @@ -0,0 +1,193 @@ +import {Uri} from "vscode"; +import * as glob from "glob"; +import {merge} from "lodash"; +import * as yaml from "yaml"; +import path from "path"; +import {BundleSchema} from "./types"; +import {readFile, writeFile} from "fs/promises"; +import {CachedValue} from "../locking/CachedValue"; +import {minimatch} from "minimatch"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; + +const rootFilePattern: string = "{bundle,databricks}.{yaml,yml}"; +const subProjectFilePattern: string = path.join("**", rootFilePattern); + +export async function parseBundleYaml(file: Uri) { + const data = yaml.parse(await readFile(file.fsPath, "utf-8")); + return data as BundleSchema; +} + +export async function writeBundleYaml(file: Uri, data: BundleSchema) { + await writeFile(file.fsPath, yaml.stringify(data)); +} + +export async function getSubProjects(root: Uri) { + const subProjectRoots = await glob.glob( + getAbsoluteGlobPath(subProjectFilePattern, root), + {nocase: process.platform === "win32"} + ); + const normalizedRoot = path.normalize(root.fsPath); + return subProjectRoots + .map((rootFile) => { + const dirname = path.dirname(path.normalize(rootFile)); + const absolute = Uri.file(dirname); + const relative = path.relative(normalizedRoot, dirname); + return {absolute, relative}; + }) + .filter(({absolute}) => { + return absolute.fsPath !== normalizedRoot; + }); +} + +export function getAbsoluteGlobPath(path: string | Uri, root: Uri): string { + path = typeof path === "string" ? path : path.fsPath; + const uri = Uri.joinPath(root, path); + return toGlobPath(uri.fsPath); +} + +function toGlobPath(path: string) { + if (process.platform === "win32") { + return path.replace(/\\/g, "/"); + } + return path; +} + +export class BundleFileSet { + public readonly bundleDataCache: CachedValue = + new CachedValue(async () => { + let bundle = {}; + await this.forEach(async (data) => { + bundle = merge(bundle, data); + }); + return bundle as BundleSchema; + }); + + private get workspaceRoot() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + workspaceFolderManager.onDidChangeActiveWorkspaceFolder(() => { + this.bundleDataCache.invalidate(); + }); + } + + async getRootFile() { + const rootFile = await glob.glob( + getAbsoluteGlobPath(rootFilePattern, this.workspaceRoot), + {nocase: process.platform === "win32"} + ); + if (rootFile.length !== 1) { + return undefined; + } + return Uri.file(rootFile[0]); + } + + async getSubProjects( + root?: Uri + ): Promise<{relative: Uri; absolute: Uri}[]> { + const subProjectRoots = await glob.glob( + getAbsoluteGlobPath( + subProjectFilePattern, + root || this.workspaceRoot + ), + {nocase: process.platform === "win32"} + ); + const normalizedRoot = path.normalize( + root?.fsPath ?? this.workspaceRoot.fsPath + ); + return subProjectRoots + .map((rootFile) => { + const dirname = path.dirname(path.normalize(rootFile)); + const absolute = Uri.file(dirname); + const relative = Uri.file( + absolute.fsPath.replace(normalizedRoot, "") + ); + return {absolute, relative}; + }) + .filter(({absolute}) => { + return absolute.fsPath !== normalizedRoot; + }); + } + + async getIncludedFilesGlob() { + const rootFile = await this.getRootFile(); + if (rootFile === undefined) { + return undefined; + } + const bundle = await parseBundleYaml(Uri.file(rootFile.fsPath)); + if (bundle?.include === undefined || bundle?.include.length === 0) { + return undefined; + } + if (bundle?.include.length === 1) { + return bundle.include[0]; + } + return `{${bundle.include.join(",")}}`; + } + + async getIncludedFiles() { + const includedFilesGlob = await this.getIncludedFilesGlob(); + if (includedFilesGlob !== undefined) { + return ( + await glob.glob( + toGlobPath( + path.join(this.workspaceRoot.fsPath, includedFilesGlob) + ), + {nocase: process.platform === "win32"} + ) + ).map((i) => Uri.file(i)); + } + } + + async allFiles() { + const rootFile = await this.getRootFile(); + if (rootFile === undefined) { + return []; + } + + return [rootFile, ...((await this.getIncludedFiles()) ?? [])]; + } + + async findFile( + predicate: (data: BundleSchema, file: Uri) => Promise + ) { + const matchedFiles: {data: BundleSchema; file: Uri}[] = []; + this.forEach(async (data, file) => { + if (await predicate(data, file)) { + matchedFiles.push({data, file}); + } + }); + return matchedFiles; + } + + async forEach(f: (data: BundleSchema, file: Uri) => Promise) { + for (const file of await this.allFiles()) { + await f(await parseBundleYaml(file), file); + } + } + + isRootBundleFile(e: Uri) { + return minimatch( + e.fsPath, + getAbsoluteGlobPath(rootFilePattern, this.workspaceRoot) + ); + } + + async isIncludedBundleFile(e: Uri) { + let includedFilesGlob = await this.getIncludedFilesGlob(); + if (includedFilesGlob === undefined) { + return false; + } + includedFilesGlob = getAbsoluteGlobPath( + includedFilesGlob, + this.workspaceRoot + ); + return minimatch(e.fsPath, toGlobPath(includedFilesGlob)); + } + + async isBundleFile(e: Uri) { + return this.isRootBundleFile(e) || (await this.isIncludedBundleFile(e)); + } +} diff --git a/packages/databricks-vscode/src/bundle/BundleInitWizard.ts b/packages/databricks-vscode/src/bundle/BundleInitWizard.ts new file mode 100644 index 000000000..56d2471de --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleInitWizard.ts @@ -0,0 +1,276 @@ +import { + QuickPickItem, + QuickPickItemKind, + Uri, + window, + TerminalLocation, + commands, +} from "vscode"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../logger"; +import {AuthProvider} from "../configuration/auth/AuthProvider"; +import {LoginWizard} from "../configuration/LoginWizard"; +import {CliWrapper} from "../cli/CliWrapper"; +import {getSubProjects} from "./BundleFileSet"; +import {tmpdir} from "os"; +import {ShellUtils} from "../utils"; +import {Events, Telemetry} from "../telemetry"; +import {OverrideableConfigModel} from "../configuration/models/OverrideableConfigModel"; +import {writeFile, mkdir} from "fs/promises"; +import path from "path"; +import {escapePathArgument} from "../utils/shellUtils"; + +export async function promptToOpenSubProjects( + projects: {absolute: Uri; relative: string}[], + authProvider?: AuthProvider +) { + type OpenProjectItem = QuickPickItem & {uri?: Uri}; + const items: OpenProjectItem[] = projects.map((project) => { + return { + uri: project.absolute, + label: project.relative, + detail: project.absolute.fsPath, + }; + }); + items.push( + {label: "", kind: QuickPickItemKind.Separator}, + {label: "Choose another folder"} + ); + const options = { + title: "Select the project you want to open", + }; + const item = await window.showQuickPick(items, options); + if (!item?.uri) { + return; + } + + if (authProvider?.authType === "profile") { + const rootOverrideFilePath = + OverrideableConfigModel.getRootOverrideFile(item.uri); + await mkdir(path.dirname(rootOverrideFilePath.fsPath), { + recursive: true, + }); + await writeFile( + rootOverrideFilePath.fsPath, + JSON.stringify({authProfile: authProvider.toJSON().profile}) + ); + } + await commands.executeCommand("vscode.openFolder", item.uri); +} + +export class BundleInitWizard { + private logger = logging.NamedLogger.getOrCreate(Loggers.Extension); + + constructor( + private cli: CliWrapper, + private telemetry: Telemetry + ) {} + + public async initNewProject( + workspaceUri?: Uri, + existingAuthProvider?: AuthProvider + ) { + const recordEvent = this.telemetry.start(Events.BUNDLE_INIT); + try { + const authProvider = + await this.configureAuthForBundleInit(existingAuthProvider); + if (!authProvider) { + this.logger.debug( + "No valid auth providers, can't proceed with bundle init wizard" + ); + recordEvent({success: false}); + return; + } + const parentFolder = await this.promptForParentFolder(workspaceUri); + if (!parentFolder) { + this.logger.debug("No parent folder provided"); + recordEvent({success: false}); + return; + } + await this.bundleInitInTerminal(parentFolder, authProvider); + this.logger.debug( + "Finished bundle init wizard, detecting projects to initialize or open" + ); + const projects = await getSubProjects(parentFolder); + recordEvent({success: projects.length > 0}); + if (projects.length > 0) { + this.logger.debug( + `Detected ${projects.length} sub projects after the init wizard, prompting to open one` + ); + await promptToOpenSubProjects(projects, authProvider); + } else { + this.logger.debug( + `No projects detected after the init wizard, showing notification to open a folder manually` + ); + const choice = await window.showInformationMessage( + `We haven't detected any Databricks projects in "${parentFolder.fsPath}". If you initialized your project somewhere else, please open the folder manually.`, + "Open Folder" + ); + if (choice === "Open Folder") { + await commands.executeCommand("vscode.openFolder"); + } + } + return parentFolder; + } catch (e) { + recordEvent({success: false}); + throw e; + } + } + + private async configureAuthForBundleInit( + authProvider?: AuthProvider + ): Promise { + if (authProvider) { + const response = await this.promptToUseExistingAuth(authProvider); + if (response.cancelled) { + return undefined; + } else if (!response.approved) { + authProvider = undefined; + } + } + if (!authProvider) { + authProvider = await LoginWizard.run(this.cli); + } + if (authProvider && (await authProvider.check())) { + return authProvider; + } else { + return undefined; + } + } + + private async promptToUseExistingAuth(authProvider: AuthProvider) { + type AuthSelectionItem = QuickPickItem & {approved: boolean}; + const items: AuthSelectionItem[] = [ + { + label: "Use current auth", + detail: `Host: ${authProvider.host.hostname}`, + approved: true, + }, + { + label: "Setup new auth", + approved: false, + }, + ]; + const options = { + title: "What auth do you want to use for the new project?", + }; + const item = await window.showQuickPick( + items, + options + ); + return { + cancelled: item === undefined, + approved: item?.approved ?? false, + }; + } + + private async bundleInitInTerminal( + parentFolder: Uri, + authProvider: AuthProvider + ) { + const terminal = window.createTerminal({ + name: "Databricks Project Init", + isTransient: true, + location: TerminalLocation.Editor, + env: { + // Without supplying full environment and with `strictEnv: true` PowerShell will fail to start. + // On unix-like systems we don't require full environment, but it doesn't hurt. + ...process.env, + ...this.cli.getBundleInitEnvVars(authProvider), + }, + // Without strict env we will inherit our environmentVariableCollection + // which will override auth env vars we provide in this call. + strictEnv: true, + // Setting CWD avoids a possibility of the CLI picking up unrelated bundle configuration + // in the current workspace root or while traversing up the folder structure. + cwd: tmpdir(), + }); + const args = [ + "bundle", + "init", + "--output-dir", + escapePathArgument(parentFolder.fsPath), + ].join(" "); + const initialPrompt = `clear; echo "Executing: databricks ${args}\nFollow the steps below to create your new Databricks project.\n"`; + const finalPrompt = `echo "\nPress any key to close the terminal and continue ..."; ${ShellUtils.readCmd()}; exit`; + terminal.sendText( + `${initialPrompt}; ${this.cli.escapedCliPath} ${args}; ${finalPrompt}` + ); + return new Promise((resolve) => { + const closeEvent = window.onDidCloseTerminal(async (t) => { + if (t !== terminal) { + return; + } + closeEvent.dispose(); + resolve(); + }); + }); + } + + private async promptForParentFolder( + workspaceUri?: Uri + ): Promise { + const quickPick = window.createQuickPick(); + const openFolderLabel = "Open folder selection dialog"; + const initialValue = workspaceUri?.fsPath || process.env.HOME; + if (initialValue) { + quickPick.value = initialValue; + } + quickPick.title = + "Provide a path to a folder where you would want your new project to be"; + quickPick.items = createParentFolderQuickPickItems( + quickPick.value, + openFolderLabel + ); + quickPick.show(); + const disposables = [ + quickPick.onDidChangeValue(() => { + quickPick.items = createParentFolderQuickPickItems( + quickPick.value, + openFolderLabel + ); + }), + ]; + const choice = await new Promise( + (resolve) => { + disposables.push( + quickPick.onDidAccept(() => + resolve(quickPick.selectedItems[0]) + ), + quickPick.onDidHide(() => resolve(undefined)) + ); + } + ); + disposables.forEach((d) => d.dispose()); + quickPick.hide(); + if (!choice) { + return; + } + if (choice.label !== openFolderLabel) { + return Uri.file(choice.label); + } + const choices = await window.showOpenDialog({ + title: "Choose a folder where you would want your new project to be", + openLabel: "Select folder", + defaultUri: workspaceUri, + canSelectFolders: true, + canSelectFiles: false, + canSelectMany: false, + }); + return choices ? choices[0] : undefined; + } +} + +function createParentFolderQuickPickItems( + value: string | undefined, + openFolderLabel: string +) { + const items: QuickPickItem[] = value + ? [{label: value, alwaysShow: true}] + : []; + items.push( + {label: "", kind: QuickPickItemKind.Separator, alwaysShow: true}, + {label: openFolderLabel, alwaysShow: true} + ); + return items; +} diff --git a/packages/databricks-vscode/src/bundle/BundleProjectManager.ts b/packages/databricks-vscode/src/bundle/BundleProjectManager.ts new file mode 100644 index 000000000..a73070608 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleProjectManager.ts @@ -0,0 +1,341 @@ +import {ExtensionContext, Disposable, Uri, window} from "vscode"; +import fs from "node:fs/promises"; +import path from "path"; +import os from "node:os"; +import {ConnectionManager} from "../configuration/ConnectionManager"; +import {ConfigModel} from "../configuration/models/ConfigModel"; +import {BundleFileSet, getSubProjects} from "./BundleFileSet"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../logger"; +import {CachedValue} from "../locking/CachedValue"; +import {CustomWhenContext} from "../vscode-objs/CustomWhenContext"; +import {CliWrapper} from "../cli/CliWrapper"; +import {LoginWizard, saveNewProfile} from "../configuration/LoginWizard"; +import {Mutex} from "../locking"; +import {ProfileAuthProvider} from "../configuration/auth/AuthProvider"; +import {ProjectConfigFile} from "../file-managers/ProjectConfigFile"; +import {randomUUID} from "crypto"; +import {onError} from "../utils/onErrorDecorator"; +import {BundleInitWizard, promptToOpenSubProjects} from "./BundleInitWizard"; +import {EventReporter, Events, Telemetry} from "../telemetry"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; + +export class BundleProjectManager { + private logger = logging.NamedLogger.getOrCreate(Loggers.Extension); + private disposables: Disposable[] = []; + + private isBundleProjectCache = new CachedValue(async () => { + const rootBundleFile = await this.bundleFileSet.getRootFile(); + return rootBundleFile !== undefined; + }); + + public onDidChangeStatus = this.isBundleProjectCache.onDidChange; + + private projectServicesReady = false; + private projectServicesMutex = new Mutex(); + + private subProjects?: {relative: string; absolute: Uri}[]; + private legacyProjectConfig?: ProjectConfigFile; + + get workspaceUri() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private context: ExtensionContext, + private cli: CliWrapper, + private customWhenContext: CustomWhenContext, + private connectionManager: ConnectionManager, + private configModel: ConfigModel, + private bundleFileSet: BundleFileSet, + private workspaceFolderManager: WorkspaceFolderManager, + private telemetry: Telemetry + ) { + this.disposables.push( + this.workspaceFolderManager.onDidChangeActiveWorkspaceFolder( + async () => { + await this.isBundleProjectCache.refresh(); + } + ), + this.bundleFileSet.bundleDataCache.onDidChange(async () => { + try { + await this.isBundleProjectCache.refresh(); + } catch (error) { + this.logger.error( + "Failed to refresh isBundleProjectCache", + error + ); + } + }), + this.isBundleProjectCache.onDidChange(async () => { + try { + await this.configureBundleProject(); + } catch (error) { + this.logger.error( + "Failed to configure bundle project after isBundleProject change", + error + ); + const message = + (error as Error)?.message ?? "Unknown Error"; + window.showErrorMessage( + `Failed to configure Databricks project: ${message}` + ); + } + }) + ); + } + + public async isBundleProject(): Promise { + return await this.isBundleProjectCache.value; + } + + public async configureWorkspace(): Promise { + // We listen to _isBundleProject changes and call configureBundleProject + if (await this.isBundleProject()) { + return; + } + const recordEvent = this.telemetry.start( + Events.EXTENSION_INITIALIZATION + ); + // This method updates subProjectsAvailabe context. + // We have a configurationView that shows "openSubProjects" button if the context value is true. + await this.detectSubProjects(); + // This method will try to automatically create bundle config if there's existing valid project.json config. + // In the case project.json doesn't exist or its auth doesn't work, it sets pendingManualMigration context + // to enable configurationView with the configureManualMigration button. + await this.detectLegacyProjectConfig(); + + const type = this.legacyProjectConfig ? "legacy" : "unknown"; + recordEvent({success: true, type}); + } + + private async configureBundleProject() { + if (await this.isBundleProject()) { + this.logger.debug( + "Detected an existing bundle project, initializing project services" + ); + this.customWhenContext.setIsBundleProject(true); + return this.initProjectServices(); + } else { + this.logger.debug( + "No bundle config detected, disposing project services" + ); + this.customWhenContext.setIsBundleProject(false); + await this.disposeProjectServices(); + } + } + + @Mutex.synchronise("projectServicesMutex") + private async initProjectServices() { + if (this.projectServicesReady) { + this.logger.debug("Project services have already been initialized"); + return; + } + const recordEvent = this.telemetry.start( + Events.EXTENSION_INITIALIZATION + ); + try { + await this.configModel.init(); + await this.connectionManager.init(); + this.projectServicesReady = true; + recordEvent({success: true, type: "dabs"}); + } catch (e) { + recordEvent({success: false, type: "dabs"}); + throw e; + } + } + + private async disposeProjectServices() { + // TODO + } + + private async detectSubProjects() { + this.subProjects = await getSubProjects(this.workspaceUri); + this.logger.debug( + `Detected ${this.subProjects?.length} sub folders with bundle projects` + ); + this.customWhenContext.setSubProjectsAvailable( + this.subProjects?.length > 0 + ); + this.telemetry.recordEvent(Events.BUNDLE_SUB_PROJECTS, { + count: this.subProjects?.length ?? 0, + }); + } + + public async openSubProjects() { + if (this.subProjects && this.subProjects.length > 0) { + return promptToOpenSubProjects(this.subProjects); + } + } + + private setPendingManualMigration() { + this.customWhenContext.setPendingManualMigration(true); + this.telemetry.recordEvent(Events.CONNECTION_STATE_CHANGED, { + newState: "PENDING_MANUAL_MIGRATION", + }); + } + + private async detectLegacyProjectConfig() { + this.legacyProjectConfig = await this.loadLegacyProjectConfig(); + // If we have subprojects, we can't migrate automatically. We show the user option to + // manually migrate the project (create a new databricks.yml based on selected auth) + if (!this.legacyProjectConfig || (this.subProjects?.length ?? 0) > 0) { + this.setPendingManualMigration(); + return; + } + this.logger.debug( + "Detected a legacy project.json, starting automatic migration" + ); + const recordEvent = this.telemetry.start(Events.AUTO_MIGRATION); + try { + await this.startAutomaticMigration( + this.legacyProjectConfig, + recordEvent + ); + } catch (error) { + recordEvent({success: false}); + this.setPendingManualMigration(); + const message = + "Failed to perform automatic migration to Databricks Asset Bundles."; + this.logger.error(message, error); + const errorMessage = (error as Error)?.message ?? "Unknown Error"; + window.showErrorMessage(`${message} ${errorMessage}`); + } + } + + private async loadLegacyProjectConfig(): Promise< + ProjectConfigFile | undefined + > { + try { + return await ProjectConfigFile.load( + this.workspaceUri.fsPath, + this.cli + ); + } catch (error) { + this.logger.error("Failed to load legacy project config:", error); + return undefined; + } + } + + private async startAutomaticMigration( + legacyProjectConfig: ProjectConfigFile, + recordEvent: EventReporter + ) { + let authProvider = legacyProjectConfig.authProvider; + if (!(await authProvider.check())) { + this.logger.debug( + "Legacy project auth was not successful, showing 'configure' welcome screen" + ); + this.setPendingManualMigration(); + recordEvent({success: false}); + return; + } + if (!(authProvider instanceof ProfileAuthProvider)) { + const rnd = randomUUID().slice(0, 8); + const profileName = `${authProvider.authType}-${rnd}`; + this.logger.debug( + "Creating new profile before bundle migration", + profileName + ); + authProvider = await saveNewProfile( + profileName, + authProvider, + this.cli + ); + } + await this.migrateProjectJsonToBundle( + authProvider as ProfileAuthProvider, + legacyProjectConfig, + true + ); + recordEvent({success: true}); + } + + @onError({ + popup: { + prefix: "Failed to migrate the project to Databricks Asset Bundles", + }, + }) + public async startManualMigration() { + const recordEvent = this.telemetry.start(Events.MANUAL_MIGRATION); + try { + const authProvider = await LoginWizard.run(this.cli); + if ( + authProvider instanceof ProfileAuthProvider && + (await authProvider.check()) + ) { + await this.migrateProjectJsonToBundle( + authProvider, + this.legacyProjectConfig + ); + recordEvent({success: true}); + } else { + recordEvent({success: false}); + this.logger.debug( + "Incorrect auth for the project.json migration" + ); + } + } catch (e) { + recordEvent({success: false}); + throw e; + } + } + + private async migrateProjectJsonToBundle( + authProvider: ProfileAuthProvider, + legacyProjectConfig?: ProjectConfigFile, + autoMigration: boolean = false + ) { + const configVars = { + /* eslint-disable @typescript-eslint/naming-convention */ + project_name: path.basename(this.workspaceUri.fsPath), + auto_migration: autoMigration, + compute_id: legacyProjectConfig?.clusterId, + root_path: legacyProjectConfig?.workspacePath?.path, + /* eslint-enable @typescript-eslint/naming-convention */ + }; + this.logger.debug("Starting bundle migration, config:", configVars); + const configFilePath = path.join( + this.workspaceUri.fsPath, + ".databricks", + "migration-config.json" + ); + await fs.mkdir(path.dirname(configFilePath), {recursive: true}); + await fs.writeFile(configFilePath, JSON.stringify(configVars, null, 4)); + + // TODO: Add to .gitignore only if it's not already there + await fs.appendFile( + path.join(path.dirname(path.dirname(configFilePath)), ".gitignore"), + os.EOL + ".databricks" + os.EOL + ); + + const templateDirPath = this.context.asAbsolutePath( + path.join("resources", "migration-template") + ); + await this.cli.bundleInit( + templateDirPath, + this.workspaceUri.fsPath, + configFilePath, + authProvider + ); + this.logger.debug("Successfully finished bundle migration"); + } + + @onError({popup: {prefix: "Failed to initialize new Databricks project"}}) + public async initNewProject() { + const bundleInitWizard = new BundleInitWizard(this.cli, this.telemetry); + const authProvider = + this.connectionManager.databricksWorkspace?.authProvider; + const parentFolder = await bundleInitWizard.initNewProject( + this.workspaceUri, + authProvider + ); + if (parentFolder) { + await this.isBundleProjectCache.refresh(); + } + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/bundle/BundleSchema.ts b/packages/databricks-vscode/src/bundle/BundleSchema.ts new file mode 100644 index 000000000..8fd4aa2a8 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleSchema.ts @@ -0,0 +1,16729 @@ +/* eslint-disable */ +// To parse this data: +// +// import { Convert, BundleSchema } from "./file"; +// +// const bundleSchema = Convert.toBundleSchema(json); +// +// These functions will throw an error if the JSON doesn't +// match the expected interface, even if the JSON is valid. + +export interface BundleSchema { + artifacts?: {[key: string]: ArtifactClass | string} | string; + bundle?: BundleClass | string; + experimental?: ExperimentalClass | string; + include?: string[] | string; + permissions?: Array | string; + presets?: PresetsClass | string; + resources?: ResourcesClass | string; + run_as?: RunAsClass | string; + sync?: SyncClass | string; + targets?: {[key: string]: TargetClass | string} | string; + variables?: {[key: string]: VariableValue} | string; + workspace?: BundleSchem18 | string; +} + +export interface ArtifactClass { + build?: string; + executable?: string; + files?: Array | string; + path?: string; + type: string; +} + +export interface PurpleBundleSchem { + source: string; +} + +export interface BundleClass { + cluster_id?: string; + compute_id?: string; + databricks_cli_version?: string; + deployment?: FluffyBundleSchem | string; + git?: GitClass | string; + name: string; +} + +export interface FluffyBundleSchem { + fail_on_active_runs?: boolean | string; + lock?: LockClass | string; +} + +export interface LockClass { + enabled?: boolean | string; + force?: boolean | string; +} + +export interface GitClass { + branch?: string; + origin_url?: string; +} + +export interface ExperimentalClass { + pydabs?: PydabsClass | string; + python_wheel_wrapper?: boolean | string; + scripts?: {[key: string]: string} | string; + use_legacy_run_as?: boolean | string; +} + +export interface PydabsClass { + enabled?: boolean | string; + import?: string[] | string; + venv_path?: string; +} + +export interface PermissionClass { + group_name?: string; + level: string; + service_principal_name?: string; + user_name?: string; +} + +export interface PresetsClass { + jobs_max_concurrent_runs?: number | string; + name_prefix?: string; + pipelines_development?: boolean | string; + tags?: {[key: string]: string} | string; + trigger_pause_status?: string; +} + +export interface ResourcesClass { + clusters?: {[key: string]: TentacledBundleSchem | string} | string; + experiments?: {[key: string]: ExperimentClass | string} | string; + jobs?: {[key: string]: JobClass | string} | string; + model_serving_endpoints?: + | {[key: string]: ModelServingEndpointClass | string} + | string; + models?: {[key: string]: ModelClass | string} | string; + pipelines?: {[key: string]: PipelineClass | string} | string; + quality_monitors?: {[key: string]: QualityMonitorClass | string} | string; + registered_models?: {[key: string]: RegisteredModelClass | string} | string; + schemas?: {[key: string]: BundleSchem17 | string} | string; +} + +export interface TentacledBundleSchem { + /** + * When set to true, fixed and default values from the policy will be used for fields that + * are omitted. When set to false, only fixed values from the policy will be applied. + */ + apply_policy_default_values?: boolean | string; + /** + * Parameters needed in order to automatically scale clusters up and down based on load. + * Note: autoscaling works best with DB runtime versions 3.0 or later. + */ + autoscale?: StickyBundleSchem | string; + /** + * Automatically terminates the cluster after it is inactive for this time in minutes. If + * not set, + * this cluster will not be automatically terminated. If specified, the threshold must be + * between + * 10 and 10000 minutes. + * Users can also set this value to 0 to explicitly disable automatic termination. + */ + autotermination_minutes?: number | string; + /** + * Attributes related to clusters running on Amazon Web Services. + * If not specified at cluster creation, a set of default values will be used. + */ + aws_attributes?: AwsAttributesClass | string; + /** + * Attributes related to clusters running on Microsoft Azure. + * If not specified at cluster creation, a set of default values will be used. + */ + azure_attributes?: AzureAttributesClass | string; + /** + * The configuration for delivering spark logs to a long-term storage destination. + * Two kinds of destinations (dbfs and s3) are supported. Only one destination can be + * specified + * for one cluster. If the conf is given, the logs will be delivered to the destination + * every + * `5 mins`. The destination of driver logs is `$destination/$clusterId/driver`, while + * the destination of executor logs is `$destination/$clusterId/executor`. + */ + cluster_log_conf?: ClusterLogConfClass | string; + /** + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + */ + cluster_name?: string; + /** + * Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., + * AWS + * instances and EBS volumes) with these tags in addition to `default_tags`. Notes: + * + * - Currently, Databricks allows at most 45 custom tags + * + * - Clusters can only reuse cloud resources if the resources' tags are a subset of the + * cluster tags + */ + custom_tags?: {[key: string]: string} | string; + data_security_mode?: DataSecurityMode; + docker_image?: DockerImageClass | string; + /** + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + */ + driver_instance_pool_id?: string; + /** + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + */ + driver_node_type_id?: string; + /** + * Autoscaling Local Storage: when enabled, this cluster will dynamically acquire additional + * disk + * space when its Spark workers are running low on disk space. This feature requires + * specific AWS + * permissions to function correctly - refer to the User Guide for more details. + */ + enable_elastic_disk?: boolean | string; + /** + * Whether to enable LUKS on cluster VMs' local disks + */ + enable_local_disk_encryption?: boolean | string; + /** + * Attributes related to clusters running on Google Cloud Platform. + * If not specified at cluster creation, a set of default values will be used. + */ + gcp_attributes?: GcpAttributesClass | string; + /** + * The configuration for storing init scripts. Any number of destinations can be specified. + * The scripts are executed sequentially in the order provided. If `cluster_log_conf` is + * specified, init script logs are sent to `//init_scripts`. + */ + init_scripts?: Array | string; + /** + * The optional ID of the instance pool to which the cluster belongs. + */ + instance_pool_id?: string; + /** + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + */ + node_type_id?: string; + /** + * Number of worker nodes that this cluster should have. A cluster has one Spark Driver + * and `num_workers` Executors for a total of `num_workers` + 1 Spark nodes. + * + * Note: When reading the properties of a cluster, this field reflects the desired number + * of workers rather than the actual current number of workers. For instance, if a cluster + * is resized from 5 to 10 workers, this field will immediately be updated to reflect + * the target size of 10 workers, whereas the workers listed in `spark_info` will gradually + * increase from 5 to 10 as the new nodes are provisioned. + */ + num_workers?: number | string; + permissions?: Array | string; + /** + * The ID of the cluster policy used to create the cluster if applicable. + */ + policy_id?: string; + runtime_engine?: RuntimeEngine; + /** + * Single user name if data_security_mode is `SINGLE_USER` + */ + single_user_name?: string; + /** + * An object containing a set of optional, user-specified Spark configuration key-value + * pairs. + * Users can also pass in a string of extra JVM options to the driver and the executors via + * `spark.driver.extraJavaOptions` and `spark.executor.extraJavaOptions` respectively. + */ + spark_conf?: {[key: string]: string} | string; + /** + * An object containing a set of optional, user-specified environment variable key-value + * pairs. + * Please note that key-value pair of the form (X,Y) will be exported as is (i.e., + * `export X='Y'`) while launching the driver and workers. + * + * In order to specify an additional set of `SPARK_DAEMON_JAVA_OPTS`, we recommend appending + * them to `$SPARK_DAEMON_JAVA_OPTS` as shown in the example below. This ensures that all + * default databricks managed environmental variables are included as well. + * + * Example Spark environment variables: + * `{"SPARK_WORKER_MEMORY": "28000m", "SPARK_LOCAL_DIRS": "/local_disk0"}` or + * `{"SPARK_DAEMON_JAVA_OPTS": "$SPARK_DAEMON_JAVA_OPTS + * -Dspark.shuffle.service.enabled=true"}` + */ + spark_env_vars?: {[key: string]: string} | string; + /** + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + */ + spark_version?: string; + /** + * SSH public key contents that will be added to each Spark node in this cluster. The + * corresponding private keys can be used to login with the user name `ubuntu` on port + * `2200`. + * Up to 10 keys can be specified. + */ + ssh_public_keys?: string[] | string; + workload_type?: WorkloadTypeClass | string; +} + +export interface StickyBundleSchem { + /** + * The maximum number of workers to which the cluster can scale up when overloaded. + * Note that `max_workers` must be strictly greater than `min_workers`. + */ + max_workers?: number | string; + /** + * The minimum number of workers to which the cluster can scale down when underutilized. + * It is also the initial number of workers the cluster will have after creation. + */ + min_workers?: number | string; +} + +export interface AwsAttributesClass { + availability?: AwsAttributesAvailability; + /** + * The number of volumes launched for each instance. Users can choose up to 10 volumes. + * This feature is only enabled for supported node types. Legacy node types cannot specify + * custom EBS volumes. + * For node types with no instance store, at least one EBS volume needs to be specified; + * otherwise, cluster creation will fail. + * + * These EBS volumes will be mounted at `/ebs0`, `/ebs1`, and etc. + * Instance store volumes will be mounted at `/local_disk0`, `/local_disk1`, and etc. + * + * If EBS volumes are attached, Databricks will configure Spark to use only the EBS volumes + * for + * scratch storage because heterogenously sized scratch devices can lead to inefficient disk + * utilization. If no EBS volumes are attached, Databricks will configure Spark to use + * instance + * store volumes. + * + * Please note that if EBS volumes are specified, then the Spark configuration + * `spark.local.dir` + * will be overridden. + */ + ebs_volume_count?: number | string; + /** + * If using gp3 volumes, what IOPS to use for the disk. If this is not set, the maximum + * performance of a gp2 volume with the same volume size will be used. + */ + ebs_volume_iops?: number | string; + /** + * The size of each EBS volume (in GiB) launched for each instance. For general purpose + * SSD, this value must be within the range 100 - 4096. For throughput optimized HDD, + * this value must be within the range 500 - 4096. + */ + ebs_volume_size?: number | string; + /** + * If using gp3 volumes, what throughput to use for the disk. If this is not set, the + * maximum performance of a gp2 volume with the same volume size will be used. + */ + ebs_volume_throughput?: number | string; + ebs_volume_type?: EbsVolumeType; + /** + * The first `first_on_demand` nodes of the cluster will be placed on on-demand instances. + * If this value is greater than 0, the cluster driver node in particular will be placed on + * an + * on-demand instance. If this value is greater than or equal to the current cluster size, + * all + * nodes will be placed on on-demand instances. If this value is less than the current + * cluster + * size, `first_on_demand` nodes will be placed on on-demand instances and the remainder + * will + * be placed on `availability` instances. Note that this value does not affect + * cluster size and cannot currently be mutated over the lifetime of a cluster. + */ + first_on_demand?: number | string; + /** + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + */ + instance_profile_arn?: string; + /** + * The bid price for AWS spot instances, as a percentage of the corresponding instance + * type's + * on-demand price. + * For example, if this field is set to 50, and the cluster needs a new `r3.xlarge` spot + * instance, then the bid price is half of the price of + * on-demand `r3.xlarge` instances. Similarly, if this field is set to 200, the bid price is + * twice + * the price of on-demand `r3.xlarge` instances. If not specified, the default value is 100. + * When spot instances are requested for this cluster, only spot instances whose bid price + * percentage matches this field will be considered. + * Note that, for safety, we enforce this field to be no more than 10000. + * + * The default value and documentation here should be kept consistent with + * CommonConf.defaultSpotBidPricePercent and CommonConf.maxSpotBidPricePercent. + */ + spot_bid_price_percent?: number | string; + /** + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + */ + zone_id?: string; +} + +/** + * Availability type used for all subsequent nodes past the `first_on_demand` ones. + * + * Note: If `first_on_demand` is zero, this availability type will be used for the entire + * cluster. + */ +export enum AwsAttributesAvailability { + OnDemand = "ON_DEMAND", + Spot = "SPOT", + SpotWithFallback = "SPOT_WITH_FALLBACK", +} + +/** + * The type of EBS volumes that will be launched with this cluster. + */ +export enum EbsVolumeType { + GeneralPurposeSSD = "GENERAL_PURPOSE_SSD", + ThroughputOptimizedHDD = "THROUGHPUT_OPTIMIZED_HDD", +} + +export interface AzureAttributesClass { + availability?: AzureAttributesAvailability; + /** + * The first `first_on_demand` nodes of the cluster will be placed on on-demand instances. + * This value should be greater than 0, to make sure the cluster driver node is placed on an + * on-demand instance. If this value is greater than or equal to the current cluster size, + * all + * nodes will be placed on on-demand instances. If this value is less than the current + * cluster + * size, `first_on_demand` nodes will be placed on on-demand instances and the remainder + * will + * be placed on `availability` instances. Note that this value does not affect + * cluster size and cannot currently be mutated over the lifetime of a cluster. + */ + first_on_demand?: number | string; + /** + * Defines values necessary to configure and run Azure Log Analytics agent + */ + log_analytics_info?: LogAnalyticsInfoClass | string; + /** + * The max bid price to be used for Azure spot instances. + * The Max price for the bid cannot be higher than the on-demand price of the instance. + * If not specified, the default value is -1, which specifies that the instance cannot be + * evicted + * on the basis of price, and only on the basis of availability. Further, the value should > + * 0 or -1. + */ + spot_bid_max_price?: number | string; +} + +/** + * Availability type used for all subsequent nodes past the `first_on_demand` ones. + * Note: If `first_on_demand` is zero (which only happens on pool clusters), this + * availability + * type will be used for the entire cluster. + */ +export enum AzureAttributesAvailability { + OnDemandAzure = "ON_DEMAND_AZURE", + SpotAzure = "SPOT_AZURE", + SpotWithFallbackAzure = "SPOT_WITH_FALLBACK_AZURE", +} + +export interface LogAnalyticsInfoClass { + /** + * + */ + log_analytics_primary_key?: string; + /** + * + */ + log_analytics_workspace_id?: string; +} + +export interface ClusterLogConfClass { + /** + * destination needs to be provided. e.g. + * `{ "dbfs" : { "destination" : "dbfs:/home/cluster_log" } }` + */ + dbfs?: DbfsClass | string; + /** + * destination and either the region or endpoint need to be provided. e.g. + * `{ "s3": { "destination" : "s3://cluster_log_bucket/prefix", "region" : "us-west-2" } }` + * Cluster iam role is used to access s3, please make sure the cluster iam role in + * `instance_profile_arn` has permission to write data to the s3 destination. + */ + s3?: S3Class | string; +} + +export interface DbfsClass { + /** + * dbfs destination, e.g. `dbfs:/my/path` + */ + destination: string; +} + +export interface S3Class { + /** + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + */ + canned_acl?: string; + /** + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + */ + destination: string; + /** + * (Optional) Flag to enable server side encryption, `false` by default. + */ + enable_encryption?: boolean | string; + /** + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + */ + encryption_type?: string; + /** + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + */ + endpoint?: string; + /** + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + */ + kms_key?: string; + /** + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + */ + region?: string; +} + +/** + * Data security mode decides what data governance model to use when accessing data + * from a cluster. + * + * * `NONE`: No security isolation for multiple users sharing the cluster. Data governance + * features are not available in this mode. + * * `SINGLE_USER`: A secure cluster that can only be exclusively used by a single user + * specified in `single_user_name`. Most programming languages, cluster features and data + * governance features are available in this mode. + * * `USER_ISOLATION`: A secure cluster that can be shared by multiple users. Cluster users + * are fully isolated so that they cannot see each other's data and credentials. Most data + * governance features are supported in this mode. But programming languages and cluster + * features might be limited. + * + * The following modes are deprecated starting with Databricks Runtime 15.0 and + * will be removed for future Databricks Runtime versions: + * + * * `LEGACY_TABLE_ACL`: This mode is for users migrating from legacy Table ACL clusters. + * * `LEGACY_PASSTHROUGH`: This mode is for users migrating from legacy Passthrough on high + * concurrency clusters. + * * `LEGACY_SINGLE_USER`: This mode is for users migrating from legacy Passthrough on + * standard clusters. + * * `LEGACY_SINGLE_USER_STANDARD`: This mode provides a way that doesn’t have UC nor + * passthrough enabled. + */ +export enum DataSecurityMode { + LegacyPassthrough = "LEGACY_PASSTHROUGH", + LegacySingleUser = "LEGACY_SINGLE_USER", + LegacySingleUserStandard = "LEGACY_SINGLE_USER_STANDARD", + LegacyTableACL = "LEGACY_TABLE_ACL", + None = "NONE", + SingleUser = "SINGLE_USER", + UserIsolation = "USER_ISOLATION", +} + +export interface DockerImageClass { + basic_auth?: BasicAuthClass | string; + /** + * URL of the docker image. + */ + url?: string; +} + +export interface BasicAuthClass { + /** + * Password of the user + */ + password?: string; + /** + * Name of the user + */ + username?: string; +} + +export interface GcpAttributesClass { + availability?: GcpAttributesAvailability; + /** + * boot disk size in GB + */ + boot_disk_size?: number | string; + /** + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + */ + google_service_account?: string; + /** + * If provided, each node (workers and driver) in the cluster will have this number of local + * SSDs attached. Each local SSD is 375GB in size. Refer to [GCP + * documentation](https://cloud.google.com/compute/docs/disks/local-ssd#choose_number_local_ssds) + * for the supported number of local SSDs for each instance type. + */ + local_ssd_count?: number | string; + /** + * This field determines whether the spark executors will be scheduled to run on preemptible + * VMs (when set to true) versus standard compute engine VMs (when set to false; default). + * Note: Soon to be deprecated, use the availability field instead. + */ + use_preemptible_executors?: boolean | string; + /** + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + */ + zone_id?: string; +} + +/** + * This field determines whether the instance pool will contain preemptible + * VMs, on-demand VMs, or preemptible VMs with a fallback to on-demand VMs if the former is + * unavailable. + */ +export enum GcpAttributesAvailability { + OnDemandGcp = "ON_DEMAND_GCP", + PreemptibleGcp = "PREEMPTIBLE_GCP", + PreemptibleWithFallbackGcp = "PREEMPTIBLE_WITH_FALLBACK_GCP", +} + +export interface InitScriptClass { + /** + * destination needs to be provided. e.g. + * `{ "abfss" : { "destination" : + * "abfss://@.dfs.core.windows.net/" } + * } + */ + abfss?: AbfssClass | string; + /** + * destination needs to be provided. e.g. + * `{ "dbfs" : { "destination" : "dbfs:/home/cluster_log" } }` + */ + dbfs?: DbfsClass | string; + /** + * destination needs to be provided. e.g. + * `{ "file" : { "destination" : "file:/my/local/file.sh" } }` + */ + file?: IndigoBundleSchem | string; + /** + * destination needs to be provided. e.g. + * `{ "gcs": { "destination": "gs://my-bucket/file.sh" } }` + */ + gcs?: GcsClass | string; + /** + * destination and either the region or endpoint need to be provided. e.g. + * `{ "s3": { "destination" : "s3://cluster_log_bucket/prefix", "region" : "us-west-2" } }` + * Cluster iam role is used to access s3, please make sure the cluster iam role in + * `instance_profile_arn` has permission to write data to the s3 destination. + */ + s3?: S3Class | string; + /** + * destination needs to be provided. e.g. + * `{ "volumes" : { "destination" : "/Volumes/my-init.sh" } }` + */ + volumes?: VolumesClass | string; + /** + * destination needs to be provided. e.g. + * `{ "workspace" : { "destination" : "/Users/user1@databricks.com/my-init.sh" } }` + */ + workspace?: IndecentBundleSchem | string; +} + +export interface AbfssClass { + /** + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + */ + destination: string; +} + +export interface IndigoBundleSchem { + /** + * local file destination, e.g. `file:/my/local/file.sh` + */ + destination: string; +} + +export interface GcsClass { + /** + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + */ + destination: string; +} + +export interface VolumesClass { + /** + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + */ + destination: string; +} + +export interface IndecentBundleSchem { + /** + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + */ + destination: string; +} + +/** + * Determines the cluster's runtime engine, either standard or Photon. + * + * This field is not compatible with legacy `spark_version` values that contain `-photon-`. + * Remove `-photon-` from the `spark_version` and set `runtime_engine` to `PHOTON`. + * + * If left unspecified, the runtime engine defaults to standard unless the spark_version + * contains -photon-, in which case Photon will be used. + */ +export enum RuntimeEngine { + Null = "NULL", + Photon = "PHOTON", + Standard = "STANDARD", +} + +export interface WorkloadTypeClass { + /** + * defined what type of clients can use the cluster. E.g. Notebooks, Jobs + */ + clients: ClientsClass | string; +} + +export interface ClientsClass { + /** + * With jobs set, the cluster can be used for jobs + */ + jobs?: boolean | string; + /** + * With notebooks set, this cluster can be used for notebooks + */ + notebooks?: boolean | string; +} + +export interface ExperimentClass { + /** + * Location where artifacts for the experiment are stored. + */ + artifact_location?: string; + /** + * Creation time + */ + creation_time?: number | string; + /** + * Unique identifier for the experiment. + */ + experiment_id?: string; + /** + * Last update time + */ + last_update_time?: number | string; + /** + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + */ + lifecycle_stage?: string; + /** + * Human readable name that identifies the experiment. + */ + name?: string; + permissions?: Array | string; + /** + * Tags: Additional metadata key-value pairs. + */ + tags?: Array | string; +} + +export interface HilariousBundleSchem { + /** + * The tag key. + */ + key?: string; + /** + * The tag value. + */ + value?: string; +} + +export interface JobClass { + /** + * An optional continuous property for this job. The continuous property will ensure that + * there is always one run executing. Only one of `schedule` and `continuous` can be used. + */ + continuous?: ContinuousClass | string; + /** + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + */ + description?: string; + /** + * An optional set of email addresses that is notified when runs of this job begin or + * complete as well as when this job is deleted. + */ + email_notifications?: AmbitiousBundleSchem | string; + /** + * A list of task execution environment specifications that can be referenced by serverless + * tasks of this job. + * An environment is required to be present for serverless tasks. + * For serverless notebook tasks, the environment is accessible in the notebook environment + * panel. + * For other serverless tasks, the task environment is required to be specified using + * environment_key in the task settings. + */ + environments?: Array | string; + /** + * An optional specification for a remote Git repository containing the source code used by + * tasks. Version-controlled source code is supported by notebook, dbt, Python script, and + * SQL File tasks. + * + * If `git_source` is set, these tasks retrieve the file from the remote repository by + * default. However, this behavior can be overridden by setting `source` to `WORKSPACE` on + * the task. + * + * Note: dbt and SQL File tasks support only version-controlled sources. If dbt or SQL File + * tasks are used, `git_source` must be defined on the job. + */ + git_source?: GitSourceClass | string; + health?: HealthClass | string; + /** + * A list of job cluster specifications that can be shared and reused by tasks of this job. + * Libraries cannot be declared in a shared job cluster. You must declare dependent + * libraries in task settings. + */ + job_clusters?: Array | string; + /** + * An optional maximum allowed number of concurrent runs of the job. + * Set this value if you want to be able to execute multiple runs of the same job + * concurrently. + * This is useful for example if you trigger your job on a frequent schedule and want to + * allow consecutive runs to overlap with each other, or if you want to trigger multiple + * runs which differ by their input parameters. + * This setting affects only new runs. For example, suppose the job’s concurrency is 4 and + * there are 4 concurrent active runs. Then setting the concurrency to 3 won’t kill any of + * the active runs. + * However, from then on, new runs are skipped unless there are fewer than 3 active runs. + * This value cannot exceed 1000. Setting this value to `0` causes all new runs to be + * skipped. + */ + max_concurrent_runs?: number | string; + /** + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + */ + name?: string; + /** + * Optional notification settings that are used when sending notifications to each of the + * `email_notifications` and `webhook_notifications` for this job. + */ + notification_settings?: CunningBundleSchem | string; + /** + * Job-level parameter definitions + */ + parameters?: Array | string; + permissions?: Array | string; + /** + * The queue settings of the job. + */ + queue?: QueueClass | string; + run_as?: RunAsClass | string; + /** + * An optional periodic schedule for this job. The default behavior is that the job only + * runs when triggered by clicking “Run Now” in the Jobs UI or sending an API request to + * `runNow`. + */ + schedule?: MagentaBundleSchem | string; + /** + * A map of tags associated with the job. These are forwarded to the cluster as cluster tags + * for jobs clusters, and are subject to the same limitations as cluster tags. A maximum of + * 25 tags can be added to the job. + */ + tags?: {[key: string]: string} | string; + /** + * A list of task specifications to be executed by this job. + */ + tasks?: Array | string; + /** + * An optional timeout applied to each run of this job. A value of `0` means no timeout. + */ + timeout_seconds?: number | string; + /** + * A configuration to trigger a run when certain conditions are met. The default behavior is + * that the job runs only when triggered by clicking “Run Now” in the Jobs UI or sending an + * API request to `runNow`. + */ + trigger?: BundleSchem2 | string; + /** + * A collection of system notification IDs to notify when runs of this job begin or complete. + */ + webhook_notifications?: WebhookNotificationsClass | string; +} + +export interface ContinuousClass { + /** + * Indicate whether the continuous execution of the job is paused or not. Defaults to + * UNPAUSED. + */ + pause_status?: PauseStatus; +} + +/** + * Indicate whether the continuous execution of the job is paused or not. Defaults to + * UNPAUSED. + * + * Indicate whether this schedule is paused or not. + * + * Whether this trigger is paused or not. + * + * Read only field that indicates whether a schedule is paused or not. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + */ +export enum PauseStatus { + Paused = "PAUSED", + Unpaused = "UNPAUSED", +} + +export interface AmbitiousBundleSchem { + /** + * If true, do not send email to recipients specified in `on_failure` if the run is skipped. + * This field is `deprecated`. Please use the + * `notification_settings.no_alert_for_skipped_runs` field. + */ + no_alert_for_skipped_runs?: boolean | string; + /** + * A list of email addresses to be notified when the duration of a run exceeds the threshold + * specified for the `RUN_DURATION_SECONDS` metric in the `health` field. If no rule for the + * `RUN_DURATION_SECONDS` metric is specified in the `health` field for the job, + * notifications are not sent. + */ + on_duration_warning_threshold_exceeded?: string[] | string; + /** + * A list of email addresses to be notified when a run unsuccessfully completes. A run is + * considered to have completed unsuccessfully if it ends with an `INTERNAL_ERROR` + * `life_cycle_state` or a `FAILED`, or `TIMED_OUT` result_state. If this is not specified + * on job creation, reset, or update the list is empty, and notifications are not sent. + */ + on_failure?: string[] | string; + /** + * A list of email addresses to be notified when a run begins. If not specified on job + * creation, reset, or update, the list is empty, and notifications are not sent. + */ + on_start?: string[] | string; + /** + * A list of email addresses to notify when any streaming backlog thresholds are exceeded + * for any stream. + * Streaming backlog thresholds can be set in the `health` field using the following + * metrics: `STREAMING_BACKLOG_BYTES`, `STREAMING_BACKLOG_RECORDS`, + * `STREAMING_BACKLOG_SECONDS`, or `STREAMING_BACKLOG_FILES`. + * Alerting is based on the 10-minute average of these metrics. If the issue persists, + * notifications are resent every 30 minutes. + */ + on_streaming_backlog_exceeded?: string[] | string; + /** + * A list of email addresses to be notified when a run successfully completes. A run is + * considered to have completed successfully if it ends with a `TERMINATED` + * `life_cycle_state` and a `SUCCESS` result_state. If not specified on job creation, reset, + * or update, the list is empty, and notifications are not sent. + */ + on_success?: string[] | string; +} + +export interface EnvironmentClass { + /** + * The key of an environment. It has to be unique within a job. + */ + environment_key: string; + spec?: SpecClass | string; +} + +/** + * The environment entity used to preserve serverless environment side panel and jobs' + * environment for non-notebook task. + * In this minimal environment spec, only pip dependencies are supported. + */ +export interface SpecClass { + /** + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + */ + client: string; + /** + * List of pip dependencies, as supported by the version of pip in this environment. + * Each dependency is a pip requirement file line + * https://pip.pypa.io/en/stable/reference/requirements-file-format/ + * Allowed dependency could be , , (WSFS or Volumes in Databricks), + * E.g. dependencies: ["foo==0.0.1", "-r /Workspace/test/requirements.txt"] + */ + dependencies?: string[] | string; +} + +/** + * An optional specification for a remote Git repository containing the source code used by + * tasks. Version-controlled source code is supported by notebook, dbt, Python script, and + * SQL File tasks. + * + * If `git_source` is set, these tasks retrieve the file from the remote repository by + * default. However, this behavior can be overridden by setting `source` to `WORKSPACE` on + * the task. + * + * Note: dbt and SQL File tasks support only version-controlled sources. If dbt or SQL File + * tasks are used, `git_source` must be defined on the job. + */ +export interface GitSourceClass { + /** + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + */ + git_branch?: string; + /** + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + */ + git_commit?: string; + /** + * Unique identifier of the service used to host the Git repository. The value is case + * insensitive. + */ + git_provider: GitProvider; + /** + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + */ + git_tag?: string; + /** + * URL of the repository to be cloned by this job. + */ + git_url: string; +} + +/** + * Unique identifier of the service used to host the Git repository. The value is case + * insensitive. + */ +export enum GitProvider { + AwsCodeCommit = "awsCodeCommit", + AzureDevOpsServices = "azureDevOpsServices", + BitbucketCloud = "bitbucketCloud", + BitbucketServer = "bitbucketServer", + GitHub = "gitHub", + GitHubEnterprise = "gitHubEnterprise", + GitLab = "gitLab", + GitLabEnterpriseEdition = "gitLabEnterpriseEdition", +} + +/** + * An optional set of health rules that can be defined for this job. + */ +export interface HealthClass { + rules?: Array | string; +} + +export interface RuleClass { + metric: Metric; + op: RuleOp; + /** + * Specifies the threshold value that the health metric should obey to satisfy the health + * rule. + */ + value: number | string; +} + +/** + * Specifies the health metric that is being evaluated for a particular health rule. + * + * * `RUN_DURATION_SECONDS`: Expected total time for a run in seconds. + * * `STREAMING_BACKLOG_BYTES`: An estimate of the maximum bytes of data waiting to be + * consumed across all streams. This metric is in Private Preview. + * * `STREAMING_BACKLOG_RECORDS`: An estimate of the maximum offset lag across all streams. + * This metric is in Private Preview. + * * `STREAMING_BACKLOG_SECONDS`: An estimate of the maximum consumer delay across all + * streams. This metric is in Private Preview. + * * `STREAMING_BACKLOG_FILES`: An estimate of the maximum number of outstanding files + * across all streams. This metric is in Private Preview. + */ +export enum Metric { + RunDurationSeconds = "RUN_DURATION_SECONDS", + StreamingBacklogBytes = "STREAMING_BACKLOG_BYTES", + StreamingBacklogFiles = "STREAMING_BACKLOG_FILES", + StreamingBacklogRecords = "STREAMING_BACKLOG_RECORDS", + StreamingBacklogSeconds = "STREAMING_BACKLOG_SECONDS", +} + +/** + * Specifies the operator used to compare the health metric value with the specified + * threshold. + */ +export enum RuleOp { + GreaterThan = "GREATER_THAN", +} + +export interface JobClusterClass { + /** + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + */ + job_cluster_key: string; + /** + * If new_cluster, a description of a cluster that is created for each task. + */ + new_cluster: NewClusterClass | string; +} + +export interface NewClusterClass { + /** + * When set to true, fixed and default values from the policy will be used for fields that + * are omitted. When set to false, only fixed values from the policy will be applied. + */ + apply_policy_default_values?: boolean | string; + /** + * Parameters needed in order to automatically scale clusters up and down based on load. + * Note: autoscaling works best with DB runtime versions 3.0 or later. + */ + autoscale?: StickyBundleSchem | string; + /** + * Automatically terminates the cluster after it is inactive for this time in minutes. If + * not set, + * this cluster will not be automatically terminated. If specified, the threshold must be + * between + * 10 and 10000 minutes. + * Users can also set this value to 0 to explicitly disable automatic termination. + */ + autotermination_minutes?: number | string; + /** + * Attributes related to clusters running on Amazon Web Services. + * If not specified at cluster creation, a set of default values will be used. + */ + aws_attributes?: AwsAttributesClass | string; + /** + * Attributes related to clusters running on Microsoft Azure. + * If not specified at cluster creation, a set of default values will be used. + */ + azure_attributes?: AzureAttributesClass | string; + /** + * The configuration for delivering spark logs to a long-term storage destination. + * Two kinds of destinations (dbfs and s3) are supported. Only one destination can be + * specified + * for one cluster. If the conf is given, the logs will be delivered to the destination + * every + * `5 mins`. The destination of driver logs is `$destination/$clusterId/driver`, while + * the destination of executor logs is `$destination/$clusterId/executor`. + */ + cluster_log_conf?: ClusterLogConfClass | string; + /** + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + */ + cluster_name?: string; + /** + * Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., + * AWS + * instances and EBS volumes) with these tags in addition to `default_tags`. Notes: + * + * - Currently, Databricks allows at most 45 custom tags + * + * - Clusters can only reuse cloud resources if the resources' tags are a subset of the + * cluster tags + */ + custom_tags?: {[key: string]: string} | string; + data_security_mode?: DataSecurityMode; + docker_image?: DockerImageClass | string; + /** + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + */ + driver_instance_pool_id?: string; + /** + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + */ + driver_node_type_id?: string; + /** + * Autoscaling Local Storage: when enabled, this cluster will dynamically acquire additional + * disk + * space when its Spark workers are running low on disk space. This feature requires + * specific AWS + * permissions to function correctly - refer to the User Guide for more details. + */ + enable_elastic_disk?: boolean | string; + /** + * Whether to enable LUKS on cluster VMs' local disks + */ + enable_local_disk_encryption?: boolean | string; + /** + * Attributes related to clusters running on Google Cloud Platform. + * If not specified at cluster creation, a set of default values will be used. + */ + gcp_attributes?: GcpAttributesClass | string; + /** + * The configuration for storing init scripts. Any number of destinations can be specified. + * The scripts are executed sequentially in the order provided. If `cluster_log_conf` is + * specified, init script logs are sent to `//init_scripts`. + */ + init_scripts?: Array | string; + /** + * The optional ID of the instance pool to which the cluster belongs. + */ + instance_pool_id?: string; + /** + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + */ + node_type_id?: string; + /** + * Number of worker nodes that this cluster should have. A cluster has one Spark Driver + * and `num_workers` Executors for a total of `num_workers` + 1 Spark nodes. + * + * Note: When reading the properties of a cluster, this field reflects the desired number + * of workers rather than the actual current number of workers. For instance, if a cluster + * is resized from 5 to 10 workers, this field will immediately be updated to reflect + * the target size of 10 workers, whereas the workers listed in `spark_info` will gradually + * increase from 5 to 10 as the new nodes are provisioned. + */ + num_workers?: number | string; + /** + * The ID of the cluster policy used to create the cluster if applicable. + */ + policy_id?: string; + runtime_engine?: RuntimeEngine; + /** + * Single user name if data_security_mode is `SINGLE_USER` + */ + single_user_name?: string; + /** + * An object containing a set of optional, user-specified Spark configuration key-value + * pairs. + * Users can also pass in a string of extra JVM options to the driver and the executors via + * `spark.driver.extraJavaOptions` and `spark.executor.extraJavaOptions` respectively. + */ + spark_conf?: {[key: string]: string} | string; + /** + * An object containing a set of optional, user-specified environment variable key-value + * pairs. + * Please note that key-value pair of the form (X,Y) will be exported as is (i.e., + * `export X='Y'`) while launching the driver and workers. + * + * In order to specify an additional set of `SPARK_DAEMON_JAVA_OPTS`, we recommend appending + * them to `$SPARK_DAEMON_JAVA_OPTS` as shown in the example below. This ensures that all + * default databricks managed environmental variables are included as well. + * + * Example Spark environment variables: + * `{"SPARK_WORKER_MEMORY": "28000m", "SPARK_LOCAL_DIRS": "/local_disk0"}` or + * `{"SPARK_DAEMON_JAVA_OPTS": "$SPARK_DAEMON_JAVA_OPTS + * -Dspark.shuffle.service.enabled=true"}` + */ + spark_env_vars?: {[key: string]: string} | string; + /** + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + */ + spark_version?: string; + /** + * SSH public key contents that will be added to each Spark node in this cluster. The + * corresponding private keys can be used to login with the user name `ubuntu` on port + * `2200`. + * Up to 10 keys can be specified. + */ + ssh_public_keys?: string[] | string; + workload_type?: WorkloadTypeClass | string; +} + +export interface CunningBundleSchem { + /** + * If true, do not send notifications to recipients specified in `on_failure` if the run is + * canceled. + */ + no_alert_for_canceled_runs?: boolean | string; + /** + * If true, do not send notifications to recipients specified in `on_failure` if the run is + * skipped. + */ + no_alert_for_skipped_runs?: boolean | string; +} + +export interface ParameterClass { + /** + * Default value of the parameter. + */ + default: string; + /** + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + */ + name: string; +} + +export interface QueueClass { + /** + * If true, enable queueing for the job. This is a required field. + */ + enabled: boolean | string; +} + +/** + * Write-only setting. Specifies the user, service principal or group that the job/pipeline + * runs as. If not specified, the job/pipeline runs as the user who created the + * job/pipeline. + * + * Exactly one of `user_name`, `service_principal_name`, `group_name` should be specified. + * If not, an error is thrown. + */ +export interface RunAsClass { + /** + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + */ + service_principal_name?: string; + /** + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + */ + user_name?: string; +} + +export interface MagentaBundleSchem { + /** + * Indicate whether this schedule is paused or not. + */ + pause_status?: PauseStatus; + /** + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + */ + quartz_cron_expression: string; + /** + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + */ + timezone_id: string; +} + +export interface ForEachTaskClass { + /** + * An optional maximum allowed number of concurrent runs of the task. + * Set this value if you want to be able to execute multiple runs of the task concurrently. + */ + concurrency?: number | string; + /** + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + */ + inputs: string; + /** + * Configuration for the task that will be run for each element in the array + */ + task: TaskClass | string; +} + +export interface TaskClass { + /** + * If condition_task, specifies a condition with an outcome that can be used to control the + * execution of other tasks. Does not require a cluster to execute and does not support + * retries or notifications. + */ + condition_task?: ConditionTaskClass | string; + /** + * If dbt_task, indicates that this must execute a dbt task. It requires both Databricks SQL + * and the ability to use a serverless or a pro SQL warehouse. + */ + dbt_task?: DbtTaskClass | string; + /** + * An optional array of objects specifying the dependency graph of the task. All tasks + * specified in this field must complete before executing this task. The task will run only + * if the `run_if` condition is true. + * The key is `task_key`, and the value is the name assigned to the dependent task. + */ + depends_on?: Array | string; + /** + * An optional description for this task. + */ + description?: string; + /** + * An option to disable auto optimization in serverless + */ + disable_auto_optimization?: boolean | string; + /** + * An optional set of email addresses that is notified when runs of this task begin or + * complete as well as when this task is deleted. The default behavior is to not send any + * emails. + */ + email_notifications?: FriskyBundleSchem | string; + /** + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + */ + environment_key?: string; + /** + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + */ + existing_cluster_id?: string; + /** + * If for_each_task, indicates that this task must execute the nested task within it. + */ + for_each_task?: ForEachTaskClass | string; + health?: HealthClass | string; + /** + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + */ + job_cluster_key?: string; + /** + * An optional list of libraries to be installed on the cluster. + * The default value is an empty list. + */ + libraries?: Array | string; + /** + * An optional maximum number of times to retry an unsuccessful run. A run is considered to + * be unsuccessful if it completes with the `FAILED` result_state or `INTERNAL_ERROR` + * `life_cycle_state`. The value `-1` means to retry indefinitely and the value `0` means to + * never retry. + */ + max_retries?: number | string; + /** + * An optional minimal interval in milliseconds between the start of the failed run and the + * subsequent retry run. The default behavior is that unsuccessful runs are immediately + * retried. + */ + min_retry_interval_millis?: number | string; + /** + * If new_cluster, a description of a new cluster that is created for each run. + */ + new_cluster?: NewClusterClass | string; + /** + * If notebook_task, indicates that this task must run a notebook. This field may not be + * specified in conjunction with spark_jar_task. + */ + notebook_task?: NotebookTaskClass | string; + /** + * Optional notification settings that are used when sending notifications to each of the + * `email_notifications` and `webhook_notifications` for this task. + */ + notification_settings?: BraggadociousBundleSchem | string; + /** + * If pipeline_task, indicates that this task must execute a Pipeline. + */ + pipeline_task?: PipelineTaskClass | string; + /** + * If python_wheel_task, indicates that this job must execute a PythonWheel. + */ + python_wheel_task?: PythonWheelTaskClass | string; + /** + * An optional policy to specify whether to retry a job when it times out. The default + * behavior + * is to not retry on timeout. + */ + retry_on_timeout?: boolean | string; + /** + * An optional value specifying the condition determining whether the task is run once its + * dependencies have been completed. + * + * * `ALL_SUCCESS`: All dependencies have executed and succeeded + * * `AT_LEAST_ONE_SUCCESS`: At least one dependency has succeeded + * * `NONE_FAILED`: None of the dependencies have failed and at least one was executed + * * `ALL_DONE`: All dependencies have been completed + * * `AT_LEAST_ONE_FAILED`: At least one dependency failed + * * `ALL_FAILED`: ALl dependencies have failed + */ + run_if?: RunIf; + /** + * If run_job_task, indicates that this task must execute another job. + */ + run_job_task?: RunJobTaskClass | string; + /** + * If spark_jar_task, indicates that this task must run a JAR. + */ + spark_jar_task?: SparkJarTaskClass | string; + /** + * If spark_python_task, indicates that this task must run a Python file. + */ + spark_python_task?: SparkPythonTaskClass | string; + /** + * If `spark_submit_task`, indicates that this task must be launched by the spark submit + * script. This task can run only on new clusters. + * + * In the `new_cluster` specification, `libraries` and `spark_conf` are not supported. + * Instead, use `--jars` and `--py-files` to add Java and Python libraries and `--conf` to + * set the Spark configurations. + * + * `master`, `deploy-mode`, and `executor-cores` are automatically configured by Databricks; + * you _cannot_ specify them in parameters. + * + * By default, the Spark submit job uses all available memory (excluding reserved memory for + * Databricks services). You can set `--driver-memory`, and `--executor-memory` to a smaller + * value to leave some room for off-heap usage. + * + * The `--jars`, `--py-files`, `--files` arguments support DBFS and S3 paths. + */ + spark_submit_task?: SparkSubmitTaskClass | string; + /** + * If sql_task, indicates that this job must execute a SQL task. + */ + sql_task?: SQLTaskClass | string; + /** + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + */ + task_key: string; + /** + * An optional timeout applied to each run of this job task. A value of `0` means no timeout. + */ + timeout_seconds?: number | string; + /** + * A collection of system notification IDs to notify when runs of this task begin or + * complete. The default behavior is to not send any system notifications. + */ + webhook_notifications?: WebhookNotificationsClass | string; +} + +export interface ConditionTaskClass { + /** + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + */ + left: string; + /** + * * `EQUAL_TO`, `NOT_EQUAL` operators perform string comparison of their operands. This + * means that `“12.0” == “12”` will evaluate to `false`. + * * `GREATER_THAN`, `GREATER_THAN_OR_EQUAL`, `LESS_THAN`, `LESS_THAN_OR_EQUAL` operators + * perform numeric comparison of their operands. `“12.0” >= “12”` will evaluate to `true`, + * `“10.0” >= “12”` will evaluate to `false`. + * + * The boolean comparison to task values can be implemented with operators `EQUAL_TO`, + * `NOT_EQUAL`. If a task value was set to a boolean value, it will be serialized to + * `“true”` or `“false”` for the comparison. + */ + op: ConditionTaskOp; + /** + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + */ + right: string; +} + +/** + * * `EQUAL_TO`, `NOT_EQUAL` operators perform string comparison of their operands. This + * means that `“12.0” == “12”` will evaluate to `false`. + * * `GREATER_THAN`, `GREATER_THAN_OR_EQUAL`, `LESS_THAN`, `LESS_THAN_OR_EQUAL` operators + * perform numeric comparison of their operands. `“12.0” >= “12”` will evaluate to `true`, + * `“10.0” >= “12”` will evaluate to `false`. + * + * The boolean comparison to task values can be implemented with operators `EQUAL_TO`, + * `NOT_EQUAL`. If a task value was set to a boolean value, it will be serialized to + * `“true”` or `“false”` for the comparison. + */ +export enum ConditionTaskOp { + EqualTo = "EQUAL_TO", + GreaterThan = "GREATER_THAN", + GreaterThanOrEqual = "GREATER_THAN_OR_EQUAL", + LessThan = "LESS_THAN", + LessThanOrEqual = "LESS_THAN_OR_EQUAL", + NotEqual = "NOT_EQUAL", +} + +export interface DbtTaskClass { + /** + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + */ + catalog?: string; + /** + * A list of dbt commands to execute. All commands must start with `dbt`. This parameter + * must not be empty. A maximum of up to 10 commands can be provided. + */ + commands: string[] | string; + /** + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + */ + profiles_directory?: string; + /** + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + */ + project_directory?: string; + /** + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + */ + schema?: string; + /** + * Optional location type of the project directory. When set to `WORKSPACE`, the project + * will be retrieved + * from the local Databricks workspace. When set to `GIT`, the project will be retrieved + * from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * + * * `WORKSPACE`: Project is located in Databricks workspace. + * * `GIT`: Project is located in cloud Git provider. + */ + source?: Source; + /** + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + */ + warehouse_id?: string; +} + +/** + * Optional location type of the project directory. When set to `WORKSPACE`, the project + * will be retrieved + * from the local Databricks workspace. When set to `GIT`, the project will be retrieved + * from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * + * * `WORKSPACE`: Project is located in Databricks workspace. + * * `GIT`: Project is located in cloud Git provider. + * + * Optional location type of the SQL file. When set to `WORKSPACE`, the SQL file will be + * retrieved\ + * from the local Databricks workspace. When set to `GIT`, the SQL file will be retrieved + * from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * + * * `WORKSPACE`: SQL file is located in Databricks workspace. + * * `GIT`: SQL file is located in cloud Git provider. + * + * Optional location type of the notebook. When set to `WORKSPACE`, the notebook will be + * retrieved from the local Databricks workspace. When set to `GIT`, the notebook will be + * retrieved from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * * `WORKSPACE`: Notebook is located in Databricks workspace. + * * `GIT`: Notebook is located in cloud Git provider. + * + * Optional location type of the Python file. When set to `WORKSPACE` or not specified, the + * file will be retrieved from the local + * Databricks workspace or cloud location (if the `python_file` has a URI format). When set + * to `GIT`, + * the Python file will be retrieved from a Git repository defined in `git_source`. + * + * * `WORKSPACE`: The Python file is located in a Databricks workspace or at a cloud + * filesystem URI. + * * `GIT`: The Python file is located in a remote Git repository. + * + * Optional location type of the SQL file. When set to `WORKSPACE`, the SQL file will be + * retrieved + * from the local Databricks workspace. When set to `GIT`, the SQL file will be retrieved + * from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * + * * `WORKSPACE`: SQL file is located in Databricks workspace. + * * `GIT`: SQL file is located in cloud Git provider. + */ +export enum Source { + Git = "GIT", + Workspace = "WORKSPACE", +} + +export interface DependsOnClass { + /** + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + */ + outcome?: string; + /** + * The name of the task this task depends on. + */ + task_key: string; +} + +export interface FriskyBundleSchem { + /** + * If true, do not send email to recipients specified in `on_failure` if the run is skipped. + * This field is `deprecated`. Please use the + * `notification_settings.no_alert_for_skipped_runs` field. + */ + no_alert_for_skipped_runs?: boolean | string; + /** + * A list of email addresses to be notified when the duration of a run exceeds the threshold + * specified for the `RUN_DURATION_SECONDS` metric in the `health` field. If no rule for the + * `RUN_DURATION_SECONDS` metric is specified in the `health` field for the job, + * notifications are not sent. + */ + on_duration_warning_threshold_exceeded?: string[] | string; + /** + * A list of email addresses to be notified when a run unsuccessfully completes. A run is + * considered to have completed unsuccessfully if it ends with an `INTERNAL_ERROR` + * `life_cycle_state` or a `FAILED`, or `TIMED_OUT` result_state. If this is not specified + * on job creation, reset, or update the list is empty, and notifications are not sent. + */ + on_failure?: string[] | string; + /** + * A list of email addresses to be notified when a run begins. If not specified on job + * creation, reset, or update, the list is empty, and notifications are not sent. + */ + on_start?: string[] | string; + /** + * A list of email addresses to notify when any streaming backlog thresholds are exceeded + * for any stream. + * Streaming backlog thresholds can be set in the `health` field using the following + * metrics: `STREAMING_BACKLOG_BYTES`, `STREAMING_BACKLOG_RECORDS`, + * `STREAMING_BACKLOG_SECONDS`, or `STREAMING_BACKLOG_FILES`. + * Alerting is based on the 10-minute average of these metrics. If the issue persists, + * notifications are resent every 30 minutes. + */ + on_streaming_backlog_exceeded?: string[] | string; + /** + * A list of email addresses to be notified when a run successfully completes. A run is + * considered to have completed successfully if it ends with a `TERMINATED` + * `life_cycle_state` and a `SUCCESS` result_state. If not specified on job creation, reset, + * or update, the list is empty, and notifications are not sent. + */ + on_success?: string[] | string; +} + +export interface MischievousBundleSchem { + /** + * Specification of a CRAN library to be installed as part of the library + */ + cran?: CRANClass | string; + /** + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + */ + egg?: string; + /** + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + */ + jar?: string; + /** + * Specification of a maven library to be installed. For example: + * `{ "coordinates": "org.jsoup:jsoup:1.7.2" }` + */ + maven?: MavenClass | string; + /** + * Specification of a PyPi library to be installed. For example: + * `{ "package": "simplejson" }` + */ + pypi?: PypiClass | string; + /** + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + */ + requirements?: string; + /** + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + */ + whl?: string; +} + +export interface CRANClass { + /** + * The name of the CRAN package to install. + */ + package: string; + /** + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + */ + repo?: string; +} + +export interface MavenClass { + /** + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + */ + coordinates: string; + /** + * List of dependences to exclude. For example: `["slf4j:slf4j", "*:hadoop-client"]`. + * + * Maven dependency exclusions: + * + * https://maven.apache.org/guides/introduction/introduction-to-optional-and-excludes-dependencies.html. + */ + exclusions?: string[] | string; + /** + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + */ + repo?: string; +} + +export interface PypiClass { + /** + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + */ + package: string; + /** + * The repository where the package can be found. If not specified, the default pip index is + * used. + */ + repo?: string; +} + +export interface NotebookTaskClass { + /** + * Base parameters to be used for each run of this job. If the run is initiated by a call to + * :method:jobs/run + * Now with parameters specified, the two parameters maps are merged. If the same key is + * specified in + * `base_parameters` and in `run-now`, the value from `run-now` is used. + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + * + * If the notebook takes a parameter that is not specified in the job’s `base_parameters` or + * the `run-now` override parameters, + * the default value from the notebook is used. + * + * Retrieve these parameters in a notebook using + * [dbutils.widgets.get](https://docs.databricks.com/dev-tools/databricks-utils.html#dbutils-widgets). + * + * The JSON representation of this field cannot exceed 1MB. + */ + base_parameters?: {[key: string]: string} | string; + /** + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + */ + notebook_path: string; + /** + * Optional location type of the notebook. When set to `WORKSPACE`, the notebook will be + * retrieved from the local Databricks workspace. When set to `GIT`, the notebook will be + * retrieved from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * * `WORKSPACE`: Notebook is located in Databricks workspace. + * * `GIT`: Notebook is located in cloud Git provider. + */ + source?: Source; + /** + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + */ + warehouse_id?: string; +} + +export interface BraggadociousBundleSchem { + /** + * If true, do not send notifications to recipients specified in `on_start` for the retried + * runs and do not send notifications to recipients specified in `on_failure` until the last + * retry of the run. + */ + alert_on_last_attempt?: boolean | string; + /** + * If true, do not send notifications to recipients specified in `on_failure` if the run is + * canceled. + */ + no_alert_for_canceled_runs?: boolean | string; + /** + * If true, do not send notifications to recipients specified in `on_failure` if the run is + * skipped. + */ + no_alert_for_skipped_runs?: boolean | string; +} + +export interface PipelineTaskClass { + /** + * If true, triggers a full refresh on the delta live table. + */ + full_refresh?: boolean | string; + /** + * The full name of the pipeline task to execute. + */ + pipeline_id: string; +} + +export interface PythonWheelTaskClass { + /** + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + */ + entry_point: string; + /** + * Command-line parameters passed to Python wheel task in the form of `["--name=task", + * "--data=dbfs:/path/to/data.json"]`. Leave it empty if `parameters` is not null. + */ + named_parameters?: {[key: string]: string} | string; + /** + * Name of the package to execute + */ + package_name: string; + /** + * Command-line parameters passed to Python wheel task. Leave it empty if `named_parameters` + * is not null. + */ + parameters?: string[] | string; +} + +/** + * An optional value specifying the condition determining whether the task is run once its + * dependencies have been completed. + * + * * `ALL_SUCCESS`: All dependencies have executed and succeeded + * * `AT_LEAST_ONE_SUCCESS`: At least one dependency has succeeded + * * `NONE_FAILED`: None of the dependencies have failed and at least one was executed + * * `ALL_DONE`: All dependencies have been completed + * * `AT_LEAST_ONE_FAILED`: At least one dependency failed + * * `ALL_FAILED`: ALl dependencies have failed + * + * An optional value indicating the condition that determines whether the task should be run + * once its dependencies have been completed. When omitted, defaults to `ALL_SUCCESS`. + * + * Possible values are: + * * `ALL_SUCCESS`: All dependencies have executed and succeeded + * * `AT_LEAST_ONE_SUCCESS`: At least one dependency has succeeded + * * `NONE_FAILED`: None of the dependencies have failed and at least one was executed + * * `ALL_DONE`: All dependencies have been completed + * * `AT_LEAST_ONE_FAILED`: At least one dependency failed + * * `ALL_FAILED`: ALl dependencies have failed + */ +export enum RunIf { + AllDone = "ALL_DONE", + AllFailed = "ALL_FAILED", + AllSuccess = "ALL_SUCCESS", + AtLeastOneFailed = "AT_LEAST_ONE_FAILED", + AtLeastOneSuccess = "AT_LEAST_ONE_SUCCESS", + NoneFailed = "NONE_FAILED", +} + +export interface RunJobTaskClass { + /** + * An array of commands to execute for jobs with the dbt task, for example `"dbt_commands": + * ["dbt deps", "dbt seed", "dbt deps", "dbt seed", "dbt run"]` + */ + dbt_commands?: string[] | string; + /** + * A list of parameters for jobs with Spark JAR tasks, for example `"jar_params": ["john + * doe", "35"]`. + * The parameters are used to invoke the main function of the main class specified in the + * Spark JAR task. + * If not specified upon `run-now`, it defaults to an empty list. + * jar_params cannot be specified in conjunction with notebook_params. + * The JSON representation of this field (for example `{"jar_params":["john doe","35"]}`) + * cannot exceed 10,000 bytes. + * + * Use [Task parameter variables](/jobs.html\"#parameter-variables\") to set parameters + * containing information about job runs. + */ + jar_params?: string[] | string; + /** + * ID of the job to trigger. + */ + job_id: number | string; + /** + * Job-level parameters used to trigger the job. + */ + job_parameters?: {[key: string]: string} | string; + /** + * A map from keys to values for jobs with notebook task, for example `"notebook_params": + * {"name": "john doe", "age": "35"}`. + * The map is passed to the notebook and is accessible through the + * [dbutils.widgets.get](https://docs.databricks.com/dev-tools/databricks-utils.html) + * function. + * + * If not specified upon `run-now`, the triggered run uses the job’s base parameters. + * + * notebook_params cannot be specified in conjunction with jar_params. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + * + * The JSON representation of this field (for example `{"notebook_params":{"name":"john + * doe","age":"35"}}`) cannot exceed 10,000 bytes. + */ + notebook_params?: {[key: string]: string} | string; + /** + * Controls whether the pipeline should perform a full refresh + */ + pipeline_params?: PipelineParamsClass | string; + python_named_params?: {[key: string]: string} | string; + /** + * A list of parameters for jobs with Python tasks, for example `"python_params": ["john + * doe", "35"]`. + * The parameters are passed to Python file as command-line parameters. If specified upon + * `run-now`, it would overwrite + * the parameters specified in job setting. The JSON representation of this field (for + * example `{"python_params":["john doe","35"]}`) + * cannot exceed 10,000 bytes. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + * + * Important + * + * These parameters accept only Latin characters (ASCII character set). Using non-ASCII + * characters returns an error. + * Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis. + */ + python_params?: string[] | string; + /** + * A list of parameters for jobs with spark submit task, for example `"spark_submit_params": + * ["--class", "org.apache.spark.examples.SparkPi"]`. + * The parameters are passed to spark-submit script as command-line parameters. If specified + * upon `run-now`, it would overwrite the + * parameters specified in job setting. The JSON representation of this field (for example + * `{"python_params":["john doe","35"]}`) + * cannot exceed 10,000 bytes. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs + * + * Important + * + * These parameters accept only Latin characters (ASCII character set). Using non-ASCII + * characters returns an error. + * Examples of invalid, non-ASCII characters are Chinese, Japanese kanjis, and emojis. + */ + spark_submit_params?: string[] | string; + /** + * A map from keys to values for jobs with SQL task, for example `"sql_params": {"name": + * "john doe", "age": "35"}`. The SQL alert task does not support custom parameters. + */ + sql_params?: {[key: string]: string} | string; +} + +export interface PipelineParamsClass { + /** + * If true, triggers a full refresh on the delta live table. + */ + full_refresh?: boolean | string; +} + +export interface SparkJarTaskClass { + /** + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + */ + jar_uri?: string; + /** + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + */ + main_class_name?: string; + /** + * Parameters passed to the main method. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + */ + parameters?: string[] | string; +} + +export interface SparkPythonTaskClass { + /** + * Command line parameters passed to the Python file. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + */ + parameters?: string[] | string; + /** + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + */ + python_file: string; + /** + * Optional location type of the Python file. When set to `WORKSPACE` or not specified, the + * file will be retrieved from the local + * Databricks workspace or cloud location (if the `python_file` has a URI format). When set + * to `GIT`, + * the Python file will be retrieved from a Git repository defined in `git_source`. + * + * * `WORKSPACE`: The Python file is located in a Databricks workspace or at a cloud + * filesystem URI. + * * `GIT`: The Python file is located in a remote Git repository. + */ + source?: Source; +} + +export interface SparkSubmitTaskClass { + /** + * Command-line parameters passed to spark submit. + * + * Use [Task parameter variables](https://docs.databricks.com/jobs.html#parameter-variables) + * to set parameters containing information about job runs. + */ + parameters?: string[] | string; +} + +export interface SQLTaskClass { + /** + * If alert, indicates that this job must refresh a SQL alert. + */ + alert?: AlertClass | string; + /** + * If dashboard, indicates that this job must refresh a SQL dashboard. + */ + dashboard?: DashboardClass | string; + /** + * If file, indicates that this job runs a SQL file in a remote Git repository. + */ + file?: BundleSchem1 | string; + /** + * Parameters to be used for each run of this job. The SQL alert task does not support + * custom parameters. + */ + parameters?: {[key: string]: string} | string; + /** + * If query, indicates that this job must execute a SQL query. + */ + query?: QueryClass | string; + /** + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + */ + warehouse_id: string; +} + +export interface AlertClass { + /** + * The canonical identifier of the SQL alert. + */ + alert_id: string; + /** + * If true, the alert notifications are not sent to subscribers. + */ + pause_subscriptions?: boolean | string; + /** + * If specified, alert notifications are sent to subscribers. + */ + subscriptions?: Array | string; +} + +export interface SubscriptionClass { + /** + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + */ + destination_id?: string; + /** + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + */ + user_name?: string; +} + +export interface DashboardClass { + /** + * Subject of the email sent to subscribers of this task. + */ + custom_subject?: string; + /** + * The canonical identifier of the SQL dashboard. + */ + dashboard_id: string; + /** + * If true, the dashboard snapshot is not taken, and emails are not sent to subscribers. + */ + pause_subscriptions?: boolean | string; + /** + * If specified, dashboard snapshots are sent to subscriptions. + */ + subscriptions?: Array | string; +} + +export interface BundleSchem1 { + /** + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + */ + path: string; + /** + * Optional location type of the SQL file. When set to `WORKSPACE`, the SQL file will be + * retrieved + * from the local Databricks workspace. When set to `GIT`, the SQL file will be retrieved + * from a Git repository + * defined in `git_source`. If the value is empty, the task will use `GIT` if `git_source` + * is defined and `WORKSPACE` otherwise. + * + * * `WORKSPACE`: SQL file is located in Databricks workspace. + * * `GIT`: SQL file is located in cloud Git provider. + */ + source?: Source; +} + +export interface QueryClass { + /** + * The canonical identifier of the SQL query. + */ + query_id: string; +} + +export interface WebhookNotificationsClass { + /** + * An optional list of system notification IDs to call when the duration of a run exceeds + * the threshold specified for the `RUN_DURATION_SECONDS` metric in the `health` field. A + * maximum of 3 destinations can be specified for the + * `on_duration_warning_threshold_exceeded` property. + */ + on_duration_warning_threshold_exceeded?: + | Array + | string; + /** + * An optional list of system notification IDs to call when the run fails. A maximum of 3 + * destinations can be specified for the `on_failure` property. + */ + on_failure?: + | Array + | string; + /** + * An optional list of system notification IDs to call when the run starts. A maximum of 3 + * destinations can be specified for the `on_start` property. + */ + on_start?: Array | string; + /** + * An optional list of system notification IDs to call when any streaming backlog thresholds + * are exceeded for any stream. + * Streaming backlog thresholds can be set in the `health` field using the following + * metrics: `STREAMING_BACKLOG_BYTES`, `STREAMING_BACKLOG_RECORDS`, + * `STREAMING_BACKLOG_SECONDS`, or `STREAMING_BACKLOG_FILES`. + * Alerting is based on the 10-minute average of these metrics. If the issue persists, + * notifications are resent every 30 minutes. + * A maximum of 3 destinations can be specified for the `on_streaming_backlog_exceeded` + * property. + */ + on_streaming_backlog_exceeded?: + | Array + | string; + /** + * An optional list of system notification IDs to call when the run completes successfully. + * A maximum of 3 destinations can be specified for the `on_success` property. + */ + on_success?: + | Array + | string; +} + +export interface OnDurationWarningThresholdExceededClass { + id: string; +} + +export interface BundleSchem2 { + /** + * File arrival trigger settings. + */ + file_arrival?: FileArrivalClass | string; + /** + * Whether this trigger is paused or not. + */ + pause_status?: PauseStatus; + /** + * Periodic trigger settings. + */ + periodic?: PeriodicClass | string; + /** + * Old table trigger settings name. Deprecated in favor of `table_update`. + */ + table?: TableUpdateClass | string; + table_update?: TableUpdateClass | string; +} + +export interface FileArrivalClass { + /** + * If set, the trigger starts a run only after the specified amount of time passed since + * the last time the trigger fired. The minimum allowed value is 60 seconds + */ + min_time_between_triggers_seconds?: number | string; + /** + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + */ + url: string; + /** + * If set, the trigger starts a run only after no file activity has occurred for the + * specified amount of time. + * This makes it possible to wait for a batch of incoming files to arrive before triggering + * a run. The + * minimum allowed value is 60 seconds. + */ + wait_after_last_change_seconds?: number | string; +} + +export interface PeriodicClass { + /** + * The interval at which the trigger should run. + */ + interval: number | string; + /** + * The unit of time for the interval. + */ + unit: Unit; +} + +/** + * The unit of time for the interval. + */ +export enum Unit { + Days = "DAYS", + Hours = "HOURS", + Weeks = "WEEKS", +} + +export interface TableUpdateClass { + /** + * The table(s) condition based on which to trigger a job run. + */ + condition?: Condition; + /** + * If set, the trigger starts a run only after the specified amount of time has passed since + * the last time the trigger fired. The minimum allowed value is 60 seconds. + */ + min_time_between_triggers_seconds?: number | string; + /** + * A list of Delta tables to monitor for changes. The table name must be in the format + * `catalog_name.schema_name.table_name`. + */ + table_names?: string[] | string; + /** + * If set, the trigger starts a run only after no table updates have occurred for the + * specified time + * and can be used to wait for a series of table updates before triggering a run. The + * minimum allowed value is 60 seconds. + */ + wait_after_last_change_seconds?: number | string; +} + +/** + * The table(s) condition based on which to trigger a job run. + */ +export enum Condition { + AllUpdated = "ALL_UPDATED", + AnyUpdated = "ANY_UPDATED", +} + +export interface ModelServingEndpointClass { + /** + * The AI Gateway configuration for the serving endpoint. NOTE: only external model + * endpoints are supported as of now. + */ + ai_gateway?: AIGatewayClass | string; + /** + * The core config of the serving endpoint. + */ + config: ConfigClass | string; + /** + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + */ + name: string; + permissions?: Array | string; + /** + * Rate limits to be applied to the serving endpoint. NOTE: this field is deprecated, please + * use AI Gateway to manage rate limits. + */ + rate_limits?: Array | string; + /** + * Enable route optimization for the serving endpoint. + */ + route_optimized?: boolean | string; + /** + * Tags to be attached to the serving endpoint and automatically propagated to billing logs. + */ + tags?: Array | string; +} + +export interface AIGatewayClass { + /** + * Configuration for AI Guardrails to prevent unwanted data and unsafe data in requests and + * responses. + */ + guardrails?: GuardrailsClass | string; + /** + * Configuration for payload logging using inference tables. Use these tables to monitor and + * audit data being sent to and received from model APIs and to improve model quality. + */ + inference_table_config?: InferenceTableConfigClass | string; + /** + * Configuration for rate limits which can be set to limit endpoint traffic. + */ + rate_limits?: Array | string; + /** + * Configuration to enable usage tracking using system tables. These tables allow you to + * monitor operational usage on endpoints and their associated costs. + */ + usage_tracking_config?: UsageTrackingConfigClass | string; +} + +export interface GuardrailsClass { + /** + * Configuration for input guardrail filters. + */ + input?: InputClass | string; + /** + * Configuration for output guardrail filters. + */ + output?: InputClass | string; +} + +export interface InputClass { + /** + * List of invalid keywords. AI guardrail uses keyword or string matching to decide if the + * keyword exists in the request or response content. + */ + invalid_keywords?: string[] | string; + /** + * Configuration for guardrail PII filter. + */ + pii?: PiiClass | string; + /** + * Indicates whether the safety filter is enabled. + */ + safety?: boolean | string; + /** + * The list of allowed topics. Given a chat request, this guardrail flags the request if its + * topic is not in the allowed topics. + */ + valid_topics?: string[] | string; +} + +export interface PiiClass { + /** + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + */ + behavior: Behavior; +} + +/** + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Behavior { + Block = "BLOCK", + None = "NONE", +} + +export interface InferenceTableConfigClass { + /** + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog name. + */ + catalog_name?: string; + /** + * Indicates whether the inference table is enabled. + */ + enabled?: boolean | string; + /** + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + */ + schema_name?: string; + /** + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + */ + table_name_prefix?: string; +} + +export interface BundleSchem3 { + /** + * Used to specify how many calls are allowed for a key within the renewal_period. + */ + calls: number | string; + /** + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + */ + key?: Key; + /** + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + */ + renewal_period: RenewalPeriod; +} + +/** + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Key { + Endpoint = "endpoint", + User = "user", +} + +/** + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum RenewalPeriod { + Minute = "minute", +} + +export interface UsageTrackingConfigClass { + /** + * Whether to enable usage tracking. + */ + enabled?: boolean | string; +} + +export interface ConfigClass { + /** + * Configuration for Inference Tables which automatically logs requests and responses to + * Unity Catalog. + */ + auto_capture_config?: AutoCaptureConfigClass | string; + /** + * A list of served entities for the endpoint to serve. A serving endpoint can have up to 15 + * served entities. + */ + served_entities?: Array | string; + /** + * (Deprecated, use served_entities instead) A list of served models for the endpoint to + * serve. A serving endpoint can have up to 15 served models. + */ + served_models?: Array | string; + /** + * The traffic config defining how invocations to the serving endpoint should be routed. + */ + traffic_config?: TrafficConfigClass | string; +} + +export interface AutoCaptureConfigClass { + /** + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + */ + catalog_name?: string; + /** + * Indicates whether the inference table is enabled. + */ + enabled?: boolean | string; + /** + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + */ + schema_name?: string; + /** + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + */ + table_name_prefix?: string; +} + +export interface ServedEntityClass { + /** + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + */ + entity_name?: string; + /** + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + */ + entity_version?: string; + /** + * An object containing a set of optional, user-specified environment variable key-value + * pairs used for serving this entity. + * Note: this is an experimental feature and subject to change. + * Example entity environment variables that refer to Databricks secrets: + * `{"OPENAI_API_KEY": "{{secrets/my_scope/my_key}}", "DATABRICKS_TOKEN": + * "{{secrets/my_scope2/my_key2}}"}` + */ + environment_vars?: {[key: string]: string} | string; + /** + * The external model to be served. NOTE: Only one of external_model and (entity_name, + * entity_version, workload_size, workload_type, and scale_to_zero_enabled) + * can be specified with the latter set being used for custom model serving for a Databricks + * registered model. For an existing endpoint with external_model, + * it cannot be updated to an endpoint without external_model. If the endpoint is created + * without external_model, users cannot update it to add external_model later. + * The task type of all external models within an endpoint must be the same. + */ + external_model?: ExternalModelClass | string; + /** + * ARN of the instance profile that the served entity uses to access AWS resources. + */ + instance_profile_arn?: string; + /** + * The maximum tokens per second that the endpoint can scale up to. + */ + max_provisioned_throughput?: number | string; + /** + * The minimum tokens per second that the endpoint can scale down to. + */ + min_provisioned_throughput?: number | string; + /** + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + */ + name?: string; + /** + * Whether the compute resources for the served entity should scale down to zero. + */ + scale_to_zero_enabled?: boolean | string; + /** + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + */ + workload_size?: string; + /** + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + */ + workload_type?: string; +} + +export interface ExternalModelClass { + /** + * AI21Labs Config. Only required if the provider is 'ai21labs'. + */ + ai21labs_config?: Ai21LabsConfigClass | string; + /** + * Amazon Bedrock Config. Only required if the provider is 'amazon-bedrock'. + */ + amazon_bedrock_config?: AmazonBedrockConfigClass | string; + /** + * Anthropic Config. Only required if the provider is 'anthropic'. + */ + anthropic_config?: AnthropicConfigClass | string; + /** + * Cohere Config. Only required if the provider is 'cohere'. + */ + cohere_config?: CohereConfigClass | string; + /** + * Databricks Model Serving Config. Only required if the provider is + * 'databricks-model-serving'. + */ + databricks_model_serving_config?: + | DatabricksModelServingConfigClass + | string; + /** + * Google Cloud Vertex AI Config. Only required if the provider is 'google-cloud-vertex-ai'. + */ + google_cloud_vertex_ai_config?: GoogleCloudVertexAIConfigClass | string; + /** + * The name of the external model. + */ + name: string; + /** + * OpenAI Config. Only required if the provider is 'openai'. + */ + openai_config?: OpenaiConfigClass | string; + /** + * PaLM Config. Only required if the provider is 'palm'. + */ + palm_config?: PalmConfigClass | string; + /** + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + */ + provider: Provider; + /** + * The task type of the external model. + */ + task: string; +} + +export interface Ai21LabsConfigClass { + ai21labs_api_key?: string; + ai21labs_api_key_plaintext?: string; +} + +export interface AmazonBedrockConfigClass { + /** + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + */ + aws_access_key_id?: string; + /** + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + */ + aws_access_key_id_plaintext?: string; + /** + * The AWS region to use. Bedrock has to be enabled there. + */ + aws_region: string; + /** + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + */ + aws_secret_access_key?: string; + /** + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or `aws_secret_access_key_plaintext`. + */ + aws_secret_access_key_plaintext?: string; + /** + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + */ + bedrock_provider: BedrockProvider; +} + +/** + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum BedrockProvider { + Ai21Labs = "ai21labs", + Amazon = "amazon", + Anthropic = "anthropic", + Cohere = "cohere", +} + +export interface AnthropicConfigClass { + /** + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + */ + anthropic_api_key?: string; + /** + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + */ + anthropic_api_key_plaintext?: string; +} + +export interface CohereConfigClass { + /** + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + */ + cohere_api_base?: string; + /** + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + */ + cohere_api_key?: string; + /** + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + */ + cohere_api_key_plaintext?: string; +} + +export interface DatabricksModelServingConfigClass { + /** + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + */ + databricks_api_token?: string; + /** + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + */ + databricks_api_token_plaintext?: string; + /** + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + */ + databricks_workspace_url: string; +} + +export interface GoogleCloudVertexAIConfigClass { + private_key?: string; + private_key_plaintext?: string; + project_id?: string; + region?: string; +} + +export interface OpenaiConfigClass { + microsoft_entra_client_id?: string; + microsoft_entra_client_secret?: string; + microsoft_entra_client_secret_plaintext?: string; + microsoft_entra_tenant_id?: string; + openai_api_base?: string; + openai_api_key?: string; + openai_api_key_plaintext?: string; + openai_api_type?: string; + openai_api_version?: string; + openai_deployment_name?: string; + openai_organization?: string; +} + +export interface PalmConfigClass { + palm_api_key?: string; + palm_api_key_plaintext?: string; +} + +/** + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Provider { + Ai21Labs = "ai21labs", + AmazonBedrock = "amazon-bedrock", + Anthropic = "anthropic", + Cohere = "cohere", + DatabricksModelServing = "databricks-model-serving", + GoogleCloudVertexAI = "google-cloud-vertex-ai", + Openai = "openai", + Palm = "palm", +} + +export interface ServedModelClass { + /** + * An object containing a set of optional, user-specified environment variable key-value + * pairs used for serving this model. + * Note: this is an experimental feature and subject to change. + * Example model environment variables that refer to Databricks secrets: `{"OPENAI_API_KEY": + * "{{secrets/my_scope/my_key}}", "DATABRICKS_TOKEN": "{{secrets/my_scope2/my_key2}}"}` + */ + environment_vars?: {[key: string]: string} | string; + /** + * ARN of the instance profile that the served model will use to access AWS resources. + */ + instance_profile_arn?: string; + /** + * The maximum tokens per second that the endpoint can scale up to. + */ + max_provisioned_throughput?: number | string; + /** + * The minimum tokens per second that the endpoint can scale down to. + */ + min_provisioned_throughput?: number | string; + /** + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + */ + model_name: string; + /** + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + */ + model_version: string; + /** + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + */ + name?: string; + /** + * Whether the compute resources for the served model should scale down to zero. + */ + scale_to_zero_enabled: boolean | string; + /** + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + */ + workload_size?: WorkloadSize; + /** + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + */ + workload_type?: WorkloadTypeEnum; +} + +/** + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum WorkloadSize { + Large = "Large", + Medium = "Medium", + Small = "Small", +} + +/** + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum WorkloadTypeEnum { + CPU = "CPU", + GPULarge = "GPU_LARGE", + GPUMedium = "GPU_MEDIUM", + GPUSmall = "GPU_SMALL", + MultigpuMedium = "MULTIGPU_MEDIUM", +} + +export interface TrafficConfigClass { + /** + * The list of routes that define traffic to each served entity. + */ + routes?: Array | string; +} + +export interface RouteClass { + /** + * The name of the served model this route configures traffic for. + */ + served_model_name: string; + /** + * The percentage of endpoint traffic to send to this route. It must be an integer between 0 + * and 100 inclusive. + */ + traffic_percentage: number | string; +} + +export interface BundleSchem4 { + /** + * Used to specify how many calls are allowed for a key within the renewal_period. + */ + calls: number | string; + /** + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + */ + key?: Key; + /** + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + */ + renewal_period: RenewalPeriod; +} + +export interface BundleSchem5 { + /** + * Key field for a serving endpoint tag. + */ + key: string; + /** + * Optional value field for a serving endpoint tag. + */ + value?: string; +} + +export interface ModelClass { + /** + * Timestamp recorded when this `registered_model` was created. + */ + creation_timestamp?: number | string; + /** + * Description of this `registered_model`. + */ + description?: string; + /** + * Timestamp recorded when metadata for this `registered_model` was last updated. + */ + last_updated_timestamp?: number | string; + /** + * Collection of latest model versions for each stage. + * Only contains models with current `READY` status. + */ + latest_versions?: Array | string; + /** + * Unique name for the model. + */ + name?: string; + permissions?: Array | string; + /** + * Tags: Additional metadata key-value pairs for this `registered_model`. + */ + tags?: Array | string; + /** + * User that created this `registered_model` + */ + user_id?: string; +} + +export interface LatestVersionClass { + /** + * Timestamp recorded when this `model_version` was created. + */ + creation_timestamp?: number | string; + /** + * Current stage for this `model_version`. + */ + current_stage?: string; + /** + * Description of this `model_version`. + */ + description?: string; + /** + * Timestamp recorded when metadata for this `model_version` was last updated. + */ + last_updated_timestamp?: number | string; + /** + * Unique name of the model + */ + name?: string; + /** + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + */ + run_id?: string; + /** + * Run Link: Direct link to the run that generated this version + */ + run_link?: string; + /** + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + */ + source?: string; + /** + * Current status of `model_version` + */ + status?: Status; + /** + * Details on current `status`, if it is pending or failed. + */ + status_message?: string; + /** + * Tags: Additional metadata key-value pairs for this `model_version`. + */ + tags?: Array | string; + /** + * User that created this `model_version`. + */ + user_id?: string; + /** + * Model's version number. + */ + version?: string; +} + +/** + * Current status of `model_version` + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Status { + FailedRegistration = "FAILED_REGISTRATION", + PendingRegistration = "PENDING_REGISTRATION", + Ready = "READY", +} + +export interface BundleSchem6 { + /** + * The tag key. + */ + key?: string; + /** + * The tag value. + */ + value?: string; +} + +export interface BundleSchem7 { + /** + * The tag key. + */ + key?: string; + /** + * The tag value. + */ + value?: string; +} + +export interface PipelineClass { + /** + * Budget policy of this pipeline. + */ + budget_policy_id?: string; + /** + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + */ + catalog?: string; + /** + * DLT Release Channel that specifies which version to use. + */ + channel?: string; + /** + * Cluster settings for this pipeline deployment. + */ + clusters?: Array | string; + /** + * String-String configuration for this pipeline execution. + */ + configuration?: {[key: string]: string} | string; + /** + * Whether the pipeline is continuous or triggered. This replaces `trigger`. + */ + continuous?: boolean | string; + /** + * Deployment type of this pipeline. + */ + deployment?: BundleSchem10 | string; + /** + * Whether the pipeline is in Development mode. Defaults to false. + */ + development?: boolean | string; + /** + * Pipeline product edition. + */ + edition?: string; + /** + * Filters on which Pipeline packages to include in the deployed graph. + */ + filters?: FiltersClass | string; + /** + * The definition of a gateway pipeline to support CDC. + */ + gateway_definition?: GatewayDefinitionClass | string; + /** + * Unique identifier for this pipeline. + */ + id?: string; + /** + * The configuration for a managed ingestion pipeline. These settings cannot be used with + * the 'libraries', 'target' or 'catalog' settings. + */ + ingestion_definition?: IngestionDefinitionClass | string; + /** + * Libraries or code needed by this deployment. + */ + libraries?: Array | string; + /** + * Friendly identifier for this pipeline. + */ + name?: string; + /** + * List of notification settings for this pipeline. + */ + notifications?: Array | string; + permissions?: Array | string; + /** + * Whether Photon is enabled for this pipeline. + */ + photon?: boolean | string; + /** + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + */ + schema?: string; + /** + * Whether serverless compute is enabled for this pipeline. + */ + serverless?: boolean | string; + /** + * DBFS root directory for storing checkpoints and tables. + */ + storage?: string; + /** + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + */ + target?: string; + /** + * Which pipeline trigger to use. Deprecated: Use `continuous` instead. + */ + trigger?: BundleSchem15 | string; +} + +export interface BundleSchem8 { + /** + * Note: This field won't be persisted. Only API users will check this field. + */ + apply_policy_default_values?: boolean | string; + /** + * Parameters needed in order to automatically scale clusters up and down based on load. + * Note: autoscaling works best with DB runtime versions 3.0 or later. + */ + autoscale?: BundleSchem9 | string; + /** + * Attributes related to clusters running on Amazon Web Services. + * If not specified at cluster creation, a set of default values will be used. + */ + aws_attributes?: AwsAttributesClass | string; + /** + * Attributes related to clusters running on Microsoft Azure. + * If not specified at cluster creation, a set of default values will be used. + */ + azure_attributes?: AzureAttributesClass | string; + /** + * The configuration for delivering spark logs to a long-term storage destination. + * Only dbfs destinations are supported. Only one destination can be specified + * for one cluster. If the conf is given, the logs will be delivered to the destination + * every + * `5 mins`. The destination of driver logs is `$destination/$clusterId/driver`, while + * the destination of executor logs is `$destination/$clusterId/executor`. + */ + cluster_log_conf?: ClusterLogConfClass | string; + /** + * Additional tags for cluster resources. Databricks will tag all cluster resources (e.g., + * AWS + * instances and EBS volumes) with these tags in addition to `default_tags`. Notes: + * + * - Currently, Databricks allows at most 45 custom tags + * + * - Clusters can only reuse cloud resources if the resources' tags are a subset of the + * cluster tags + */ + custom_tags?: {[key: string]: string} | string; + /** + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + */ + driver_instance_pool_id?: string; + /** + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + */ + driver_node_type_id?: string; + /** + * Whether to enable local disk encryption for the cluster. + */ + enable_local_disk_encryption?: boolean | string; + /** + * Attributes related to clusters running on Google Cloud Platform. + * If not specified at cluster creation, a set of default values will be used. + */ + gcp_attributes?: GcpAttributesClass | string; + /** + * The configuration for storing init scripts. Any number of destinations can be specified. + * The scripts are executed sequentially in the order provided. If `cluster_log_conf` is + * specified, init script logs are sent to `//init_scripts`. + */ + init_scripts?: Array | string; + /** + * The optional ID of the instance pool to which the cluster belongs. + */ + instance_pool_id?: string; + /** + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + */ + label?: string; + /** + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + */ + node_type_id?: string; + /** + * Number of worker nodes that this cluster should have. A cluster has one Spark Driver + * and `num_workers` Executors for a total of `num_workers` + 1 Spark nodes. + * + * Note: When reading the properties of a cluster, this field reflects the desired number + * of workers rather than the actual current number of workers. For instance, if a cluster + * is resized from 5 to 10 workers, this field will immediately be updated to reflect + * the target size of 10 workers, whereas the workers listed in `spark_info` will gradually + * increase from 5 to 10 as the new nodes are provisioned. + */ + num_workers?: number | string; + /** + * The ID of the cluster policy used to create the cluster if applicable. + */ + policy_id?: string; + /** + * An object containing a set of optional, user-specified Spark configuration key-value + * pairs. + * See :method:clusters/create for more details. + */ + spark_conf?: {[key: string]: string} | string; + /** + * An object containing a set of optional, user-specified environment variable key-value + * pairs. + * Please note that key-value pair of the form (X,Y) will be exported as is (i.e., + * `export X='Y'`) while launching the driver and workers. + * + * In order to specify an additional set of `SPARK_DAEMON_JAVA_OPTS`, we recommend appending + * them to `$SPARK_DAEMON_JAVA_OPTS` as shown in the example below. This ensures that all + * default databricks managed environmental variables are included as well. + * + * Example Spark environment variables: + * `{"SPARK_WORKER_MEMORY": "28000m", "SPARK_LOCAL_DIRS": "/local_disk0"}` or + * `{"SPARK_DAEMON_JAVA_OPTS": "$SPARK_DAEMON_JAVA_OPTS + * -Dspark.shuffle.service.enabled=true"}` + */ + spark_env_vars?: {[key: string]: string} | string; + /** + * SSH public key contents that will be added to each Spark node in this cluster. The + * corresponding private keys can be used to login with the user name `ubuntu` on port + * `2200`. + * Up to 10 keys can be specified. + */ + ssh_public_keys?: string[] | string; +} + +export interface BundleSchem9 { + /** + * The maximum number of workers to which the cluster can scale up when overloaded. + * `max_workers` must be strictly greater than `min_workers`. + */ + max_workers: number | string; + /** + * The minimum number of workers the cluster can scale down to when underutilized. + * It is also the initial number of workers the cluster will have after creation. + */ + min_workers: number | string; + /** + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + */ + mode?: Mode; +} + +/** + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Mode { + Enhanced = "ENHANCED", + Legacy = "LEGACY", +} + +export interface BundleSchem10 { + /** + * The deployment method that manages the pipeline. + */ + kind?: Kind; + /** + * The path to the file containing metadata about the deployment. + */ + metadata_file_path?: string; +} + +/** + * The deployment method that manages the pipeline. + * + * The deployment method that manages the pipeline: + * - BUNDLE: The pipeline is managed by a Databricks Asset Bundle. + */ +export enum Kind { + Bundle = "BUNDLE", +} + +export interface FiltersClass { + /** + * Paths to exclude. + */ + exclude?: string[] | string; + /** + * Paths to include. + */ + include?: string[] | string; +} + +export interface GatewayDefinitionClass { + /** + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + */ + connection_id?: string; + /** + * Required, Immutable. The name of the catalog for the gateway pipeline's storage location. + */ + gateway_storage_catalog?: string; + /** + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + */ + gateway_storage_name?: string; + /** + * Required, Immutable. The name of the schema for the gateway pipelines's storage location. + */ + gateway_storage_schema?: string; +} + +export interface IngestionDefinitionClass { + /** + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + */ + connection_name?: string; + /** + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + */ + ingestion_gateway_id?: string; + /** + * Required. Settings specifying tables to replicate and the destination for the replicated + * tables. + */ + objects?: Array | string; + /** + * Configuration settings to control the ingestion of tables. These settings are applied to + * all tables in the pipeline. + */ + table_configuration?: TableConfigurationClass | string; +} + +export interface ObjectClass { + /** + * Select tables from a specific source schema. + */ + schema?: BundleSchem11 | string; + /** + * Select tables from a specific source table. + */ + table?: BundleSchem12 | string; +} + +export interface BundleSchem11 { + /** + * Required. Destination catalog to store tables. + */ + destination_catalog?: string; + /** + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + */ + destination_schema?: string; + /** + * The source catalog name. Might be optional depending on the type of source. + */ + source_catalog?: string; + /** + * Required. Schema name in the source database. + */ + source_schema?: string; + /** + * Configuration settings to control the ingestion of tables. These settings are applied to + * all tables in this schema and override the table_configuration defined in the + * IngestionPipelineDefinition object. + */ + table_configuration?: TableConfigurationClass | string; +} + +export interface TableConfigurationClass { + /** + * The primary key of the table used to apply changes. + */ + primary_keys?: string[] | string; + /** + * If true, formula fields defined in the table are included in the ingestion. This setting + * is only valid for the Salesforce connector + */ + salesforce_include_formula_fields?: boolean | string; + /** + * The SCD type to use to ingest the table. + */ + scd_type?: ScdType; +} + +/** + * The SCD type to use to ingest the table. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum ScdType { + ScdType1 = "SCD_TYPE_1", + ScdType2 = "SCD_TYPE_2", +} + +export interface BundleSchem12 { + /** + * Required. Destination catalog to store table. + */ + destination_catalog?: string; + /** + * Required. Destination schema to store table. + */ + destination_schema?: string; + /** + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + */ + destination_table?: string; + /** + * Source catalog name. Might be optional depending on the type of source. + */ + source_catalog?: string; + /** + * Schema name in the source database. Might be optional depending on the type of source. + */ + source_schema?: string; + /** + * Required. Table name in the source database. + */ + source_table?: string; + /** + * Configuration settings to control the ingestion of tables. These settings override the + * table_configuration defined in the IngestionPipelineDefinition object and the SchemaSpec. + */ + table_configuration?: TableConfigurationClass | string; +} + +export interface BundleSchem13 { + /** + * The path to a file that defines a pipeline and is stored in the Databricks Repos. + */ + file?: BundleSchem14 | string; + /** + * URI of the jar to be installed. Currently only DBFS is supported. + */ + jar?: string; + /** + * Specification of a maven library to be installed. + */ + maven?: MavenClass | string; + /** + * The path to a notebook that defines a pipeline and is stored in the Databricks workspace. + */ + notebook?: NotebookClass | string; + /** + * URI of the whl to be installed. + */ + whl?: string; +} + +export interface BundleSchem14 { + /** + * The absolute path of the file. + */ + path?: string; +} + +export interface NotebookClass { + /** + * The absolute path of the notebook. + */ + path?: string; +} + +export interface NotificationClass { + /** + * A list of alerts that trigger the sending of notifications to the configured + * destinations. The supported alerts are: + * + * * `on-update-success`: A pipeline update completes successfully. + * * `on-update-failure`: Each time a pipeline update fails. + * * `on-update-fatal-failure`: A pipeline update fails with a non-retryable (fatal) error. + * * `on-flow-failure`: A single data flow fails. + */ + alerts?: string[] | string; + /** + * A list of email addresses notified when a configured alert is triggered. + */ + email_recipients?: string[] | string; +} + +export interface BundleSchem15 { + cron?: CronClass | string; + manual?: ManualClass | string; +} + +export interface CronClass { + quartz_cron_schedule?: string; + timezone_id?: string; +} + +export interface ManualClass {} + +export interface QualityMonitorClass { + /** + * The directory to store monitoring assets (e.g. dashboard, metric tables). + */ + assets_dir: string; + /** + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + */ + baseline_table_name?: string; + /** + * Custom metrics to compute on the monitored table. These can be aggregate metrics, derived + * metrics (from already computed aggregate metrics), or drift metrics (comparing metrics + * across time + * windows). + */ + custom_metrics?: Array | string; + /** + * The data classification config for the monitor. + */ + data_classification_config?: DataClassificationConfigClass | string; + /** + * Configuration for monitoring inference logs. + */ + inference_log?: InferenceLogClass | string; + /** + * The notification settings for the monitor. + */ + notifications?: NotificationsClass | string; + /** + * Schema where output metric tables are created. + */ + output_schema_name: string; + /** + * The schedule for automatically updating and refreshing metric tables. + */ + schedule?: BundleSchem16 | string; + /** + * Whether to skip creating a default dashboard summarizing data quality metrics. + */ + skip_builtin_dashboard?: boolean | string; + /** + * List of column expressions to slice data with for targeted analysis. The data is grouped + * by + * each expression independently, resulting in a separate slice for each predicate and its + * complements. For high-cardinality columns, only the top 100 unique values by frequency + * will + * generate slices. + */ + slicing_exprs?: string[] | string; + /** + * Configuration for monitoring snapshot tables. + */ + snapshot?: SnapshotClass | string; + /** + * Configuration for monitoring time series tables. + */ + time_series?: TimeSeriesClass | string; + /** + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + */ + warehouse_id?: string; +} + +export interface CustomMetricClass { + /** + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + */ + definition: string; + /** + * A list of column names in the input table the metric should be computed for. + * Can use ``":table"`` to indicate that the metric needs information from multiple columns. + */ + input_columns: string[] | string; + /** + * Name of the metric in the output tables. + */ + name: string; + /** + * The output type of the custom metric. + */ + output_data_type: string; + /** + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + */ + type: Type; +} + +/** + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum Type { + CustomMetricTypeAggregate = "CUSTOM_METRIC_TYPE_AGGREGATE", + CustomMetricTypeDerived = "CUSTOM_METRIC_TYPE_DERIVED", + CustomMetricTypeDrift = "CUSTOM_METRIC_TYPE_DRIFT", +} + +export interface DataClassificationConfigClass { + /** + * Whether data classification is enabled. + */ + enabled?: boolean | string; +} + +export interface InferenceLogClass { + /** + * Granularities for aggregating data into time windows based on their timestamp. Currently + * the following static + * granularities are supported: + * {``"5 minutes"``, ``"30 minutes"``, ``"1 hour"``, ``"1 day"``, ``" week(s)"``, ``"1 + * month"``, ``"1 year"``}. + */ + granularities: string[] | string; + /** + * Optional column that contains the ground truth for the prediction. + */ + label_col?: string; + /** + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + */ + model_id_col: string; + /** + * Column that contains the output/prediction from the model. + */ + prediction_col: string; + /** + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + */ + prediction_proba_col?: string; + /** + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + */ + problem_type: ProblemType; + /** + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + */ + timestamp_col: string; +} + +/** + * Problem type the model aims to solve. Determines the type of model-quality metrics that + * will be computed. + * + * Nodes for this cluster will only be placed on AWS instances with this instance profile. + * If + * ommitted, nodes will be placed on instances without an IAM instance profile. The instance + * profile must have previously been added to the Databricks environment by an account + * administrator. + * + * This feature may only be available to certain customer plans. + * + * If this field is ommitted, we will pull in the default from the conf if it exists. + * + * Identifier for the availability zone/datacenter in which the cluster resides. + * This string will be of a form like "us-west-2a". The provided availability + * zone must be in the same region as the Databricks deployment. For example, "us-west-2a" + * is not a valid zone id if the Databricks deployment resides in the "us-east-1" region. + * This is an optional field at cluster creation, and if not specified, a default zone will + * be used. + * If the zone specified is "auto", will try to place cluster in a zone with high + * availability, + * and will retry placement in a different AZ if there is not enough capacity. + * The list of available zones as well as the default value can be found by using the + * `List Zones` method. + * + * + * + * dbfs destination, e.g. `dbfs:/my/path` + * + * (Optional) Set canned access control list for the logs, e.g. `bucket-owner-full-control`. + * If `canned_cal` is set, please make sure the cluster iam role has `s3:PutObjectAcl` + * permission on + * the destination bucket and prefix. The full list of possible canned acl can be found at + * http://docs.aws.amazon.com/AmazonS3/latest/dev/acl-overview.html#canned-acl. + * Please also note that by default only the object owner gets full controls. If you are + * using cross account + * role for writing data, you may want to set `bucket-owner-full-control` to make bucket + * owner able to + * read the logs. + * + * S3 destination, e.g. `s3://my-bucket/some-prefix` Note that logs will be delivered using + * cluster iam role, please make sure you set cluster iam role and the role has write access + * to the + * destination. Please also note that you cannot use AWS keys to deliver logs. + * + * (Optional) The encryption type, it could be `sse-s3` or `sse-kms`. It will be used only + * when + * encryption is enabled and the default type is `sse-s3`. + * + * S3 endpoint, e.g. `https://s3-us-west-2.amazonaws.com`. Either region or endpoint needs + * to be set. + * If both are set, endpoint will be used. + * + * (Optional) Kms key which will be used if encryption is enabled and encryption type is set + * to `sse-kms`. + * + * S3 region, e.g. `us-west-2`. Either region or endpoint needs to be set. If both are set, + * endpoint will be used. + * + * Cluster name requested by the user. This doesn't have to be unique. + * If not specified at creation, the cluster name will be an empty string. + * + * + * Password of the user + * + * Name of the user + * + * URL of the docker image. + * + * The optional ID of the instance pool for the driver of the cluster belongs. + * The pool cluster uses the instance pool with id (instance_pool_id) if the driver pool is + * not + * assigned. + * + * The node type of the Spark driver. Note that this field is optional; + * if unset, the driver node type will be set as the same value + * as `node_type_id` defined above. + * + * + * If provided, the cluster will impersonate the google service account when accessing + * gcloud services (like GCS). The google service account + * must have previously been added to the Databricks environment by an account + * administrator. + * + * Identifier for the availability zone in which the cluster resides. + * This can be one of the following: + * - "HA" => High availability, spread nodes across availability zones for a Databricks + * deployment region [default] + * - "AUTO" => Databricks picks an availability zone to schedule the cluster on. + * - A GCP availability zone => Pick One of the available zones for (machine type + region) + * from https://cloud.google.com/compute/docs/regions-zones. + * + * abfss destination, e.g. + * `abfss://@.dfs.core.windows.net/`. + * + * local file destination, e.g. `file:/my/local/file.sh` + * + * GCS destination/URI, e.g. `gs://my-bucket/some-prefix` + * + * Unity Catalog Volumes file destination, e.g. `/Volumes/my-init.sh` + * + * workspace files destination, e.g. `/Users/user1@databricks.com/my-init.sh` + * + * The optional ID of the instance pool to which the cluster belongs. + * + * This field encodes, through a single value, the resources available to each of + * the Spark nodes in this cluster. For example, the Spark nodes can be provisioned + * and optimized for memory or compute intensive workloads. A list of available node + * types can be retrieved by using the :method:clusters/listNodeTypes API call. + * + * + * The ID of the cluster policy used to create the cluster if applicable. + * + * Single user name if data_security_mode is `SINGLE_USER` + * + * The Spark version of the cluster, e.g. `3.3.x-scala2.11`. + * A list of available Spark versions can be retrieved by using + * the :method:clusters/sparkVersions API call. + * + * + * Location where artifacts for the experiment are stored. + * + * Unique identifier for the experiment. + * + * Current life cycle stage of the experiment: "active" or "deleted". + * Deleted experiments are not returned by APIs. + * + * Human readable name that identifies the experiment. + * + * The tag key. + * + * The tag value. + * + * An optional description for the job. The maximum length is 27700 characters in UTF-8 + * encoding. + * + * The key of an environment. It has to be unique within a job. + * + * Client version used by the environment + * The client is the user-facing environment of the runtime. + * Each client comes with a specific set of pre-installed libraries. + * The version is a string, consisting of the major client version. + * + * Name of the branch to be checked out and used by this job. This field cannot be specified + * in conjunction with git_tag or git_commit. + * + * Commit to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_tag. + * + * Name of the tag to be checked out and used by this job. This field cannot be specified in + * conjunction with git_branch or git_commit. + * + * URL of the repository to be cloned by this job. + * + * A unique name for the job cluster. This field is required and must be unique within the + * job. + * `JobTaskSettings` may refer to this field to determine which cluster to launch for the + * task execution. + * + * An optional name for the job. The maximum length is 4096 bytes in UTF-8 encoding. + * + * Default value of the parameter. + * + * The name of the defined parameter. May only contain alphanumeric characters, `_`, `-`, + * and `.` + * + * Application ID of an active service principal. Setting this field requires the + * `servicePrincipal/user` role. + * + * The email of an active workspace user. Non-admin users can only set this field to their + * own email. + * + * A Cron expression using Quartz syntax that describes the schedule for a job. See [Cron + * Trigger](http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html) + * for details. This field is required. + * + * A Java timezone ID. The schedule for a job is resolved with respect to this timezone. See + * [Java TimeZone](https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html) for + * details. This field is required. + * + * The left operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * The right operand of the condition task. Can be either a string value or a job state or + * parameter reference. + * + * Optional name of the catalog to use. The value is the top level in the 3-level namespace + * of Unity Catalog (catalog / schema / relation). The catalog value can only be specified + * if a warehouse_id is specified. Requires dbt-databricks >= 1.1.1. + * + * Optional (relative) path to the profiles directory. Can only be specified if no + * warehouse_id is specified. If no warehouse_id is specified and this folder is unset, the + * root directory is used. + * + * Path to the project directory. Optional for Git sourced tasks, in which + * case if no value is provided, the root of the Git repository is used. + * + * Optional schema to write to. This parameter is only used when a warehouse_id is also + * provided. If not provided, the `default` schema is used. + * + * ID of the SQL warehouse to connect to. If provided, we automatically generate and provide + * the profile and connection details to dbt. It can be overridden on a per-command basis by + * using the `--profiles-dir` command line argument. + * + * Can only be specified on condition task dependencies. The outcome of the dependent task + * that must be met for this task to run. + * + * The name of the task this task depends on. + * + * An optional description for this task. + * + * The key that references an environment spec in a job. This field is required for Python + * script, Python wheel and dbt tasks when using serverless compute. + * + * If existing_cluster_id, the ID of an existing cluster that is used for all runs. + * When running jobs or tasks on an existing cluster, you may need to manually restart + * the cluster if it stops responding. We suggest running jobs and tasks on new clusters for + * greater reliability + * + * Array for task to iterate on. This can be a JSON string or a reference to + * an array parameter. + * + * If job_cluster_key, this task is executed reusing the cluster specified in + * `job.settings.job_clusters`. + * + * The name of the CRAN package to install. + * + * The repository where the package can be found. If not specified, the default CRAN repo is + * used. + * + * Deprecated. URI of the egg library to install. Installing Python egg files is deprecated + * and is not supported in Databricks Runtime 14.0 and above. + * + * URI of the JAR library to install. Supported URIs include Workspace paths, Unity Catalog + * Volumes paths, and S3 URIs. + * For example: `{ "jar": "/Workspace/path/to/library.jar" }`, `{ "jar" : + * "/Volumes/path/to/library.jar" }` or + * `{ "jar": "s3://my-bucket/library.jar" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * Gradle-style maven coordinates. For example: "org.jsoup:jsoup:1.7.2". + * + * Maven repo to install the Maven package from. If omitted, both Maven Central Repository + * and Spark Packages are searched. + * + * The name of the pypi package to install. An optional exact version specification is also + * supported. Examples: "simplejson" and "simplejson==3.8.0". + * + * The repository where the package can be found. If not specified, the default pip index is + * used. + * + * URI of the requirements.txt file to install. Only Workspace paths and Unity Catalog + * Volumes paths are supported. + * For example: `{ "requirements": "/Workspace/path/to/requirements.txt" }` or `{ + * "requirements" : "/Volumes/path/to/requirements.txt" }` + * + * URI of the wheel library to install. Supported URIs include Workspace paths, Unity + * Catalog Volumes paths, and S3 URIs. + * For example: `{ "whl": "/Workspace/path/to/library.whl" }`, `{ "whl" : + * "/Volumes/path/to/library.whl" }` or + * `{ "whl": "s3://my-bucket/library.whl" }`. + * If S3 is used, please make sure the cluster has read access on the library. You may need + * to + * launch the cluster with an IAM role to access the S3 URI. + * + * The path of the notebook to be run in the Databricks workspace or remote repository. + * For notebooks stored in the Databricks workspace, the path must be absolute and begin + * with a slash. + * For notebooks stored in a remote repository, the path must be relative. This field is + * required. + * + * Optional `warehouse_id` to run the notebook on a SQL warehouse. Classic SQL warehouses + * are NOT supported, please use serverless or pro SQL warehouses. + * + * Note that SQL warehouses only support SQL cells; if the notebook contains non-SQL cells, + * the run will fail. + * + * The full name of the pipeline task to execute. + * + * Named entry point to use, if it does not exist in the metadata of the package it executes + * the function from the package directly using `$packageName.$entryPoint()` + * + * Name of the package to execute + * + * Deprecated since 04/2016. Provide a `jar` through the `libraries` field instead. For an + * example, see :method:jobs/create. + * + * The full name of the class containing the main method to be executed. This class must be + * contained in a JAR provided as a library. + * + * The code must use `SparkContext.getOrCreate` to obtain a Spark context; otherwise, runs + * of the job fail. + * + * The Python file to be executed. Cloud file URIs (such as dbfs:/, s3:/, adls:/, gcs:/) and + * workspace paths are supported. For python files stored in the Databricks workspace, the + * path must be absolute and begin with `/`. For files stored in a remote repository, the + * path must be relative. This field is required. + * + * The canonical identifier of the SQL alert. + * + * The canonical identifier of the destination to receive email notification. This parameter + * is mutually exclusive with user_name. You cannot set both destination_id and user_name + * for subscription notifications. + * + * The user name to receive the subscription email. This parameter is mutually exclusive + * with destination_id. You cannot set both destination_id and user_name for subscription + * notifications. + * + * Subject of the email sent to subscribers of this task. + * + * The canonical identifier of the SQL dashboard. + * + * Path of the SQL file. Must be relative if the source is a remote Git repository and + * absolute for workspace paths. + * + * The canonical identifier of the SQL query. + * + * The canonical identifier of the SQL warehouse. Recommended to use with serverless or pro + * SQL warehouses. Classic SQL warehouses are only supported for SQL alert, dashboard and + * query tasks and are limited to scheduled single-task jobs. + * + * A unique name for the task. This field is used to refer to this task from other tasks. + * This field is required and must be unique within its parent job. + * On Update or Reset, this field is used to reference the tasks to be updated or reset. + * + * URL to be monitored for file arrivals. The path must point to the root or a subpath of + * the external location. + * + * The name of the catalog in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the catalog + * name. + * + * The name of the schema in Unity Catalog. Required when enabling inference tables. NOTE: + * On update, you have to disable inference table first in order to change the schema name. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you have to disable inference + * table first in order to change the prefix name. + * + * The name of the catalog in Unity Catalog. NOTE: On update, you cannot change the catalog + * name if the inference table is already enabled. + * + * The name of the schema in Unity Catalog. NOTE: On update, you cannot change the schema + * name if the inference table is already enabled. + * + * The prefix of the table in Unity Catalog. NOTE: On update, you cannot change the prefix + * name if the inference table is already enabled. + * + * The name of the entity to be served. The entity may be a model in the Databricks Model + * Registry, a model in the Unity Catalog (UC), + * or a function of type FEATURE_SPEC in the UC. If it is a UC object, the full name of the + * object should be given in the form of + * __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry to be served or empty if the entity + * is a FEATURE_SPEC. + * + * The Databricks secret key reference for an AWS access key ID with permissions to interact + * with Bedrock services. If you prefer to paste your API key directly, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * An AWS access key ID with permissions to interact with Bedrock services provided as a + * plaintext string. If you prefer to reference your key using Databricks Secrets, see + * `aws_access_key_id`. You must provide an API key using one of the following fields: + * `aws_access_key_id` or `aws_access_key_id_plaintext`. + * + * The AWS region to use. Bedrock has to be enabled there. + * + * The Databricks secret key reference for an AWS secret access key paired with the access + * key ID, with permissions to interact with Bedrock services. If you prefer to paste your + * API key directly, see `aws_secret_access_key_plaintext`. You must provide an API key + * using one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * An AWS secret access key paired with the access key ID, with permissions to interact with + * Bedrock services provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `aws_secret_access_key`. You must provide an API key using + * one of the following fields: `aws_secret_access_key` or + * `aws_secret_access_key_plaintext`. + * + * The Databricks secret key reference for an Anthropic API key. If you prefer to paste your + * API key directly, see `anthropic_api_key_plaintext`. You must provide an API key using + * one of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * The Anthropic API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `anthropic_api_key`. You must provide an API key using one + * of the following fields: `anthropic_api_key` or `anthropic_api_key_plaintext`. + * + * This is an optional field to provide a customized base URL for the Cohere API. + * If left unspecified, the standard Cohere base URL is used. + * + * + * The Databricks secret key reference for a Cohere API key. If you prefer to paste your API + * key directly, see `cohere_api_key_plaintext`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Cohere API key provided as a plaintext string. If you prefer to reference your key + * using Databricks Secrets, see `cohere_api_key`. You must provide an API key using one of + * the following fields: `cohere_api_key` or `cohere_api_key_plaintext`. + * + * The Databricks secret key reference for a Databricks API token that corresponds to a user + * or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model. + * If you prefer to paste your API key directly, see `databricks_api_token_plaintext`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The Databricks API token that corresponds to a user or service + * principal with Can Query access to the model serving endpoint pointed to by this external + * model provided as a plaintext string. + * If you prefer to reference your key using Databricks Secrets, see `databricks_api_token`. + * You must provide an API key using one of the following fields: `databricks_api_token` or + * `databricks_api_token_plaintext`. + * + * + * The URL of the Databricks workspace containing the model serving endpoint pointed to by + * this external model. + * + * + * The name of the external model. + * + * The task type of the external model. + * + * ARN of the instance profile that the served entity uses to access AWS resources. + * + * The name of a served entity. It must be unique across an endpoint. A served entity name + * can consist of alphanumeric characters, dashes, and underscores. + * If not specified for an external model, this field defaults to external_model.name, with + * '.' and ':' replaced with '-', and if not specified for other + * entities, it defaults to -. + * + * + * The workload size of the served entity. The workload size corresponds to a range of + * provisioned concurrency that the compute autoscales between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size is 0. + * + * + * The workload type of the served entity. The workload type selects which type of compute + * to use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * ARN of the instance profile that the served model will use to access AWS resources. + * + * The name of the model in Databricks Model Registry to be served or if the model resides + * in Unity Catalog, the full name of model, + * in the form of __catalog_name__.__schema_name__.__model_name__. + * + * + * The version of the model in Databricks Model Registry or Unity Catalog to be served. + * + * The name of a served model. It must be unique across an endpoint. If not specified, this + * field will default to -. + * A served model name can consist of alphanumeric characters, dashes, and underscores. + * + * + * The name of the served model this route configures traffic for. + * + * The name of the serving endpoint. This field is required and must be unique across a + * Databricks workspace. + * An endpoint name can consist of alphanumeric characters, dashes, and underscores. + * + * + * Key field for a serving endpoint tag. + * + * Optional value field for a serving endpoint tag. + * + * Description of this `registered_model`. + * + * Current stage for this `model_version`. + * + * Description of this `model_version`. + * + * Unique name of the model + * + * MLflow run ID used when creating `model_version`, if `source` was generated by an + * experiment run stored in MLflow tracking server. + * + * Run Link: Direct link to the run that generated this version + * + * URI indicating the location of the source model artifacts, used when creating + * `model_version` + * + * Details on current `status`, if it is pending or failed. + * + * User that created this `model_version`. + * + * Model's version number. + * + * Unique name for the model. + * + * User that created this `registered_model` + * + * Budget policy of this pipeline. + * + * A catalog in Unity Catalog to publish data from this pipeline to. If `target` is + * specified, tables in this pipeline are published to a `target` schema inside `catalog` + * (for example, `catalog`.`target`.`table`). If `target` is not specified, no data is + * published to Unity Catalog. + * + * DLT Release Channel that specifies which version to use. + * + * The node type of the Spark driver. + * Note that this field is optional; if unset, the driver node type will be set as the same + * value + * as `node_type_id` defined above. + * + * A label for the cluster specification, either `default` to configure the default cluster, + * or `maintenance` to configure the maintenance cluster. This field is optional. The + * default value is `default`. + * + * The path to the file containing metadata about the deployment. + * + * Pipeline product edition. + * + * Immutable. The Unity Catalog connection this gateway pipeline uses to communicate with + * the source. + * + * Required, Immutable. The name of the catalog for the gateway pipeline's storage + * location. + * + * Optional. The Unity Catalog-compatible name for the gateway storage location. + * This is the destination to use for the data that is extracted by the gateway. + * Delta Live Tables system will automatically create the storage location under the catalog + * and schema. + * + * + * Required, Immutable. The name of the schema for the gateway pipelines's storage + * location. + * + * Unique identifier for this pipeline. + * + * Immutable. The Unity Catalog connection this ingestion pipeline uses to communicate with + * the source. Specify either ingestion_gateway_id or connection_name. + * + * Immutable. Identifier for the ingestion gateway used by this ingestion pipeline to + * communicate with the source. Specify either ingestion_gateway_id or connection_name. + * + * Required. Destination catalog to store tables. + * + * Required. Destination schema to store tables in. Tables with the same name as the source + * tables are created in this destination schema. The pipeline fails If a table with the + * same name already exists. + * + * The source catalog name. Might be optional depending on the type of source. + * + * Required. Schema name in the source database. + * + * Required. Destination catalog to store table. + * + * Required. Destination schema to store table. + * + * Optional. Destination table name. The pipeline fails If a table with that name already + * exists. If not set, the source table name is used. + * + * Source catalog name. Might be optional depending on the type of source. + * + * Schema name in the source database. Might be optional depending on the type of source. + * + * Required. Table name in the source database. + * + * The absolute path of the file. + * + * URI of the jar to be installed. Currently only DBFS is supported. + * + * + * The absolute path of the notebook. + * + * URI of the whl to be installed. + * + * Friendly identifier for this pipeline. + * + * The default schema (database) where tables are read from or published to. The presence of + * this field implies that the pipeline is in direct publishing mode. + * + * DBFS root directory for storing checkpoints and tables. + * + * Target schema (database) to add tables in this pipeline to. If not specified, no data is + * published to the Hive metastore or Unity Catalog. To publish to Unity Catalog, also + * specify `catalog`. + * + * The directory to store monitoring assets (e.g. dashboard, metric tables). + * + * Name of the baseline table from which drift metrics are computed from. + * Columns in the monitored table should also be present in the baseline table. + * + * + * Jinja template for a SQL expression that specifies how to compute the metric. See [create + * metric + * definition](https://docs.databricks.com/en/lakehouse-monitoring/custom-metrics.html#create-definition). + * + * Name of the metric in the output tables. + * + * The output type of the custom metric. + * + * Optional column that contains the ground truth for the prediction. + * + * Column that contains the id of the model generating the predictions. Metrics will be + * computed per model id by + * default, and also across all model ids. + * + * + * Column that contains the output/prediction from the model. + * + * Optional column that contains the prediction probabilities for each class in a + * classification problem type. + * The values in this column should be a map, mapping each class label to the prediction + * probability for a given + * sample. The map should be of PySpark MapType(). + * + * + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + * + * + * Schema where output metric tables are created. + * + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + * + * + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + * + * + * Optional argument to specify the warehouse for dashboard creation. If not specified, the + * first running + * warehouse will be used. + * + * + * The name of the catalog where the schema and the registered model reside + * + * The comment attached to the registered model + * + * The name of the registered model + * + * The name of the schema where the registered model resides + * + * The storage location on the cloud under which model version data files are stored + * + * Name of parent catalog. + * + * User-provided free-form text description. + * + * Name of schema, relative to parent catalog. + * + * Storage root URL for managed tables within schema. + * + * Behavior for PII filter. Currently only 'BLOCK' is supported. If 'BLOCK' is set for the + * input guardrail and the request contains PII, the request is not sent to the model server + * and 400 status code is returned; if 'BLOCK' is set for the output guardrail and the model + * response contains PII, the PII info in the response is redacted and 400 status code is + * returned. + * + * Key field for a rate limit. Currently, only 'user' and 'endpoint' are supported, with + * 'endpoint' being the default if not specified. + * + * Renewal period field for a rate limit. Currently, only 'minute' is supported. + * + * The underlying provider in Amazon Bedrock. Supported values (case insensitive) include: + * Anthropic, Cohere, AI21Labs, Amazon. + * + * The name of the provider for the external model. Currently, the supported providers are + * 'ai21labs', 'anthropic', + * 'amazon-bedrock', 'cohere', 'databricks-model-serving', 'google-cloud-vertex-ai', + * 'openai', and 'palm'.", + * + * + * The workload size of the served model. The workload size corresponds to a range of + * provisioned concurrency that the compute will autoscale between. + * A single unit of provisioned concurrency can process one request at a time. + * Valid workload sizes are "Small" (4 - 4 provisioned concurrency), "Medium" (8 - 16 + * provisioned concurrency), and "Large" (16 - 64 provisioned concurrency). + * If scale-to-zero is enabled, the lower bound of the provisioned concurrency for each + * workload size will be 0. + * + * + * The workload type of the served model. The workload type selects which type of compute to + * use in the endpoint. The default value for this parameter is + * "CPU". For deep learning workloads, GPU acceleration is available by selecting workload + * types like GPU_SMALL and others. + * See the available [GPU + * types](https://docs.databricks.com/machine-learning/model-serving/create-manage-serving-endpoints.html#gpu-workload-types). + * + * + * Key field for a serving endpoint rate limit. Currently, only 'user' and 'endpoint' are + * supported, with 'endpoint' being the default if not specified. + * + * Renewal period field for a serving endpoint rate limit. Currently, only 'minute' is + * supported. + * + * Current status of `model_version` + * + * Databricks Enhanced Autoscaling optimizes cluster utilization by automatically + * allocating cluster resources based on workload volume, with minimal impact to + * the data processing latency of your pipelines. Enhanced Autoscaling is available + * for `updates` clusters only. The legacy autoscaling feature is used for `maintenance` + * clusters. + * + * + * The SCD type to use to ingest the table. + * + * Can only be one of ``"CUSTOM_METRIC_TYPE_AGGREGATE"``, ``"CUSTOM_METRIC_TYPE_DERIVED"``, + * or ``"CUSTOM_METRIC_TYPE_DRIFT"``. + * The ``"CUSTOM_METRIC_TYPE_AGGREGATE"`` and ``"CUSTOM_METRIC_TYPE_DERIVED"`` metrics + * are computed on a single table, whereas the ``"CUSTOM_METRIC_TYPE_DRIFT"`` compare + * metrics across + * baseline and input table, or across the two consecutive time windows. + * - CUSTOM_METRIC_TYPE_AGGREGATE: only depend on the existing columns in your table + * - CUSTOM_METRIC_TYPE_DERIVED: depend on previously computed aggregate metrics + * - CUSTOM_METRIC_TYPE_DRIFT: depend on previously computed aggregate or derived metrics + * + * + * Read only field that indicates whether a schedule is paused or not. + */ +export enum ProblemType { + ProblemTypeClassification = "PROBLEM_TYPE_CLASSIFICATION", + ProblemTypeRegression = "PROBLEM_TYPE_REGRESSION", +} + +export interface NotificationsClass { + /** + * Who to send notifications to on monitor failure. + */ + on_failure?: OnNewClassificationTagDetectedClass | string; + /** + * Who to send notifications to when new data classification tags are detected. + */ + on_new_classification_tag_detected?: + | OnNewClassificationTagDetectedClass + | string; +} + +export interface OnNewClassificationTagDetectedClass { + /** + * The list of email addresses to send the notification to. A maximum of 5 email addresses + * is supported. + */ + email_addresses?: string[] | string; +} + +export interface BundleSchem16 { + /** + * Read only field that indicates whether a schedule is paused or not. + */ + pause_status?: PauseStatus; + /** + * The expression that determines when to run the monitor. See + * [examples](https://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html). + */ + quartz_cron_expression: string; + /** + * The timezone id (e.g., ``"PST"``) in which to evaluate the quartz expression. + */ + timezone_id: string; +} + +export interface SnapshotClass {} + +export interface TimeSeriesClass { + /** + * Granularities for aggregating data into time windows based on their timestamp. Currently + * the following static + * granularities are supported: + * {``"5 minutes"``, ``"30 minutes"``, ``"1 hour"``, ``"1 day"``, ``" week(s)"``, ``"1 + * month"``, ``"1 year"``}. + */ + granularities: string[] | string; + /** + * Column that contains the timestamps of requests. The column must be one of the following: + * - A ``TimestampType`` column + * - A column whose values can be converted to timestamps through the pyspark + * ``to_timestamp`` + * [function](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html). + */ + timestamp_col: string; +} + +export interface RegisteredModelClass { + /** + * The name of the catalog where the schema and the registered model reside + */ + catalog_name: string; + /** + * The comment attached to the registered model + */ + comment?: string; + grants?: Array | string; + /** + * The name of the registered model + */ + name: string; + /** + * The name of the schema where the registered model resides + */ + schema_name: string; + /** + * The storage location on the cloud under which model version data files are stored + */ + storage_location?: string; +} + +export interface GrantClass { + principal: string; + privileges: string[] | string; +} + +export interface BundleSchem17 { + /** + * Name of parent catalog. + */ + catalog_name: string; + /** + * User-provided free-form text description. + */ + comment?: string; + grants?: Array | string; + /** + * Name of schema, relative to parent catalog. + */ + name: string; + properties?: {[key: string]: string} | string; + /** + * Storage root URL for managed tables within schema. + */ + storage_root?: string; +} + +export interface SyncClass { + exclude?: string[] | string; + include?: string[] | string; + paths?: string[] | string; +} + +export interface TargetClass { + artifacts?: {[key: string]: ArtifactClass | string} | string; + bundle?: BundleClass | string; + cluster_id?: string; + compute_id?: string; + default?: boolean | string; + git?: GitClass | string; + mode?: string; + permissions?: Array | string; + presets?: PresetsClass | string; + resources?: ResourcesClass | string; + run_as?: RunAsClass | string; + sync?: SyncClass | string; + variables?: {[key: string]: any} | string; + workspace?: BundleSchem18 | string; +} + +export interface BundleSchem18 { + artifact_path?: string; + auth_type?: string; + azure_client_id?: string; + azure_environment?: string; + azure_login_app_id?: string; + azure_tenant_id?: string; + azure_use_msi?: boolean | string; + azure_workspace_resource_id?: string; + client_id?: string; + file_path?: string; + google_service_account?: string; + host?: string; + profile?: string; + resource_path?: string; + root_path?: string; + state_path?: string; +} + +export interface VariableValue { + default?: any; + description?: string; + lookup?: LookupClass | string; + type?: string; +} + +export interface LookupClass { + alert?: string; + cluster?: string; + cluster_policy?: string; + dashboard?: string; + instance_pool?: string; + job?: string; + metastore?: string; + pipeline?: string; + query?: string; + service_principal?: string; + warehouse?: string; +} + +// Converts JSON strings to/from your types +// and asserts the results of JSON.parse at runtime +export class Convert { + public static toBundleSchema(json: string): BundleSchema { + return cast(JSON.parse(json), r("BundleSchema")); + } + + public static bundleSchemaToJson(value: BundleSchema): string { + return JSON.stringify(uncast(value, r("BundleSchema")), null, 2); + } +} + +function invalidValue(typ: any, val: any, key: any, parent: any = ""): never { + const prettyTyp = prettyTypeName(typ); + const parentText = parent ? ` on ${parent}` : ""; + const keyText = key ? ` for key "${key}"` : ""; + throw Error( + `Invalid value${keyText}${parentText}. Expected ${prettyTyp} but got ${JSON.stringify( + val + )}` + ); +} + +function prettyTypeName(typ: any): string { + if (Array.isArray(typ)) { + if (typ.length === 2 && typ[0] === undefined) { + return `an optional ${prettyTypeName(typ[1])}`; + } else { + return `one of [${typ + .map((a) => { + return prettyTypeName(a); + }) + .join(", ")}]`; + } + } else if (typeof typ === "object" && typ.literal !== undefined) { + return typ.literal; + } else { + return typeof typ; + } +} + +function jsonToJSProps(typ: any): any { + if (typ.jsonToJS === undefined) { + const map: any = {}; + typ.props.forEach((p: any) => (map[p.json] = {key: p.js, typ: p.typ})); + typ.jsonToJS = map; + } + return typ.jsonToJS; +} + +function jsToJSONProps(typ: any): any { + if (typ.jsToJSON === undefined) { + const map: any = {}; + typ.props.forEach((p: any) => (map[p.js] = {key: p.json, typ: p.typ})); + typ.jsToJSON = map; + } + return typ.jsToJSON; +} + +function transform( + val: any, + typ: any, + getProps: any, + key: any = "", + parent: any = "" +): any { + function transformPrimitive(typ: string, val: any): any { + if (typeof typ === typeof val) return val; + return invalidValue(typ, val, key, parent); + } + + function transformUnion(typs: any[], val: any): any { + // val must validate against one typ in typs + const l = typs.length; + for (let i = 0; i < l; i++) { + const typ = typs[i]; + try { + return transform(val, typ, getProps); + } catch (_) {} + } + return invalidValue(typs, val, key, parent); + } + + function transformEnum(cases: string[], val: any): any { + if (cases.indexOf(val) !== -1) return val; + return invalidValue( + cases.map((a) => { + return l(a); + }), + val, + key, + parent + ); + } + + function transformArray(typ: any, val: any): any { + // val must be an array with no invalid elements + if (!Array.isArray(val)) + return invalidValue(l("array"), val, key, parent); + return val.map((el) => transform(el, typ, getProps)); + } + + function transformDate(val: any): any { + if (val === null) { + return null; + } + const d = new Date(val); + if (isNaN(d.valueOf())) { + return invalidValue(l("Date"), val, key, parent); + } + return d; + } + + function transformObject( + props: {[k: string]: any}, + additional: any, + val: any + ): any { + if (val === null || typeof val !== "object" || Array.isArray(val)) { + return invalidValue(l(ref || "object"), val, key, parent); + } + const result: any = {}; + Object.getOwnPropertyNames(props).forEach((key) => { + const prop = props[key]; + const v = Object.prototype.hasOwnProperty.call(val, key) + ? val[key] + : undefined; + result[prop.key] = transform(v, prop.typ, getProps, key, ref); + }); + Object.getOwnPropertyNames(val).forEach((key) => { + if (!Object.prototype.hasOwnProperty.call(props, key)) { + result[key] = transform( + val[key], + additional, + getProps, + key, + ref + ); + } + }); + return result; + } + + if (typ === "any") return val; + if (typ === null) { + if (val === null) return val; + return invalidValue(typ, val, key, parent); + } + if (typ === false) return invalidValue(typ, val, key, parent); + let ref: any = undefined; + while (typeof typ === "object" && typ.ref !== undefined) { + ref = typ.ref; + typ = typeMap[typ.ref]; + } + if (Array.isArray(typ)) return transformEnum(typ, val); + if (typeof typ === "object") { + return typ.hasOwnProperty("unionMembers") + ? transformUnion(typ.unionMembers, val) + : typ.hasOwnProperty("arrayItems") + ? transformArray(typ.arrayItems, val) + : typ.hasOwnProperty("props") + ? transformObject(getProps(typ), typ.additional, val) + : invalidValue(typ, val, key, parent); + } + // Numbers can be parsed by Date but shouldn't be. + if (typ === Date && typeof val !== "number") return transformDate(val); + return transformPrimitive(typ, val); +} + +function cast(val: any, typ: any): T { + return transform(val, typ, jsonToJSProps); +} + +function uncast(val: T, typ: any): any { + return transform(val, typ, jsToJSONProps); +} + +function l(typ: any) { + return {literal: typ}; +} + +function a(typ: any) { + return {arrayItems: typ}; +} + +function u(...typs: any[]) { + return {unionMembers: typs}; +} + +function o(props: any[], additional: any) { + return {props, additional}; +} + +function m(additional: any) { + return {props: [], additional}; +} + +function r(name: string) { + return {ref: name}; +} + +const typeMap: any = { + BundleSchema: o( + [ + { + json: "artifacts", + js: "artifacts", + typ: u(undefined, u(m(u(r("ArtifactClass"), "")), "")), + }, + { + json: "bundle", + js: "bundle", + typ: u(undefined, u(r("BundleClass"), "")), + }, + { + json: "experimental", + js: "experimental", + typ: u(undefined, u(r("ExperimentalClass"), "")), + }, + {json: "include", js: "include", typ: u(undefined, u(a(""), ""))}, + { + json: "permissions", + js: "permissions", + typ: u(undefined, u(a(u(r("PermissionClass"), "")), "")), + }, + { + json: "presets", + js: "presets", + typ: u(undefined, u(r("PresetsClass"), "")), + }, + { + json: "resources", + js: "resources", + typ: u(undefined, u(r("ResourcesClass"), "")), + }, + { + json: "run_as", + js: "run_as", + typ: u(undefined, u(r("RunAsClass"), "")), + }, + { + json: "sync", + js: "sync", + typ: u(undefined, u(r("SyncClass"), "")), + }, + { + json: "targets", + js: "targets", + typ: u(undefined, u(m(u(r("TargetClass"), "")), "")), + }, + { + json: "variables", + js: "variables", + typ: u(undefined, u(m(r("VariableValue")), "")), + }, + { + json: "workspace", + js: "workspace", + typ: u(undefined, u(r("BundleSchem18"), "")), + }, + ], + false + ), + ArtifactClass: o( + [ + {json: "build", js: "build", typ: u(undefined, "")}, + {json: "executable", js: "executable", typ: u(undefined, "")}, + { + json: "files", + js: "files", + typ: u(undefined, u(a(u(r("PurpleBundleSchem"), "")), "")), + }, + {json: "path", js: "path", typ: u(undefined, "")}, + {json: "type", js: "type", typ: ""}, + ], + false + ), + PurpleBundleSchem: o([{json: "source", js: "source", typ: ""}], false), + BundleClass: o( + [ + {json: "cluster_id", js: "cluster_id", typ: u(undefined, "")}, + {json: "compute_id", js: "compute_id", typ: u(undefined, "")}, + { + json: "databricks_cli_version", + js: "databricks_cli_version", + typ: u(undefined, ""), + }, + { + json: "deployment", + js: "deployment", + typ: u(undefined, u(r("FluffyBundleSchem"), "")), + }, + {json: "git", js: "git", typ: u(undefined, u(r("GitClass"), ""))}, + {json: "name", js: "name", typ: ""}, + ], + false + ), + FluffyBundleSchem: o( + [ + { + json: "fail_on_active_runs", + js: "fail_on_active_runs", + typ: u(undefined, u(true, "")), + }, + { + json: "lock", + js: "lock", + typ: u(undefined, u(r("LockClass"), "")), + }, + ], + false + ), + LockClass: o( + [ + {json: "enabled", js: "enabled", typ: u(undefined, u(true, ""))}, + {json: "force", js: "force", typ: u(undefined, u(true, ""))}, + ], + false + ), + GitClass: o( + [ + {json: "branch", js: "branch", typ: u(undefined, "")}, + {json: "origin_url", js: "origin_url", typ: u(undefined, "")}, + ], + false + ), + ExperimentalClass: o( + [ + { + json: "pydabs", + js: "pydabs", + typ: u(undefined, u(r("PydabsClass"), "")), + }, + { + json: "python_wheel_wrapper", + js: "python_wheel_wrapper", + typ: u(undefined, u(true, "")), + }, + {json: "scripts", js: "scripts", typ: u(undefined, u(m(""), ""))}, + { + json: "use_legacy_run_as", + js: "use_legacy_run_as", + typ: u(undefined, u(true, "")), + }, + ], + false + ), + PydabsClass: o( + [ + {json: "enabled", js: "enabled", typ: u(undefined, u(true, ""))}, + {json: "import", js: "import", typ: u(undefined, u(a(""), ""))}, + {json: "venv_path", js: "venv_path", typ: u(undefined, "")}, + ], + false + ), + PermissionClass: o( + [ + {json: "group_name", js: "group_name", typ: u(undefined, "")}, + {json: "level", js: "level", typ: ""}, + { + json: "service_principal_name", + js: "service_principal_name", + typ: u(undefined, ""), + }, + {json: "user_name", js: "user_name", typ: u(undefined, "")}, + ], + false + ), + PresetsClass: o( + [ + { + json: "jobs_max_concurrent_runs", + js: "jobs_max_concurrent_runs", + typ: u(undefined, u(0, "")), + }, + {json: "name_prefix", js: "name_prefix", typ: u(undefined, "")}, + { + json: "pipelines_development", + js: "pipelines_development", + typ: u(undefined, u(true, "")), + }, + {json: "tags", js: "tags", typ: u(undefined, u(m(""), ""))}, + { + json: "trigger_pause_status", + js: "trigger_pause_status", + typ: u(undefined, ""), + }, + ], + false + ), + ResourcesClass: o( + [ + { + json: "clusters", + js: "clusters", + typ: u(undefined, u(m(u(r("TentacledBundleSchem"), "")), "")), + }, + { + json: "experiments", + js: "experiments", + typ: u(undefined, u(m(u(r("ExperimentClass"), "")), "")), + }, + { + json: "jobs", + js: "jobs", + typ: u(undefined, u(m(u(r("JobClass"), "")), "")), + }, + { + json: "model_serving_endpoints", + js: "model_serving_endpoints", + typ: u( + undefined, + u(m(u(r("ModelServingEndpointClass"), "")), "") + ), + }, + { 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"google_service_account", + js: "google_service_account", + typ: u(undefined, ""), + }, + {json: "host", js: "host", typ: u(undefined, "")}, + {json: "profile", js: "profile", typ: u(undefined, "")}, + {json: "resource_path", js: "resource_path", typ: u(undefined, "")}, + {json: "root_path", js: "root_path", typ: u(undefined, "")}, + {json: "state_path", js: "state_path", typ: u(undefined, "")}, + ], + false + ), + VariableValue: o( + [ + {json: "default", js: "default", typ: u(undefined, "any")}, + {json: "description", js: "description", typ: u(undefined, "")}, + { + json: "lookup", + js: "lookup", + typ: u(undefined, u(r("LookupClass"), "")), + }, + {json: "type", js: "type", typ: u(undefined, "")}, + ], + false + ), + LookupClass: o( + [ + {json: "alert", js: "alert", typ: u(undefined, "")}, + {json: "cluster", js: "cluster", typ: u(undefined, "")}, + { + json: "cluster_policy", + js: "cluster_policy", + typ: u(undefined, ""), + }, + {json: "dashboard", js: "dashboard", typ: u(undefined, "")}, + {json: "instance_pool", js: "instance_pool", typ: u(undefined, "")}, + {json: "job", js: "job", typ: u(undefined, "")}, + {json: "metastore", js: "metastore", typ: u(undefined, "")}, + {json: "pipeline", js: "pipeline", typ: u(undefined, "")}, + {json: "query", js: "query", typ: u(undefined, "")}, + { + json: "service_principal", + js: "service_principal", + typ: u(undefined, ""), + }, + {json: "warehouse", js: "warehouse", typ: u(undefined, "")}, + ], + false + ), + AwsAttributesAvailability: ["ON_DEMAND", "SPOT", "SPOT_WITH_FALLBACK"], + EbsVolumeType: ["GENERAL_PURPOSE_SSD", "THROUGHPUT_OPTIMIZED_HDD"], + AzureAttributesAvailability: [ + "ON_DEMAND_AZURE", + "SPOT_AZURE", + "SPOT_WITH_FALLBACK_AZURE", + ], + DataSecurityMode: [ + "LEGACY_PASSTHROUGH", + "LEGACY_SINGLE_USER", + "LEGACY_SINGLE_USER_STANDARD", + "LEGACY_TABLE_ACL", + "NONE", + "SINGLE_USER", + "USER_ISOLATION", + ], + GcpAttributesAvailability: [ + "ON_DEMAND_GCP", + "PREEMPTIBLE_GCP", + "PREEMPTIBLE_WITH_FALLBACK_GCP", + ], + RuntimeEngine: ["NULL", "PHOTON", "STANDARD"], + PauseStatus: ["PAUSED", "UNPAUSED"], + GitProvider: [ + "awsCodeCommit", + "azureDevOpsServices", + "bitbucketCloud", + "bitbucketServer", + "gitHub", + "gitHubEnterprise", + "gitLab", + "gitLabEnterpriseEdition", + ], + Metric: [ + "RUN_DURATION_SECONDS", + "STREAMING_BACKLOG_BYTES", + "STREAMING_BACKLOG_FILES", + "STREAMING_BACKLOG_RECORDS", + "STREAMING_BACKLOG_SECONDS", + ], + RuleOp: ["GREATER_THAN"], + ConditionTaskOp: [ + "EQUAL_TO", + "GREATER_THAN", + "GREATER_THAN_OR_EQUAL", + "LESS_THAN", + "LESS_THAN_OR_EQUAL", + "NOT_EQUAL", + ], + Source: ["GIT", "WORKSPACE"], + RunIf: [ + "ALL_DONE", + "ALL_FAILED", + "ALL_SUCCESS", + "AT_LEAST_ONE_FAILED", + "AT_LEAST_ONE_SUCCESS", + "NONE_FAILED", + ], + Unit: ["DAYS", "HOURS", "WEEKS"], + Condition: ["ALL_UPDATED", "ANY_UPDATED"], + Behavior: ["BLOCK", "NONE"], + Key: ["endpoint", "user"], + RenewalPeriod: ["minute"], + BedrockProvider: ["ai21labs", "amazon", "anthropic", "cohere"], + Provider: [ + "ai21labs", + "amazon-bedrock", + "anthropic", + "cohere", + "databricks-model-serving", + "google-cloud-vertex-ai", + "openai", + "palm", + ], + WorkloadSize: ["Large", "Medium", "Small"], + WorkloadTypeEnum: [ + "CPU", + "GPU_LARGE", + "GPU_MEDIUM", + "GPU_SMALL", + "MULTIGPU_MEDIUM", + ], + Status: ["FAILED_REGISTRATION", "PENDING_REGISTRATION", "READY"], + Mode: ["ENHANCED", "LEGACY"], + Kind: ["BUNDLE"], + ScdType: ["SCD_TYPE_1", "SCD_TYPE_2"], + Type: [ + "CUSTOM_METRIC_TYPE_AGGREGATE", + "CUSTOM_METRIC_TYPE_DERIVED", + "CUSTOM_METRIC_TYPE_DRIFT", + ], + ProblemType: ["PROBLEM_TYPE_CLASSIFICATION", "PROBLEM_TYPE_REGRESSION"], +}; diff --git a/packages/databricks-vscode/src/bundle/BundleWatcher.ts b/packages/databricks-vscode/src/bundle/BundleWatcher.ts new file mode 100644 index 000000000..fe24b9c7b --- /dev/null +++ b/packages/databricks-vscode/src/bundle/BundleWatcher.ts @@ -0,0 +1,92 @@ +import {Disposable, EventEmitter, Uri, workspace} from "vscode"; +import {BundleFileSet, getAbsoluteGlobPath} from "./BundleFileSet"; +import path from "path"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; + +export class BundleWatcher implements Disposable { + private disposables: Disposable[] = []; + + private readonly _onDidChange = new EventEmitter(); + public readonly onDidChange = this._onDidChange.event; + + private readonly _onDidChangeRootFile = new EventEmitter(); + public readonly onDidChangeRootFile = this._onDidChangeRootFile.event; + + private readonly _onDidCreate = new EventEmitter(); + public readonly onDidCreate = this._onDidCreate.event; + + private readonly _onDidDelete = new EventEmitter(); + public readonly onDidDelete = this._onDidDelete.event; + + private initCleanup: Disposable; + constructor( + private readonly bundleFileSet: BundleFileSet, + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + this.initCleanup = this.init(); + this.disposables.push( + this.workspaceFolderManager.onDidChangeActiveWorkspaceFolder(() => { + this.initCleanup.dispose(); + this.initCleanup = this.init(); + this.bundleFileSet.bundleDataCache.invalidate(); + }) + ); + } + + private init() { + const yamlWatcher = workspace.createFileSystemWatcher( + getAbsoluteGlobPath( + path.join("**", "*.{yaml,yml}"), + this.workspaceFolderManager.activeWorkspaceFolder.uri + ) + ); + + const disposables: Disposable[] = [ + yamlWatcher, + yamlWatcher.onDidCreate((e) => { + this.yamlFileChangeHandler(e, "CREATE"); + }), + yamlWatcher.onDidChange((e) => { + this.yamlFileChangeHandler(e, "CHANGE"); + }), + yamlWatcher.onDidDelete((e) => { + this.yamlFileChangeHandler(e, "DELETE"); + }), + ]; + + return { + dispose: () => { + disposables.forEach((i) => i.dispose()); + }, + }; + } + + private async yamlFileChangeHandler( + e: Uri, + type: "CREATE" | "CHANGE" | "DELETE" + ) { + if (!(await this.bundleFileSet.isBundleFile(e))) { + return; + } + + this.bundleFileSet.bundleDataCache.invalidate(); + this._onDidChange.fire(); + // to provide additional granularity, we also fire an event when the root bundle file changes + if (this.bundleFileSet.isRootBundleFile(e)) { + this._onDidChangeRootFile.fire(); + } + switch (type) { + case "CREATE": + this._onDidCreate.fire(e); + break; + case "DELETE": + this._onDidDelete.fire(e); + break; + } + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + this.initCleanup.dispose(); + } +} diff --git a/packages/databricks-vscode/src/bundle/GenerateBundle.ts b/packages/databricks-vscode/src/bundle/GenerateBundle.ts deleted file mode 100644 index 55a948ef0..000000000 --- a/packages/databricks-vscode/src/bundle/GenerateBundle.ts +++ /dev/null @@ -1,46 +0,0 @@ -import {CliWrapper} from "../cli/CliWrapper"; -import {extensions, Uri} from "vscode"; -import path from "node:path"; - -export async function generateBundleSchema(cli: CliWrapper) { - // get freshly generated bundle schema - const bundleSchema = await cli.getBundleSchema(); - - // URI scheme for DABs JSON schemas - const dabsUriScheme = "dabs"; - - // URI for bundle root config json schema - const rootConfigSchemaUri = `${dabsUriScheme}:///root.json`; - - const extensionYaml = extensions.getExtension("redhat.vscode-yaml"); - if (extensionYaml) { - const redHatYamlSchemaApi = await extensionYaml.activate(); - - // We use the API exposed from teh activate() function of the redhat.vscode-yaml - // extension to registor a custom schema provider - redHatYamlSchemaApi.registerContributor( - "dabs", - (resource: string) => { - const validFileNames: string[] = [ - "databricks.yml", - "databricks.yaml", - "bundle.yml", - "bundle.yaml", - ]; - for (const name of validFileNames) { - if (path.basename(resource) === name) { - return rootConfigSchemaUri; - } - } - return undefined; - }, - (uri: string) => { - // Any JSON schemas with URI scheme = "dabs" resolves here - const parsedUri = Uri.parse(uri); - if (parsedUri.scheme === dabsUriScheme) { - return bundleSchema; - } - } - ); - } -} diff --git a/packages/databricks-vscode/src/bundle/bundleAutocompleteProvider.ts b/packages/databricks-vscode/src/bundle/bundleAutocompleteProvider.ts new file mode 100644 index 000000000..e3676e7d2 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/bundleAutocompleteProvider.ts @@ -0,0 +1,65 @@ +import {CliWrapper} from "../cli/CliWrapper"; +import {ExtensionContext, extensions, Uri} from "vscode"; +import {BundleFileSet} from "./BundleFileSet"; +import {BundleWatcher} from "./BundleWatcher"; + +export async function registerBundleAutocompleteProvider( + cli: CliWrapper, + bundleFileSet: BundleFileSet, + bundleWatcher: BundleWatcher, + context: ExtensionContext +) { + // get freshly generated bundle schema + const bundleSchema = await cli.getBundleSchema(); + + // URI scheme for DABs JSON schemas + const dabsUriScheme = "dabs"; + + // URI for bundle root config json schema + const rootConfigSchemaUri = `${dabsUriScheme}:///databricks-asset-bundles.json`; + + const extensionYaml = extensions.getExtension("redhat.vscode-yaml"); + if (extensionYaml) { + const redHatYamlSchemaApi = await extensionYaml.activate(); + + // We use the API exposed from teh activate() function of the redhat.vscode-yaml + // extension to registor a custom schema provider + let bundleFileList = await bundleFileSet.allFiles(); + context.subscriptions.push( + bundleWatcher.onDidChangeRootFile(async () => { + bundleFileList = await bundleFileSet.allFiles(); + }), + bundleWatcher.onDidCreate(async (e) => { + bundleFileList.push(e); + }), + bundleWatcher.onDidDelete(async (e) => { + const idx = bundleFileList.findIndex( + (v) => v.fsPath === e.fsPath + ); + if (idx !== -1) { + bundleFileList.splice(idx, 1); + } + }) + ); + redHatYamlSchemaApi.registerContributor( + "dabs", + (resource: string) => { + const resourceUri = Uri.parse(resource); + if ( + bundleFileList.find( + (i) => i.fsPath === resourceUri.fsPath + ) !== undefined + ) { + return rootConfigSchemaUri; + } + }, + (uri: string) => { + // Any JSON schemas with URI scheme = "dabs" resolves here + const parsedUri = Uri.parse(uri); + if (parsedUri.scheme === dabsUriScheme) { + return bundleSchema; + } + } + ); + } +} diff --git a/packages/databricks-vscode/src/bundle/index.ts b/packages/databricks-vscode/src/bundle/index.ts new file mode 100644 index 000000000..116c9cd6a --- /dev/null +++ b/packages/databricks-vscode/src/bundle/index.ts @@ -0,0 +1,3 @@ +export {BundleWatcher} from "./BundleWatcher"; +export {BundleFileSet, parseBundleYaml, writeBundleYaml} from "./BundleFileSet"; +export {registerBundleAutocompleteProvider} from "./bundleAutocompleteProvider"; diff --git a/packages/databricks-vscode/src/bundle/models/BundlePreValidateModel.ts b/packages/databricks-vscode/src/bundle/models/BundlePreValidateModel.ts new file mode 100644 index 000000000..05cb6135f --- /dev/null +++ b/packages/databricks-vscode/src/bundle/models/BundlePreValidateModel.ts @@ -0,0 +1,160 @@ +import {Uri} from "vscode"; +import {BundleFileSet, BundleWatcher} from ".."; +import {BundleSchema, BundleTarget} from "../types"; +import {BaseModelWithStateCache} from "../../configuration/models/BaseModelWithStateCache"; +import {UrlUtils} from "../../utils"; +import {Mutex} from "../../locking"; +import * as lodash from "lodash"; +import {withOnErrorHandler} from "../../utils/onErrorDecorator"; + +export type BundlePreValidateState = { + host?: URL; + mode?: "development" | "staging" | "production"; + authParams?: Record; +} & BundleTarget & { + preValidateBundleSchema?: BundleSchema & { + variables: { + [k in keyof Required["variables"]]: + | Required["variables"][k] + | string; + }; + }; + }; + +/** + * Reads and writes bundle configs. This class does not notify when the configs change. + * We use the BundleWatcher to notify when the configs change. + */ +export class BundlePreValidateModel extends BaseModelWithStateCache { + protected mutex = new Mutex(); + private target: string | undefined; + + constructor( + private readonly bundleFileSet: BundleFileSet, + private readonly bunldeFileWatcher: BundleWatcher + ) { + super(); + this.disposables.push( + this.bunldeFileWatcher.onDidChange( + withOnErrorHandler( + async () => { + await this.stateCache.refresh(); + }, + {popup: false, log: true, throw: false} + ) + ) + ); + } + + get targets() { + return (async () => { + const bundle = await this.bundleFileSet.bundleDataCache.value; + const targets = Object.assign({}, bundle.targets ?? {}); + + Object.keys(targets ?? {}).map((key) => { + targets[key] = this.getRawTargetData(bundle, key); + }); + + return targets; + })(); + } + + get defaultTarget() { + return this.targets.then((targets) => { + if (targets === undefined) { + return undefined; + } + const defaultTarget = Object.keys(targets).find( + (target) => targets[target].default + ); + return defaultTarget; + }); + } + + public setTarget(target: string | undefined) { + this.target = target; + this.resetCache(); + } + + protected readStateFromTarget( + target?: BundleTarget + ): BundlePreValidateState | undefined { + return target + ? { + ...target, + host: UrlUtils.normalizeHost(target?.workspace?.host ?? ""), + mode: target?.mode as BundlePreValidateState["mode"], + authParams: undefined, + } + : undefined; + } + + private getRawTargetData(bundle: BundleSchema, target: string) { + const targetObject = Object.assign({}, bundle?.targets?.[target]); + const globalWorkspace = Object.assign({}, bundle?.workspace); + if (targetObject !== undefined) { + targetObject.workspace = lodash.merge( + globalWorkspace ?? {}, + targetObject.workspace + ); + } + return targetObject; + } + + protected async readState() { + if (this.target === undefined) { + return {}; + } + + const bundle = await this.bundleFileSet.bundleDataCache.value; + const targertData = + this.readStateFromTarget( + this.getRawTargetData(bundle, this.target) + ) ?? {}; + + return { + ...targertData, + preValidateBundleSchema: bundle, + }; + } + + public async getFileToWrite(key: string) { + const filesWithTarget: Uri[] = []; + const filesWithConfig = ( + await this.bundleFileSet.findFile(async (data, file) => { + const bundleTarget = data.targets?.[this.target ?? ""]; + if (bundleTarget === undefined) { + return false; + } + filesWithTarget.push(file); + + if (this.readStateFromTarget(bundleTarget) === undefined) { + return false; + } + return true; + }) + ).map((file) => file.file); + + if (filesWithConfig.length > 1) { + throw new Error( + `Multiple files found to write the config ${key} for target ${this.target}` + ); + } + + if (filesWithConfig.length === 0 && filesWithTarget.length === 0) { + throw new Error( + `No files found to write the config ${key} for target ${this.target}` + ); + } + + return [...filesWithConfig, ...filesWithTarget][0]; + } + + public resetCache(): void { + this.stateCache.set({}); + } + + public dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/bundle/models/BundleRemoteStateModel.ts b/packages/databricks-vscode/src/bundle/models/BundleRemoteStateModel.ts new file mode 100644 index 000000000..1a479f69e --- /dev/null +++ b/packages/databricks-vscode/src/bundle/models/BundleRemoteStateModel.ts @@ -0,0 +1,195 @@ +import {CliWrapper} from "../../cli/CliWrapper"; +import {BaseModelWithStateCache} from "../../configuration/models/BaseModelWithStateCache"; +import {Mutex} from "../../locking"; + +import {BundleTarget, Resource, ResourceKey, Resources} from "../types"; +import {AuthProvider} from "../../configuration/auth/AuthProvider"; +import lodash from "lodash"; +import {WorkspaceConfigs} from "../../vscode-objs/WorkspaceConfigs"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../../logger"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; +import {CancellationToken} from "vscode"; + +/* eslint-disable @typescript-eslint/naming-convention */ +export type BundleResourceModifiedStatus = "created" | "deleted" | "updated"; +export type BundleRemoteState = BundleTarget & { + resources?: Resources & { + [r in ResourceKey]?: { + [k in keyof Required>[r]]?: Resource< + BundleTarget, + r + > & { + id?: string; + modified_status?: BundleResourceModifiedStatus; + }; + }; + }; +}; + +/* eslint-enable @typescript-eslint/naming-convention */ +export function getResource( + key: string, + resources?: BundleRemoteState["resources"] +) { + return key.split(".").reduce((prev: any, k) => { + if (prev === undefined) { + return undefined; + } + return prev[k]; + }, resources ?? {}); +} + +export class BundleRemoteStateModel extends BaseModelWithStateCache { + public target: string | undefined; + public authProvider: AuthProvider | undefined; + protected mutex = new Mutex(); + private logger = logging.NamedLogger.getOrCreate(Loggers.Bundle); + + get workspaceFolder() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private readonly cli: CliWrapper, + private readonly workspaceFolderManager: WorkspaceFolderManager, + private readonly workspaceConfigs: WorkspaceConfigs + ) { + super(); + } + + @Mutex.synchronise("mutex") + public async refresh() { + return await this.stateCache.refresh(); + } + + @Mutex.synchronise("mutex") + public async deploy(force = false, token?: CancellationToken) { + if (this.target === undefined) { + throw new Error("Target is undefined"); + } + if (this.authProvider === undefined) { + throw new Error("No authentication method is set"); + } + + await this.cli.bundleDeploy( + this.target, + this.authProvider, + this.workspaceFolder, + this.workspaceConfigs.databrickscfgLocation, + this.logger, + force, + token + ); + } + + @Mutex.synchronise("mutex") + public async destroy(force = false, token: CancellationToken) { + if (this.target === undefined) { + throw new Error("Target is undefined"); + } + if (this.authProvider === undefined) { + throw new Error("No authentication method is set"); + } + + await this.cli.bundleDestroy( + this.target, + this.authProvider, + this.workspaceFolder, + this.workspaceConfigs.databrickscfgLocation, + this.logger, + force, + token + ); + } + + @Mutex.synchronise("mutex") + public async sync(token: CancellationToken) { + if (this.target === undefined) { + throw new Error("Target is undefined"); + } + if (this.authProvider === undefined) { + throw new Error("No authentication method is set"); + } + + await this.cli.bundleSync( + this.target, + this.authProvider, + this.workspaceFolder, + this.workspaceConfigs.databrickscfgLocation, + this.logger, + token + ); + } + + public async getRunCommand(resourceKey: string) { + if (this.target === undefined) { + throw new Error("Target is undefined"); + } + if (this.authProvider === undefined) { + throw new Error("No authentication method is set"); + } + + return await this.cli.getBundleRunCommand( + this.target, + this.authProvider, + resourceKey, + this.workspaceFolder, + this.workspaceConfigs.databrickscfgLocation + ); + } + + public setTarget(target: string | undefined) { + if (this.target === target) { + return; + } + this.target = target; + this.resetCache(); + this.authProvider = undefined; + } + + public setAuthProvider(authProvider: AuthProvider | undefined) { + if ( + !lodash.isEqual(this.authProvider?.toJSON(), authProvider?.toJSON()) + ) { + this.authProvider = authProvider; + } + } + + protected async readState(): Promise { + if (this.target === undefined || this.authProvider === undefined) { + return {}; + } + + const {stdout} = await this.cli.bundleSummarise( + this.target, + this.authProvider, + this.workspaceFolder, + this.workspaceConfigs.databrickscfgLocation, + this.logger + ); + + if (stdout === "" || stdout === undefined) { + return {}; + } + return JSON.parse(stdout); + } + + /** + * @param key dot separated string that uniquely identifies a resource in the nested resources object + */ + async getResource(key: string) { + const resources = await this.get("resources"); + return key.split(".").reduce((prev: any, k) => { + return prev[k]; + }, resources); + } + + public resetCache(): void { + this.stateCache.set({}); + } + + dispose() { + super.dispose(); + } +} diff --git a/packages/databricks-vscode/src/bundle/models/BundleValidateModel.ts b/packages/databricks-vscode/src/bundle/models/BundleValidateModel.ts new file mode 100644 index 000000000..e958b84c4 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/models/BundleValidateModel.ts @@ -0,0 +1,101 @@ +import {BundleWatcher} from "../BundleWatcher"; +import {AuthProvider} from "../../configuration/auth/AuthProvider"; +import {Mutex} from "../../locking"; +import {CliWrapper} from "../../cli/CliWrapper"; +import {BundleTarget} from "../types"; +import lodash from "lodash"; +import {workspaceConfigs} from "../../vscode-objs/WorkspaceConfigs"; +import {BaseModelWithStateCache} from "../../configuration/models/BaseModelWithStateCache"; +import {withOnErrorHandler} from "../../utils/onErrorDecorator"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../../logger"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; + +export type BundleValidateState = { + clusterId?: string; + remoteRootPath?: string; +} & BundleTarget; + +export class BundleValidateModel extends BaseModelWithStateCache { + public target: string | undefined; + public authProvider: AuthProvider | undefined; + protected mutex = new Mutex(); + protected logger = logging.NamedLogger.getOrCreate(Loggers.Bundle); + + constructor( + private readonly bundleWatcher: BundleWatcher, + private readonly cli: CliWrapper, + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + super(); + this.disposables.push( + this.bundleWatcher.onDidChange( + withOnErrorHandler( + async () => { + await this.stateCache.refresh(); + }, + {log: true, throw: false} + ) + ) + ); + } + + public async refresh() { + await this.stateCache.refresh(); + } + + public setTarget(target: string | undefined) { + if (this.target === target) { + return; + } + this.target = target; + this.resetCache(); + this.authProvider = undefined; + } + + public setAuthProvider(authProvider: AuthProvider | undefined) { + if ( + !lodash.isEqual(this.authProvider?.toJSON(), authProvider?.toJSON()) + ) { + this.authProvider = authProvider; + } + } + + protected async readState(): Promise { + if ( + !this.target || + !this.authProvider || + !this.workspaceFolderManager.activeWorkspaceFolder + ) { + return {}; + } + + const validateOutput = JSON.parse( + ( + await this.cli.bundleValidate( + this.target, + this.authProvider, + this.workspaceFolderManager.activeWorkspaceFolder?.uri, + workspaceConfigs.databrickscfgLocation, + this.logger + ) + ).stdout + ) as BundleTarget; + + return { + clusterId: + validateOutput?.bundle?.compute_id ?? + validateOutput?.bundle?.cluster_id, + remoteRootPath: validateOutput?.workspace?.file_path, + ...validateOutput, + }; + } + + public resetCache(): void { + this.stateCache.set({}); + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/bundle/models/BundleVariableModel.ts b/packages/databricks-vscode/src/bundle/models/BundleVariableModel.ts new file mode 100644 index 000000000..a0f215047 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/models/BundleVariableModel.ts @@ -0,0 +1,256 @@ +import {Uri, FileSystemWatcher, workspace, window} from "vscode"; +import {BaseModelWithStateCache} from "../../configuration/models/BaseModelWithStateCache"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {Mutex} from "../../locking"; +import {BundleSchema} from "../types"; +import {readFile} from "fs/promises"; +import {NamedLogger} from "@databricks/databricks-sdk/dist/logging"; +import {Loggers} from "../../logger"; +import {onError} from "../../utils/onErrorDecorator"; +import {BundleValidateModel} from "./BundleValidateModel"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; + +export type BundleVariable = Required["variables"][string] & { + valueInTarget?: string; + vscodeOverrideValue?: string; +}; + +export type BundleVariableModelState = { + variables?: Record; +}; + +export class BundleVariableModel extends BaseModelWithStateCache { + protected mutex: Mutex = new Mutex(); + private target: string | undefined; + private overrideFileWatcher: FileSystemWatcher | undefined; + + get workspaceRoot() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private readonly configModel: ConfigModel, + private readonly bundleValidateModel: BundleValidateModel, + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + super(); + this.disposables.push( + this.configModel.onDidChangeKey("validateConfig")(async () => { + await this.stateCache.refresh(); + }), + this.configModel.onDidChangeKey("preValidateConfig")(async () => { + await this.stateCache.refresh(); + }), + this.configModel.onDidChangeTarget(async () => { + this.setTarget(this.configModel.target); + }), + this.onDidChangeKey("variables")(async () => { + await this.writeFile(); + }) + ); + } + + public async writeFile() { + if (this.bundleVariableFilePath === undefined) { + return; + } + + await workspace.fs.writeFile( + this.bundleVariableFilePath, + Buffer.from(await this.getFileContent(), "utf8") + ); + } + public resetCache(): void { + this.stateCache.set({variables: {}}); + } + setTarget(target: string | undefined) { + if (this.target === target) { + return; + } + + this.target = target; + this.resetCache(); + + if (this.target === undefined) { + this.overrideFileWatcher?.dispose(); + this.overrideFileWatcher = undefined; + return; + } + + this.overrideFileWatcher = workspace.createFileSystemWatcher( + this.bundleVariableFilePath!.fsPath + ); + + this.disposables.push( + this.overrideFileWatcher, + this.overrideFileWatcher.onDidChange(async () => { + await this.bundleValidateModel.refresh(); + await this.stateCache.refresh(); + }), + this.overrideFileWatcher.onDidCreate(async () => { + await this.bundleValidateModel.refresh(); + await this.stateCache.refresh(); + }), + this.overrideFileWatcher.onDidDelete(async () => { + await this.bundleValidateModel.refresh(); + await this.stateCache.refresh(); + }) + ); + } + + get bundleVariableFilePath() { + const target = this.configModel.target; + if (target === undefined) { + return undefined; + } + + return Uri.joinPath( + this.workspaceRoot, + ".databricks", + "bundle", + target, + "vscode.bundlevars.json" + ).with({scheme: "file"}); + } + + private async getVariableOverrides(): Promise< + Record + > { + if (this.bundleVariableFilePath === undefined) { + return {}; + } + + try { + const rawData: Record = JSON.parse( + await readFile(this.bundleVariableFilePath.fsPath, "utf-8") + ); + + return Object.fromEntries( + Object.entries(rawData) + .map(([key, value]) => { + if (value.length === 0) { + return [key, undefined]; + } + return [key, value]; + }) + .filter((v) => v[1] !== undefined) + ); + } catch (e: any) { + NamedLogger.getOrCreate(Loggers.Extension).debug( + "No bundle variable overrides found.", + e + ); + return {}; + } + } + + protected async readState(): Promise { + const preValidateConfig = + await this.configModel.get("preValidateConfig"); + + // If no global variables are defined, return an empty map + if (preValidateConfig === undefined) { + return {}; + } + + const globalVariableDefinitions = + preValidateConfig.preValidateBundleSchema?.variables ?? {}; + const inTargetVariables = preValidateConfig.variables ?? {}; + const overrides = await this.getVariableOverrides(); + const inTargetPostValidateVariables = + (await this.configModel.get("validateConfig"))?.variables ?? {}; + + const variables: Record = {}; + + for (const key of Object.keys(globalVariableDefinitions)) { + let definition = globalVariableDefinitions[key]; + if (typeof definition === "string") { + definition = {default: definition}; + } + const inTargetVariable = inTargetVariables[key]; + + // We check heuristically if the vairable is required, because bundle validate does not work if + // a required variable is not set. + const isRequired = + (inTargetVariable ?? + definition.lookup ?? + definition.default) === undefined; + + variables[key] = { + ...definition, + lookup: + typeof inTargetVariable?.lookup === "object" + ? inTargetVariable.lookup + : definition.lookup, + + // If the value is not required based on our heuristic check, we use the value from the validate + // command. + valueInTarget: + typeof inTargetVariable === "string" + ? inTargetVariable + : isRequired + ? undefined + : inTargetPostValidateVariables[key]?.value ?? + definition.default, + vscodeOverrideValue: overrides[key], + }; + } + + return {variables: variables}; + } + + async getEnvVariables(): Promise> { + const overrides = await this.getVariableOverrides(); + return Object.fromEntries( + Object.entries(overrides) + .filter(([key]) => overrides[key] !== undefined) + .map(([key, value]) => [`BUNDLE_VAR_${key}`, value]) + ) as Record; + } + + async getFileContent() { + const variables = await this.getVariableOverrides(); + return JSON.stringify( + Object.fromEntries( + Object.entries(variables) + .filter((v) => v[1] !== undefined) + .map(([key, value]) => [key, value ?? ""]) + ), + null, + 4 + ); + } + + async openBundleVariableFile() { + if (this.bundleVariableFilePath === undefined) { + window.showErrorMessage( + "Unable to open bundle variable file. No target selected." + ); + return; + } + + await this.writeFile(); + const doc = await workspace.openTextDocument( + this.bundleVariableFilePath + ); + await window.showTextDocument(doc); + } + + @onError({ + log: true, + popup: {prefix: "Error deleting bundle variable file."}, + }) + async deleteBundleVariableFile() { + if (this.bundleVariableFilePath === undefined) { + return; + } + + try { + await workspace.fs.delete(this.bundleVariableFilePath); + } catch (e: any) { + if (e.code !== "ENOENT" && e.code !== "FileNotFound") { + throw e; + } + } + } +} diff --git a/packages/databricks-vscode/src/bundle/run/BundleRunStatus.ts b/packages/databricks-vscode/src/bundle/run/BundleRunStatus.ts new file mode 100644 index 000000000..f229ceef9 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/BundleRunStatus.ts @@ -0,0 +1,32 @@ +import {EventEmitter} from "vscode"; +import {RunState} from "./types"; +import {ResourceKey} from "../types"; +import {BundleRemoteState} from "../models/BundleRemoteStateModel"; +import {Time, TimeUnits} from "@databricks/databricks-sdk"; +export abstract class BundleRunStatus { + abstract readonly type: ResourceKey; + protected readonly onDidChangeEmitter = new EventEmitter(); + readonly onDidChange = this.onDidChangeEmitter.event; + runId: string | undefined; + data: any; + + constructor() { + // Timeout in 60 seconds if we don't have a runId till then. + setTimeout(() => { + if (this.runState === "unknown") { + this.runState = "timeout"; + } + }, new Time(60, TimeUnits.seconds).toMillSeconds().value); + } + protected _runState: RunState = "unknown"; + public get runState(): RunState { + return this._runState; + } + public set runState(value: RunState) { + this._runState = value; + this.onDidChangeEmitter.fire(); + } + + abstract parseId(output: string): void; + abstract cancel(): Promise; +} diff --git a/packages/databricks-vscode/src/bundle/run/BundleRunStatusManager.ts b/packages/databricks-vscode/src/bundle/run/BundleRunStatusManager.ts new file mode 100644 index 000000000..557765b59 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/BundleRunStatusManager.ts @@ -0,0 +1,129 @@ +import {Disposable, EventEmitter} from "vscode"; +import {BundleRemoteState, getResource} from "../models/BundleRemoteStateModel"; +import {BundleRunTerminalManager} from "./BundleRunTerminalManager"; +import {JobRunStatus} from "./JobRunStatus"; +import {AuthProvider} from "../../configuration/auth/AuthProvider"; +import {BundleRunStatus} from "./BundleRunStatus"; +import {PipelineRunStatus} from "./PipelineRunStatus"; +import {Resource, ResourceKey} from "../types"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../../logger"; +/** + * This class monitors the cli bundle run output and record ids for runs. It also polls for status of the these runs. + */ +export class BundleRunStatusManager implements Disposable { + private logger = logging.NamedLogger.getOrCreate(Loggers.Extension); + private disposables: Disposable[] = []; + public readonly runStatuses: Map = new Map(); + + private readonly onDidChangeEmitter = new EventEmitter(); + readonly onDidChange = this.onDidChangeEmitter.event; + + constructor( + private readonly configModel: ConfigModel, + private readonly bundleRunTerminalManager: BundleRunTerminalManager + ) { + this.disposables.push( + this.configModel.onDidChangeTarget(() => { + this.runStatuses.clear(); + this.onDidChangeEmitter.fire(); + }) + ); + } + + getRunStatusMonitor( + resourceKey: string, + resourceType: ResourceKey, + authProvider: AuthProvider, + resource: any + ): BundleRunStatus { + switch (resourceType) { + case "jobs": + return new JobRunStatus(authProvider); + case "pipelines": { + const id = ( + resource as Resource + ).id; + if (id === undefined) { + throw new Error( + `Pipeline id is undefined for ${resourceKey}. This likely means the pipeline is not deployed.` + ); + } + + return new PipelineRunStatus(authProvider, id); + } + default: + throw new Error(`Unknown resource type ${resourceType}`); + } + } + + async run( + resourceKey: string, + resourceType: ResourceKey + ) { + const target = this.configModel.target; + const authProvider = this.configModel.authProvider; + const resource = getResource( + resourceKey, + (await this.configModel.get("remoteStateConfig"))?.resources + ); + + if (target === undefined) { + throw new Error(`Cannot run ${resourceKey}, Target is undefined`); + } + if (authProvider === undefined) { + throw new Error( + `Cannot run ${resourceKey}, AuthProvider is undefined` + ); + } + if (resource === undefined) { + throw new Error( + `Cannot run ${resourceKey}, Resource is not deployed` + ); + } + + const remoteRunStatus = this.getRunStatusMonitor( + resourceKey, + resourceType, + authProvider, + resource + ); + this.runStatuses.set(resourceKey, remoteRunStatus); + this.disposables.push( + remoteRunStatus.onDidChange(() => { + this.onDidChangeEmitter.fire(); + }) + ); + this.onDidChangeEmitter.fire(); + try { + const result = await this.bundleRunTerminalManager.run( + resourceKey, + (data) => remoteRunStatus.parseId(data) + ); + if (result.cancelled) { + await remoteRunStatus.cancel(); + } + return result; + } catch (e) { + // In the case of a failed run cancellation is expected to fail too. + // Because of it we catch errors from the `cancel` and log them, re-throwing original error that will be shown to the user. + await remoteRunStatus.cancel().catch((error) => { + this.logger.error( + "Error while cancelling a run after a failure", + error + ); + }); + remoteRunStatus.runState = "error"; + throw e; + } + } + + async cancel(resourceKey: string) { + this.bundleRunTerminalManager.cancel(resourceKey); + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/bundle/run/BundleRunTerminalManager.ts b/packages/databricks-vscode/src/bundle/run/BundleRunTerminalManager.ts new file mode 100644 index 000000000..bce3bc628 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/BundleRunTerminalManager.ts @@ -0,0 +1,144 @@ +import {CancellationTokenSource, Disposable, Terminal, window} from "vscode"; +import {BundleRemoteStateModel} from "../models/BundleRemoteStateModel"; +import {CustomOutputTerminal} from "./CustomOutputTerminal"; + +export class BundleRunTerminalManager implements Disposable { + private disposables: Disposable[] = []; + private terminalDetails: Map< + string, + { + terminal: Terminal; + pty: CustomOutputTerminal; + } + > = new Map(); + + private cancellationTokenSources: Map = + new Map(); + + constructor( + private readonly bundleRemoteStateModel: BundleRemoteStateModel + ) {} + + getTerminalName(target: string, resourceKey: string) { + return `Run ${resourceKey} (${target})`; + } + + async run( + resourceKey: string, + onDidUpdate?: (data: string) => void + ): Promise<{cancelled: boolean; exitCode?: number | null}> { + const target = this.bundleRemoteStateModel.target; + if (target === undefined) { + throw new Error(`Cannot run ${resourceKey}, Target is undefined`); + } + const terminalName = this.getTerminalName(target, resourceKey); + + if (!this.terminalDetails.has(terminalName)) { + this.terminalDetails.set( + terminalName, + this.createTerminal(terminalName) + ); + } + let terminal = this.terminalDetails.get(terminalName)!; + + const disposables: Disposable[] = []; + try { + terminal.terminal.show(); + if ( + window.terminals.find( + (i) => i.name === terminal?.terminal.name + ) === undefined + ) { + // The terminal has been closed. Recreate everything. + terminal = this.createTerminal(terminalName); + this.terminalDetails.set(terminalName, terminal); + } + if (terminal.pty.process !== undefined) { + // There is already a process running. Raise error + throw new Error( + `Process already running. Pid: ${terminal.pty.process.pid}` + ); + } + + const cancellationTokenSource = new CancellationTokenSource(); + this.cancellationTokenSources.set( + terminalName, + cancellationTokenSource + ); + const onCancellationEvent = + cancellationTokenSource.token.onCancellationRequested(() => { + terminal?.pty.close(); + //Dispose self on cancellation + onCancellationEvent.dispose(); + }, this.disposables); + + const cmd = + await this.bundleRemoteStateModel.getRunCommand(resourceKey); + + // spawn a new process with the latest command, in the same terminal. + terminal.pty.spawn(cmd); + terminal.terminal.show(); + + disposables.push( + terminal.pty.onDidWrite((data) => { + onDidUpdate?.(data); + }) + ); + + // Wait for the process to exit + return await new Promise((resolve, reject) => { + terminal.pty.onDidCloseProcess((exitCode) => { + if (exitCode === 0 || terminal.pty.isClosed) { + // Resolve when the process exits with code 0 or is closed by human action + resolve({cancelled: terminal.pty.isClosed, exitCode}); + } else { + reject( + new Error(`Process exited with code ${exitCode}`) + ); + } + }, disposables); + }); + } finally { + disposables.forEach((i) => i.dispose()); + + this.cancellationTokenSources.get(terminalName)?.cancel(); + this.cancellationTokenSources.get(terminalName)?.dispose(); + this.cancellationTokenSources.delete(terminalName); + } + } + + createTerminal(terminalName: string) { + const pty = new CustomOutputTerminal(); + const terminal = { + pty, + terminal: window.createTerminal({ + name: terminalName, + pty, + isTransient: true, + }), + }; + + this.disposables.push(terminal.terminal); + return terminal; + } + + cancel(resourceKey: string) { + const target = this.bundleRemoteStateModel.target; + if (target === undefined) { + throw new Error( + `Cannot delete ${resourceKey}, Target is undefined` + ); + } + + const terminalName = this.getTerminalName(target, resourceKey); + window.terminals.find((i) => i.name === terminalName)?.show(); + + this.cancellationTokenSources.get(terminalName)?.cancel(); + this.cancellationTokenSources.get(terminalName)?.dispose(); + this.cancellationTokenSources.delete(terminalName); + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/bundle/run/CustomOutputTerminal.ts b/packages/databricks-vscode/src/bundle/run/CustomOutputTerminal.ts new file mode 100644 index 000000000..7d31cf8c2 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/CustomOutputTerminal.ts @@ -0,0 +1,102 @@ +import {ChildProcess, SpawnOptions, spawn} from "child_process"; +import {quote} from "shell-quote"; +import {Pseudoterminal, Event, EventEmitter} from "vscode"; + +export class CustomOutputTerminal implements Pseudoterminal { + /** Is the terminal closed by user action */ + public isClosed = false; + private writeEmitter = new EventEmitter(); + onDidWrite: Event = this.writeEmitter.event; + + private closeEmitter = new EventEmitter(); + onDidClose: Event = this.closeEmitter.event; + + private onDidCloseProcessEmitter = new EventEmitter(); + onDidCloseProcess: Event = + this.onDidCloseProcessEmitter.event; + + private _process: ChildProcess | undefined; + public get process(): ChildProcess | undefined { + return this._process; + } + + constructor() {} + + open(): void {} + + spawn({ + cmd, + args, + options, + }: { + cmd: string; + args: string[]; + options: SpawnOptions; + }): void { + this.isClosed = false; + this.writeEmitter.fire("\x1b[2J\x1b[H\r\n"); + this.writeEmitter.fire(quote([cmd, ...args]) + "\r\n\r\n"); + + this._process = spawn(cmd, args, options); + if (!this.process) { + throw new Error("Can't start process: process is undefined"); + } + + if (!this.process.stderr) { + throw new Error("Can't start process: can't pipe stderr process"); + } + + if (!this.process.stdout) { + throw new Error("Can't start process: can't pipe stdout process"); + } + + const handleOutput = (data: Buffer) => { + let dataStr = data.toString(); + dataStr = dataStr.replaceAll("\n", "\r\n"); + if (!dataStr.endsWith("\r\n")) { + dataStr = dataStr + "\r\n"; + } + this.writeEmitter.fire(dataStr); + }; + this.process.stdout.on("data", handleOutput); + this.process.stderr.on("data", handleOutput); + + this.process.on("close", async (exitCode) => { + if (exitCode === 0) { + this.writeEmitter.fire( + "\x1b[32mProcess completed successfully\x1b[0m\r\n" + ); + } + + if (exitCode !== 0 && exitCode !== null) { + this.writeEmitter.fire( + "\x1b[31mProcess exited with code " + + exitCode + + "\x1b[0m\r\n" + ); + // Wait for 2 seconds to let the error rendering finish + await new Promise((resolve) => setTimeout(resolve, 2000)); + } + + this.onDidCloseProcessEmitter.fire(exitCode); + this._process = undefined; + }); + + this.process.on("error", (err) => { + this.writeEmitter.fire("\x1b[31m" + err.message + "\x1b[0m\r\n"); + this.writeEmitter.fire( + "\x1b[31m" + (err.stack ?? "") + "\x1b[0m\r\n" + ); + }); + } + + close(): void { + this.isClosed = true; + if (this.process !== undefined) { + this.writeEmitter.fire( + "\x1b[31mProcess killed by user input\x1b[0m\r\n" + ); + } + this.process?.kill(); + } +} diff --git a/packages/databricks-vscode/src/bundle/run/JobRunStatus.ts b/packages/databricks-vscode/src/bundle/run/JobRunStatus.ts new file mode 100644 index 000000000..618ed4050 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/JobRunStatus.ts @@ -0,0 +1,79 @@ +/* eslint-disable @typescript-eslint/naming-convention */ +import { + JobsError, + JobsRetriableError, + Run, +} from "@databricks/databricks-sdk/dist/apis/jobs"; +import {Event, EventEmitter} from "vscode"; +import {AuthProvider} from "../../configuration/auth/AuthProvider"; +import {onError} from "../../utils/onErrorDecorator"; +import {BundleRunStatus} from "./BundleRunStatus"; + +export class JobRunStatus extends BundleRunStatus { + readonly type = "jobs"; + data: Run | undefined; + private readonly onDidCompleteEmitter = new EventEmitter(); + onDidComplete: Event = this.onDidCompleteEmitter.event; + + constructor(private readonly authProvider: AuthProvider) { + super(); + } + + parseId(output: string) { + if (this.runId !== undefined || this.runState !== "unknown") { + return; + } + const match = output.match(/.*\/run\/(\d*).*/); + if (match === null) { + return; + } + this.runId = match[1]; + + this.startPolling(); + } + + @onError({popup: {prefix: "Failed to check the run status for the job."}}) + private async startPolling() { + if (this.runState !== "unknown") { + return; + } + + if (this.runId === undefined) { + throw new Error("No run id found"); + } + + const client = await this.authProvider.getWorkspaceClient(); + try { + this.runState = "running"; + await ( + await client.jobs.getRun({run_id: parseInt(this.runId)}) + ).wait({ + onProgress: async (progress) => { + this.data = progress; + this.onDidChangeEmitter.fire(); + }, + }); + } catch (e) { + this.runState = "error"; + if (e instanceof JobsError || e instanceof JobsRetriableError) { + // On progress is already fired for these status updates. We let the listeners handle it. + return; + } + throw e; + } + this.runState = "completed"; + } + + async cancel(): Promise { + if (this.runId === undefined || this.runState !== "running") { + this.runState = "cancelled"; + return; + } + + const client = await this.authProvider.getWorkspaceClient(); + await ( + await client.jobs.cancelRun({run_id: parseInt(this.runId)}) + ).wait(); + this.runState = "cancelled"; + } +} diff --git a/packages/databricks-vscode/src/bundle/run/PipelineRunStatus.ts b/packages/databricks-vscode/src/bundle/run/PipelineRunStatus.ts new file mode 100644 index 000000000..6beece33d --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/PipelineRunStatus.ts @@ -0,0 +1,122 @@ +/* eslint-disable @typescript-eslint/naming-convention */ +import {BundleRunStatus} from "./BundleRunStatus"; +import {AuthProvider} from "../../configuration/auth/AuthProvider"; +import {onError} from "../../utils/onErrorDecorator"; +import {pipelines} from "@databricks/databricks-sdk"; + +function isRunning(status?: pipelines.UpdateInfoState) { + if (status === undefined) { + return false; + } + return !["COMPLETED", "FAILED", "CANCELED"].includes(status); +} + +export class PipelineRunStatus extends BundleRunStatus { + readonly type = "pipelines"; + private interval?: NodeJS.Timeout; + data: pipelines.GetUpdateResponse | undefined; + constructor( + private readonly authProvider: AuthProvider, + private readonly pipelineId: string + ) { + super(); + } + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + parseId(output: string): void { + if (this.runId !== undefined || this.runState !== "unknown") { + return; + } + output = output.trim(); + const match = output.match(/.*https:\/\/.*\/updates\/(.*)$/); + if (match === null) { + return; + } + this.runId = match[1]; + + this.startPolling(); + } + + @onError({ + popup: {prefix: "Failed to check the run status for the pipeline."}, + }) + private async startPolling() { + if (this.runState !== "unknown") { + return; + } + + if (this.runId === undefined) { + throw new Error("No update id"); + } + + const client = await this.authProvider.getWorkspaceClient(); + this.runState = "running"; + + this.interval = setInterval(async () => { + try { + if (this.runId === undefined) { + throw new Error("No update id"); + } + const update = await client.pipelines.getUpdate({ + pipeline_id: this.pipelineId, + update_id: this.runId, + }); + this.data = update; + + // If update is completed, we stop polling. + if (!isRunning(update.update?.state)) { + this.markCompleted(); + return; + } + + this.onDidChangeEmitter.fire(); + } catch (e) { + this.runState = "error"; + throw e; + } + }, 5_000); + } + + private markCompleted() { + if (this.interval !== undefined) { + clearInterval(this.interval); + this.interval = undefined; + } + this.runState = "completed"; + } + + private markCancelled() { + if (this.interval !== undefined) { + clearInterval(this.interval); + this.interval = undefined; + } + this.runState = "cancelled"; + } + + async cancel() { + if (this.runState !== "running" || this.runId === undefined) { + this.markCancelled(); + return; + } + + const client = await this.authProvider.getWorkspaceClient(); + const update = await client.pipelines.getUpdate({ + pipeline_id: this.pipelineId, + update_id: this.runId, + }); + // Only stop the pipeline if the tracked update is still running. The stop API stops the + // latest update, which might not be the tracked update. + if (isRunning(update.update?.state)) { + await ( + await client.pipelines.stop({ + pipeline_id: this.pipelineId, + }) + ).wait(); + } + this.data = await client.pipelines.getUpdate({ + pipeline_id: this.pipelineId, + update_id: this.runId, + }); + this.markCancelled(); + } +} diff --git a/packages/databricks-vscode/src/bundle/run/types.ts b/packages/databricks-vscode/src/bundle/run/types.ts new file mode 100644 index 000000000..07cba9de7 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/run/types.ts @@ -0,0 +1,7 @@ +export type RunState = + | "running" + | "completed" + | "unknown" + | "error" + | "timeout" + | "cancelled"; diff --git a/packages/databricks-vscode/src/bundle/types.ts b/packages/databricks-vscode/src/bundle/types.ts new file mode 100644 index 000000000..e1bd8e445 --- /dev/null +++ b/packages/databricks-vscode/src/bundle/types.ts @@ -0,0 +1,22 @@ +import {BundleSchema as OriginalBundleSchema} from "./BundleSchema"; + +type RemoveStringFromUnion = T extends string ? never : T; +type RemoveStringFromUnionTypes = T extends object + ? { + [K in keyof T]: T[K] extends string | undefined + ? T[K] + : RemoveStringFromUnionTypes; + } + : RemoveStringFromUnion; + +// CLI generates schema with additional string types added for almost complex sub types (to support complex variables). +// We usually work with `bundle validate` or `summary` outputs, which have expanded variables, so we don't need +// to account for additional string types. +export type BundleSchema = RemoveStringFromUnionTypes; +export type BundleTarget = Required["targets"][string]; + +export type Resources = T extends {resources?: infer D} ? D : never; +export type ResourceKey = keyof Resources; +export type Resource> = Required< + Resources +>[K][keyof Required>[K]]; diff --git a/packages/databricks-vscode/src/cli/CliWrapper.test.ts b/packages/databricks-vscode/src/cli/CliWrapper.test.ts index a1e5e925f..d2a6b5508 100644 --- a/packages/databricks-vscode/src/cli/CliWrapper.test.ts +++ b/packages/databricks-vscode/src/cli/CliWrapper.test.ts @@ -1,27 +1,31 @@ import * as assert from "assert"; import {Uri} from "vscode"; -import { - LocalUri, - RemoteUri, - SyncDestinationMapper, -} from "../sync/SyncDestination"; import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {promisify} from "node:util"; import {execFile as execFileCb} from "node:child_process"; import {withFile} from "tmp-promise"; import {writeFile, readFile} from "node:fs/promises"; -import {when, spy, reset} from "ts-mockito"; -import {CliWrapper} from "./CliWrapper"; +import {when, spy, reset, instance, mock} from "ts-mockito"; +import {CliWrapper, waitForProcess} from "./CliWrapper"; import path from "node:path"; import os from "node:os"; import crypto from "node:crypto"; import {Context} from "@databricks/databricks-sdk/dist/context"; import {logging} from "@databricks/databricks-sdk"; +import {LoggerManager} from "../logger"; +import {ProfileAuthProvider} from "../configuration/auth/AuthProvider"; +import {isMatch} from "lodash"; +import {removeUndefinedKeys} from "../utils/envVarGenerators"; import {writeFileSync} from "fs"; +import {ChildProcess, ChildProcessWithoutNullStreams} from "child_process"; +import {Readable} from "stream"; const execFile = promisify(execFileCb); const cliPath = path.join(__dirname, "../../bin/databricks"); +// eslint-disable-next-line @typescript-eslint/no-var-requires +const extensionVersion = require("../../package.json").version; + function getTempLogFilePath() { return path.join( os.tmpdir(), @@ -36,11 +40,14 @@ function createCliWrapper(logFilePath?: string) { return path.join(__dirname, "../..", relativePath); }, } as any, + instance(mock(LoggerManager)), logFilePath ); } -describe(__filename, () => { +describe(__filename, function () { + this.timeout("10s"); + it("should embed a working databricks CLI", async () => { const result = await execFile(cliPath, ["--help"]); assert.ok(result.stdout.indexOf("databricks") > 0); @@ -58,7 +65,7 @@ describe(__filename, () => { mocks.push(configsSpy); when(configsSpy.loggingEnabled).thenReturn(true); const cli = createCliWrapper(logFilePath); - await execFile(cli.cliPath, ["version", ...cli.loggingArguments]); + await execFile(cli.cliPath, ["version", ...cli.getLoggingArguments()]); const file = await readFile(logFilePath); // Just checking if the file is not empty to avoid depending on internal CLI log patterns assert.ok(file.toString().length > 0); @@ -67,25 +74,16 @@ describe(__filename, () => { it("should create sync commands", async () => { const logFilePath = getTempLogFilePath(); const cli = createCliWrapper(logFilePath); - const mapper = new SyncDestinationMapper( - new LocalUri(Uri.file("/user/project")), - new RemoteUri( - Uri.from({ - scheme: "wsfs", - path: "/Repos/user@databricks.com/project", - }) - ) - ); - const syncCommand = `${cliPath} sync . /Repos/user@databricks.com/project --watch --output json`; + const syncCommand = `${cliPath} bundle sync --watch --output json`; const loggingArgs = `--log-level debug --log-file ${logFilePath} --log-format json`; - let {command, args} = cli.getSyncCommand(mapper, "incremental"); + let {command, args} = cli.getSyncCommand("incremental"); assert.equal( [command, ...args].join(" "), [syncCommand, loggingArgs].join(" ") ); - ({command, args} = cli.getSyncCommand(mapper, "full")); + ({command, args} = cli.getSyncCommand("full")); assert.equal( [command, ...args].join(" "), [syncCommand, loggingArgs, "--full"].join(" ") @@ -94,24 +92,10 @@ describe(__filename, () => { const configsSpy = spy(workspaceConfigs); mocks.push(configsSpy); when(configsSpy.loggingEnabled).thenReturn(false); - ({command, args} = cli.getSyncCommand(mapper, "incremental")); + ({command, args} = cli.getSyncCommand("incremental")); assert.equal([command, ...args].join(" "), syncCommand); }); - it("should create an 'add profile' command", () => { - const cli = createCliWrapper(); - - const {command, args} = cli.getAddProfileCommand( - "DEFAULT", - new URL("https://databricks.com") - ); - - assert.equal( - [command, ...args].join(" "), - `${cliPath} configure --no-interactive --profile DEFAULT --host https://databricks.com/ --token` - ); - }); - it("should list profiles when no config file exists", async () => { const logFilePath = getTempLogFilePath(); const cli = createCliWrapper(logFilePath); @@ -218,4 +202,75 @@ nothing = true assert.equal(profiles.length, 0); }); }); + + it("should set required env vars to the bundle run CLI calls", async () => { + const logFilePath = getTempLogFilePath(); + const cli = createCliWrapper(logFilePath); + const authProvider = new ProfileAuthProvider( + new URL("https://test.com"), + "PROFILE", + cli, + true + ); + const workspaceFolder = Uri.file("/test/123"); + const runCmd = await cli.getBundleRunCommand( + "dev", + authProvider, + "resource-key", + workspaceFolder + ); + const expected = { + args: ["bundle", "run", "--target", "dev", "resource-key"], + cmd: cli.cliPath, + options: { + cwd: workspaceFolder.fsPath, + env: removeUndefinedKeys({ + /* eslint-disable @typescript-eslint/naming-convention */ + DATABRICKS_CLI_UPSTREAM: "databricks-vscode", + DATABRICKS_CLI_UPSTREAM_VERSION: extensionVersion, + DATABRICKS_CONFIG_PROFILE: "PROFILE", + DATABRICKS_HOST: "https://test.com/", + DATABRICKS_LOG_FILE: logFilePath, + DATABRICKS_LOG_FORMAT: "json", + DATABRICKS_LOG_LEVEL: "debug", + DATABRICKS_OUTPUT_FORMAT: "json", + HOME: process.env.HOME, + PATH: process.env.PATH, + /* eslint-enable @typescript-eslint/naming-convention */ + }), + }, + }; + try { + assert.ok(isMatch(runCmd, expected)); + } catch (e) { + // Run this in the "catch" case to show better error messages + assert.deepStrictEqual(runCmd, expected); + throw e; + } + }); +}); + +describe("waitForProcess", () => { + it("should return correctly formatted stdout and stderr", async () => { + const process = new ChildProcess(); + const stdoutChunks = [`{"hello": "wor`, `ld"}`]; + const stderrChunks = [`{"error": "no`, `oo"}`]; + process.stdout = new Readable({ + read() { + this.push(stdoutChunks.shift()); + }, + }); + process.stderr = new Readable({ + read() { + this.push(stderrChunks.shift()); + }, + }); + const waitPromise = waitForProcess( + process as ChildProcessWithoutNullStreams + ); + process.emit("close", 0); + const {stdout, stderr} = await waitPromise; + assert.equal(stdout, `{"hello": "world"}`); + assert.equal(stderr, `{"error": "nooo"}`); + }); }); diff --git a/packages/databricks-vscode/src/cli/CliWrapper.ts b/packages/databricks-vscode/src/cli/CliWrapper.ts index f50dfaf57..422adf676 100644 --- a/packages/databricks-vscode/src/cli/CliWrapper.ts +++ b/packages/databricks-vscode/src/cli/CliWrapper.ts @@ -1,15 +1,91 @@ -import {execFile as execFileCb, spawn} from "child_process"; -import {ExtensionContext, window, commands} from "vscode"; -import {SyncDestinationMapper} from "../sync/SyncDestination"; +import { + ChildProcessWithoutNullStreams, + SpawnOptionsWithoutStdio, + execFile as execFileCb, + spawn, +} from "child_process"; +import { + ExtensionContext, + window, + Uri, + commands, + CancellationToken, +} from "vscode"; import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {promisify} from "node:util"; import {logging} from "@databricks/databricks-sdk"; -import {Loggers} from "../logger"; +import {LoggerManager, Loggers} from "../logger"; import {Context, context} from "@databricks/databricks-sdk/dist/context"; import {Cloud} from "../utils/constants"; +import {EnvVarGenerators, FileUtils, UrlUtils} from "../utils"; +import {AuthProvider} from "../configuration/auth/AuthProvider"; +import {removeUndefinedKeys} from "../utils/envVarGenerators"; +import {quote} from "shell-quote"; +import {BundleVariableModel} from "../bundle/models/BundleVariableModel"; +import {MsPythonExtensionWrapper} from "../language/MsPythonExtensionWrapper"; +import path from "path"; +import {isPowershell} from "../utils/shellUtils"; const withLogContext = logging.withLogContext; -const execFile = promisify(execFileCb); +function getEscapedCommandAndAgrs( + cmd: string, + args: string[], + options: SpawnOptionsWithoutStdio +) { + if (process.platform === "win32") { + args = [ + "/d", //Disables execution of AutoRun commands, which are like .bashrc commands. + "/c", //Carries out the command specified by and then exits the command processor. + `""${cmd}" ${args.map((a) => `"${a}"`).join(" ")}"`, + ]; + cmd = "cmd.exe"; + options = {...options, windowsVerbatimArguments: true}; + } + return {cmd, args, options}; +} + +export async function cancellableExecFile( + file: string, + args: string[], + options: Omit = {}, + cancellationToken?: CancellationToken +): Promise<{ + stdout: string; + stderr: string; +}> { + const abortController = new AbortController(); + cancellationToken?.onCancellationRequested(() => abortController.abort()); + const signal = abortController.signal; + + const res = await promisify(execFileCb)(file, args, { + ...options, + signal, + }); + return {stdout: res.stdout.toString(), stderr: res.stderr.toString()}; +} + +export const execFile = async ( + file: string, + args: string[], + options: Omit = {}, + cancellationToken?: CancellationToken +): Promise<{ + stdout: string; + stderr: string; +}> => { + const { + cmd, + args: escapedArgs, + options: escapedOptions, + } = getEscapedCommandAndAgrs(file, args, options); + + return await cancellableExecFile( + cmd, + escapedArgs, + escapedOptions, + cancellationToken + ); +}; export interface Command { command: string; @@ -26,12 +102,167 @@ export interface ConfigEntry { } export type SyncType = "full" | "incremental"; +export class ProcessError extends Error { + constructor( + message: string, + public code: number | null + ) { + super(message); + } + + showErrorMessage(prefix?: string) { + if (this.message.includes("no value assigned to required variable")) { + window + .showErrorMessage( + (prefix?.trimEnd().concat(" ") ?? "") + + `No value assigned to required variables.`, + "Assign Values" + ) + .then((choice) => { + if (choice === "Assign Values") { + commands.executeCommand("databricks.bundle.showLogs"); + commands.executeCommand("dabsVariableView.focus"); + commands.executeCommand( + "databricks.bundle.variable.openFile" + ); + } + }); + return; + } -function getValidHost(host: string) { - if (host.match(/^(?:(?:https?):\/\/)?(.(?!:\/\/))+$/) !== null) { - return new URL(host); - } else { - throw new TypeError("Invalid type for host"); + window + .showErrorMessage( + (prefix?.trimEnd().concat(" ") ?? "") + + `Error executing Databricks CLI command.`, + "Show Logs" + ) + .then((choice) => { + if (choice === "Show Logs") { + commands.executeCommand("databricks.bundle.showLogs"); + } + }); + } +} + +export class CancellationError extends Error { + constructor() { + super("Cancelled"); + } +} + +export async function waitForProcess( + p: ChildProcessWithoutNullStreams, + onStdOut?: (data: string) => void, + onStdError?: (data: string) => void +) { + const stdout: string[] = []; + p.stdout.on("data", (data) => { + stdout.push(data.toString()); + if (onStdOut) { + onStdOut(data.toString()); + } + }); + + const stderr: string[] = []; + p.stderr.on("data", (data) => { + stderr.push(data.toString()); + if (onStdError) { + onStdError(data.toString()); + } + }); + + await new Promise((resolve, reject) => { + p.on("close", (code) => { + if (code === 0) { + resolve(); + } else { + reject(new ProcessError(stderr.join(""), code)); + } + }); + p.on("error", (e) => new ProcessError(e.message, null)); + }); + + return {stdout: stdout.join(""), stderr: stderr.join("")}; +} + +async function runBundleCommand( + bundleOpName: string, + cmd: string, + args: string[] = [], + workspaceFolder: Uri, + displayLogs: { + start: string | string[]; + end: string; + error: string; + }, + env: Record = {}, + logger?: logging.NamedLogger, + outputHandlers: { + onStdOut?: (data: string) => void; + onStdError?: (data: string) => void; + } = {}, + cancellationToken?: CancellationToken +) { + const defaultOutputHandlers = { + onStdOut: (data: string) => { + logger?.info(data, {bundleOpName}); + }, + onStdError: (data: string) => { + logger?.info(data, {bundleOpName}); + }, + }; + const {onStdOut, onStdError} = { + ...defaultOutputHandlers, + ...outputHandlers, + }; + const startLogs = + typeof displayLogs.start === "string" + ? [displayLogs.start] + : displayLogs.start; + + startLogs.forEach((msg) => { + logger?.info(msg, {bundleOpName}); + }); + + logger?.debug(quote([cmd, ...args]), {bundleOpName}); + const abortController = new AbortController(); + let options: SpawnOptionsWithoutStdio = { + cwd: workspaceFolder.fsPath, + env: removeUndefinedKeys(env), + signal: abortController.signal, + }; + + ({cmd, args, options} = getEscapedCommandAndAgrs(cmd, args, options)); + try { + const p = spawn(cmd, args, options); + cancellationToken?.onCancellationRequested(() => { + if (process.platform === "win32" && p.pid) { + // On windows aborting the signal doesn't kill the CLI. + // Use taskkill here with the "force" and "tree" flags (to kill sub-processes too) + spawn("taskkill", ["/pid", String(p.pid), "/T", "/F"]); + } else { + abortController.abort(); + } + }); + const {stdout, stderr} = await waitForProcess(p, onStdOut, onStdError); + logger?.info(displayLogs.end, { + bundleOpName, + }); + logger?.debug("output", {stdout, stderr, bundleOpName}); + return {stdout, stderr}; + } catch (e: any) { + if (cancellationToken?.isCancellationRequested) { + logger?.warn(`${displayLogs.error} Reason: Cancelled`, { + bundleOpName, + }); + throw new CancellationError(); + } else { + logger?.error(`${displayLogs.error} ${e.message ?? ""}`, { + ...e, + bundleOpName, + }); + throw new ProcessError(e.message, e.code); + } } } /** @@ -41,16 +272,33 @@ function getValidHost(host: string) { * of the databricks CLI */ export class CliWrapper { + private clusterId?: string; + private _bundleVariableModel?: BundleVariableModel; + private pythonExtension?: MsPythonExtensionWrapper; + constructor( private extensionContext: ExtensionContext, + private loggerManager: LoggerManager, private logFilePath?: string ) {} + public set bundleVariableModel(model: BundleVariableModel) { + this._bundleVariableModel = model; + } + + public setPythonExtension(pythonExtension: MsPythonExtensionWrapper) { + this.pythonExtension = pythonExtension; + } + + public setClusterId(clusterId?: string) { + this.clusterId = clusterId; + } + get cliPath(): string { return this.extensionContext.asAbsolutePath("./bin/databricks"); } - get loggingArguments(): string[] { + getLoggingArguments(): string[] { if (!workspaceConfigs.loggingEnabled) { return []; } @@ -64,21 +312,36 @@ export class CliWrapper { ]; } + getLogginEnvVars(): Record { + if (!workspaceConfigs.loggingEnabled) { + return {}; + } + return { + /* eslint-disable @typescript-eslint/naming-convention */ + DATABRICKS_LOG_LEVEL: "debug", + DATABRICKS_LOG_FILE: this.logFilePath ?? "stderr", + DATABRICKS_LOG_FORMAT: "json", + /* eslint-enable @typescript-eslint/naming-convention */ + }; + } + + get escapedCliPath(): string { + return isPowershell() + ? `& "${this.cliPath.replace('"', '\\"')}"` + : `'${this.cliPath.replaceAll("'", "\\'")}'`; + } + /** * Constructs the databricks sync command */ - getSyncCommand( - syncDestination: SyncDestinationMapper, - syncType: SyncType - ): Command { + getSyncCommand(syncType: SyncType): Command { const args = [ + "bundle", "sync", - ".", - syncDestination.remoteUri.path, "--watch", "--output", "json", - ...this.loggingArguments, + ...this.getLoggingArguments(), ]; if (syncType === "full") { args.push("--full"); @@ -93,7 +356,7 @@ export class CliWrapper { "auth", "profiles", "--skip-validate", - ...this.loggingArguments, + ...this.getLoggingArguments(), ], }; } @@ -109,12 +372,11 @@ export class CliWrapper { try { res = await execFile(cmd.command, cmd.args, { env: { - /* eslint-disable @typescript-eslint/naming-convention */ - HOME: process.env.HOME, - DATABRICKS_CONFIG_FILE: - configfilePath || process.env.DATABRICKS_CONFIG_FILE, - DATABRICKS_OUTPUT_FORMAT: "json", - /* eslint-enable @typescript-eslint/naming-convention */ + ...EnvVarGenerators.getEnvVarsForCli( + this.extensionContext, + configfilePath + ), + ...EnvVarGenerators.getProxyEnvVars(), }, }); } catch (e) { @@ -125,10 +387,18 @@ export class CliWrapper { "Failed to parse Databricks Config File, please make sure it's in the correct ini format"; } else if (e.message.includes("spawn UNKNOWN")) { msg = `Failed to parse Databricks Config File using databricks CLI, please make sure you have permissions to execute this binary: "${this.cliPath}"`; + } else { + msg += e.message; } } ctx?.logger?.error(msg, e); - this.showConfigFileWarning(msg); + window + .showWarningMessage(msg, "Open Databricks Config File") + .then(async (choice) => { + if (choice === "Open Databricks Config File") { + await FileUtils.openDatabricksConfigFile(); + } + }); return []; } @@ -138,11 +408,12 @@ export class CliWrapper { profiles = profiles.filter((p: any) => !p.account_id); const result = []; + let hasError = false; for (const profile of profiles) { try { result.push({ name: profile.name, - host: getValidHost(profile.host), + host: UrlUtils.normalizeHost(profile.host), accountId: profile.account_id, cloud: profile.cloud, authType: profile.auth_type, @@ -156,63 +427,295 @@ export class CliWrapper { msg = `Error parsing profile ${profile.name}`; } ctx?.logger?.error(msg, e); - this.showConfigFileWarning(msg); + hasError = true; } } + + if (hasError) { + window + .showWarningMessage( + "There were errors in parsing some profiles", + "Open Databricks Config File", + "Show Error Logs" + ) + .then(async (choice) => { + if (choice === "Open Databricks Config File") { + await FileUtils.openDatabricksConfigFile(); + } + if (choice === "Show Error Logs") { + this.loggerManager.showOutputChannel("Databricks Logs"); + } + }); + } return result; } - private async showConfigFileWarning(msg: string) { - const openAction = "Open Databricks Config File"; - const choice = await window.showWarningMessage( - msg, - openAction, - "Ignore" + public async getBundleSchema(): Promise { + const {stdout} = await execFile(this.cliPath, [ + "bundle", + "schema", + ...this.getLoggingArguments(), + ]); + return stdout; + } + + async getBundleCommandEnvVars( + authProvider: AuthProvider, + configfilePath?: string + ) { + // Add python executable to PATH + const executable = await this.pythonExtension?.getPythonExecutable(); + const cliEnvVars = EnvVarGenerators.getEnvVarsForCli( + this.extensionContext, + configfilePath ); - if (choice === openAction) { - commands.executeCommand( - "databricks.connection.openDatabricksConfigFile" - ); + let shellPath = cliEnvVars.PATH; + if (executable) { + shellPath = `${path.dirname(executable)}${ + path.delimiter + }${shellPath}`; } + + return removeUndefinedKeys({ + ...cliEnvVars, + ...EnvVarGenerators.getProxyEnvVars(), + ...authProvider.toEnv(), + ...this.getLogginEnvVars(), + ...((await this._bundleVariableModel?.getEnvVariables()) ?? {}), + /* eslint-disable @typescript-eslint/naming-convention */ + DATABRICKS_CLUSTER_ID: this.clusterId, + PATH: shellPath, + /* eslint-enable @typescript-eslint/naming-convention */ + }); } - public async getBundleSchema(): Promise { - const execFile = promisify(execFileCb); - const {stdout} = await execFile(this.cliPath, ["bundle", "schema"]); - return stdout; + async bundleValidate( + target: string, + authProvider: AuthProvider, + workspaceFolder: Uri, + configfilePath?: string, + logger?: logging.NamedLogger + ) { + return await runBundleCommand( + "validate", + this.cliPath, + ["bundle", "validate", "--target", target], + workspaceFolder, + { + start: `Reading local bundle configuration for target ${target}...`, + end: "Finished reading local bundle configuration.", + error: "Failed to read local bundle configuration.", + }, + await this.getBundleCommandEnvVars(authProvider, configfilePath), + logger, + { + onStdOut: (data) => logger?.debug(data, {target}), + onStdError: (data) => logger?.debug(data, {target}), + } + ); } - getAddProfileCommand(profile: string, host: URL): Command { - return { - command: this.cliPath, - args: [ - "configure", - "--no-interactive", - "--profile", - profile, - "--host", - host.href, - "--token", + async bundleSummarise( + target: string, + authProvider: AuthProvider, + workspaceFolder: Uri, + configfilePath?: string, + logger?: logging.NamedLogger + ) { + return await runBundleCommand( + "summarize", + this.cliPath, + [ + "bundle", + "summary", + "--target", + target, + // Forces the CLI to regenerate local terraform state and pull the remote state. + // Regenerating terraform state is useful when we want to ensure that the provider version + // used in the local state matches the bundled version we supply with the extension. + "--force-pull", ], - }; + workspaceFolder, + { + start: `Refreshing bundle configuration for target ${target}...`, + end: "Bundle configuration refreshed.", + error: "Failed to refresh bundle configuration.", + }, + await this.getBundleCommandEnvVars(authProvider, configfilePath), + logger, + { + onStdOut: (data) => logger?.debug(data, {target}), + onStdError: (data) => logger?.debug(data, {target}), + } + ); } - async addProfile( - name: string, - host: URL, - token: string - ): Promise<{stdout: string; stderr: string}> { - return new Promise((resolve, reject) => { - const {command, args} = this.getAddProfileCommand(name, host); - const child = spawn(command, args, { - stdio: ["pipe", 0, 0], - }); + getBundleInitEnvVars(authProvider: AuthProvider) { + return removeUndefinedKeys({ + ...EnvVarGenerators.getEnvVarsForCli( + this.extensionContext, + workspaceConfigs.databrickscfgLocation + ), + ...EnvVarGenerators.getProxyEnvVars(), + ...this.getLogginEnvVars(), + ...authProvider.toEnv(), + // eslint-disable-next-line @typescript-eslint/naming-convention + DATABRICKS_OUTPUT_FORMAT: "text", + }); + } - child.stdin!.write(`${token}\n`); - child.stdin!.end(); + async bundleInit( + templateDirPath: string, + outputDirPath: string, + initConfigFilePath: string, + authProvider: AuthProvider + ) { + return await execFile( + this.cliPath, + [ + "bundle", + "init", + templateDirPath, + "--output-dir", + outputDirPath, + "--config-file", + initConfigFilePath, + ], + { + env: this.getBundleInitEnvVars(authProvider), + } + ); + } - child.on("error", reject); - child.on("exit", resolve); + async bundleDeploy( + target: string, + authProvider: AuthProvider, + workspaceFolder: Uri, + configfilePath?: string, + logger?: logging.NamedLogger, + force = false, + token?: CancellationToken + ) { + await commands.executeCommand("databricks.bundle.showLogs"); + return await runBundleCommand( + "deploy", + this.cliPath, + [ + "bundle", + "deploy", + "--target", + target, + "--verbose", + ...(force ? ["--force-lock"] : []), + ], + workspaceFolder, + { + start: [`Deploying the bundle for target ${target}...`].concat( + this.clusterId + ? [`DATABRICKS_CLUSTER_ID=${this.clusterId}`] + : [] + ), + end: "Bundle deployed successfully.", + error: "Failed to deploy the bundle.", + }, + await this.getBundleCommandEnvVars(authProvider, configfilePath), + logger, + {}, + token + ); + } + + async bundleDestroy( + target: string, + authProvider: AuthProvider, + workspaceFolder: Uri, + configfilePath?: string, + logger?: logging.NamedLogger, + force = false, + token?: CancellationToken + ) { + await commands.executeCommand("databricks.bundle.showLogs"); + return await runBundleCommand( + "destroy", + this.cliPath, + [ + "bundle", + "destroy", + "--target", + target, + "--auto-approve", + ...(force ? ["--force-lock"] : []), + ], + workspaceFolder, + { + start: `Destroying the bundle for target ${target}...`, + end: "Bundle destroyed successfully.", + error: "Failed to destroy the bundle.", + }, + await this.getBundleCommandEnvVars(authProvider, configfilePath), + logger, + {}, + token + ); + } + + async bundleSync( + target: string, + authProvider: AuthProvider, + workspaceFolder: Uri, + configfilePath?: string, + logger?: logging.NamedLogger, + token?: CancellationToken + ) { + await commands.executeCommand("databricks.bundle.showLogs"); + return await runBundleCommand( + "sync", + this.cliPath, + ["bundle", "sync", "--target", target, "--output", "text"], + workspaceFolder, + { + start: `Uploading bundle assets for target ${target}...`, + end: "Bundle assets uploaded successfully.", + error: "Failed to upload bundle assets.", + }, + await this.getBundleCommandEnvVars(authProvider, configfilePath), + logger, + {}, + token + ); + } + + async getBundleRunCommand( + target: string, + authProvider: AuthProvider, + resourceKey: string, + workspaceFolder: Uri, + configfilePath?: string + ): Promise<{ + cmd: string; + args: string[]; + options: SpawnOptionsWithoutStdio; + }> { + const env: Record = removeUndefinedKeys({ + ...EnvVarGenerators.getEnvVarsForCli( + this.extensionContext, + configfilePath + ), + ...EnvVarGenerators.getProxyEnvVars(), + ...authProvider.toEnv(), + ...((await this._bundleVariableModel?.getEnvVariables()) ?? {}), + ...this.getLogginEnvVars(), + // eslint-disable-next-line @typescript-eslint/naming-convention + DATABRICKS_CLUSTER_ID: this.clusterId, }); + + return { + cmd: this.cliPath, + args: ["bundle", "run", "--target", target, resourceKey], + options: { + cwd: workspaceFolder.fsPath, + env, + }, + }; } } diff --git a/packages/databricks-vscode/src/cli/SyncTasks.test.ts b/packages/databricks-vscode/src/cli/SyncTasks.test.ts index 7d8ee8a94..4476e68c6 100644 --- a/packages/databricks-vscode/src/cli/SyncTasks.test.ts +++ b/packages/databricks-vscode/src/cli/SyncTasks.test.ts @@ -9,6 +9,7 @@ import {LocalUri, SyncDestinationMapper} from "../sync/SyncDestination"; import {PackageMetaData} from "../utils/packageJsonUtils"; import {LazyCustomSyncTerminal, SyncTask} from "./SyncTasks"; import type {CliWrapper} from "./CliWrapper"; +import {ConfigModel} from "../configuration/models/ConfigModel"; describe(__filename, () => { let connection: ConnectionManager; @@ -23,6 +24,7 @@ describe(__filename, () => { it("should create a sync task", () => { const task = new SyncTask( instance(connection), + instance(mock()), instance(cli), "incremental", { @@ -62,11 +64,12 @@ describe(__filename, () => { when(mockDbWorkspace.authProvider).thenReturn( new ProfileAuthProvider( new URL("https://000000000000.00.azuredatabricks.net/"), - "profile" + "profile", + instance(cli) ) ); when(mockDbWorkspace.host).thenReturn( - Uri.parse("https://000000000000.00.azuredatabricks.net/") + new URL("https://000000000000.00.azuredatabricks.net/") ); const mockSyncDestination = mock(SyncDestinationMapper); @@ -82,8 +85,11 @@ describe(__filename, () => { instance(mockSyncDestination) ); + const mockConfigModel = mock(ConfigModel); + when(mockConfigModel.target).thenReturn("dev"); terminal = new LazyCustomSyncTerminal( instance(connection), + instance(mockConfigModel), instance(cli), "full", { @@ -103,6 +109,7 @@ describe(__filename, () => { /* eslint-disable @typescript-eslint/naming-convention */ DATABRICKS_CLI_UPSTREAM: "databricks-vscode", DATABRICKS_CLI_UPSTREAM_VERSION: "1.0.0", + DATABRICKS_BUNDLE_TARGET: "dev", DATABRICKS_HOST: "https://000000000000.00.azuredatabricks.net/", DATABRICKS_AUTH_TYPE: "metadata-service", @@ -124,6 +131,7 @@ describe(__filename, () => { /* eslint-disable @typescript-eslint/naming-convention */ DATABRICKS_CLI_UPSTREAM: "databricks-vscode", DATABRICKS_CLI_UPSTREAM_VERSION: "1.0.0", + DATABRICKS_BUNDLE_TARGET: "dev", DATABRICKS_HOST: "https://000000000000.00.azuredatabricks.net/", DATABRICKS_AUTH_TYPE: "metadata-service", diff --git a/packages/databricks-vscode/src/cli/SyncTasks.ts b/packages/databricks-vscode/src/cli/SyncTasks.ts index 29dfdcd45..21c13c0f6 100644 --- a/packages/databricks-vscode/src/cli/SyncTasks.ts +++ b/packages/databricks-vscode/src/cli/SyncTasks.ts @@ -20,6 +20,7 @@ import {Context, context} from "@databricks/databricks-sdk/dist/context"; import {PackageMetaData} from "../utils/packageJsonUtils"; import {RWLock} from "../locking"; import {EnvVarGenerators} from "../utils"; +import {ConfigModel} from "../configuration/models/ConfigModel"; const {withLogContext} = logging; @@ -38,6 +39,7 @@ const cliToTaskSyncType = new Map([ export class SyncTask extends Task { constructor( connection: ConnectionManager, + configModel: ConfigModel, cli: CliWrapper, syncType: SyncType, packageMetadata: PackageMetaData, @@ -54,6 +56,7 @@ export class SyncTask extends Task { new CustomExecution(async (): Promise => { return new LazyCustomSyncTerminal( connection, + configModel, cli, syncType, packageMetadata, @@ -229,6 +232,7 @@ export class LazyCustomSyncTerminal extends CustomSyncTerminal { constructor( private connection: ConnectionManager, + private configModel: ConfigModel, private cli: CliWrapper, private syncType: SyncType, private packageMetadata: PackageMetaData, @@ -245,12 +249,12 @@ export class LazyCustomSyncTerminal extends CustomSyncTerminal { Object.defineProperties(this, { cmd: { get: () => { - return this.getSyncCommand(ctx).command; + return this.getSyncCommand().command; }, }, args: { get: () => { - return this.getSyncCommand(ctx).args; + return this.getSyncCommand().args; }, }, options: { @@ -297,28 +301,22 @@ export class LazyCustomSyncTerminal extends CustomSyncTerminal { HOME: process.env.HOME, PATH: process.env.PATH, ...EnvVarGenerators.removeUndefinedKeys( - EnvVarGenerators.getCommonDatabricksEnvVars(this.connection) + EnvVarGenerators.getCommonDatabricksEnvVars( + this.connection, + this.configModel + ) ), /* eslint-enable @typescript-eslint/naming-convention */ }, } as SpawnOptions; } - @withLogContext(Loggers.Extension) - getSyncCommand(@context ctx?: Context): Command { + getSyncCommand(): Command { if (this.command) { return this.command; } - const syncDestination = this.connection.syncDestinationMapper; - - if (!syncDestination) { - throw this.showErrorAndKillThis( - "Can't start sync: Databricks synchronization destination not configured!", - ctx - ); - } - this.command = this.cli.getSyncCommand(syncDestination, this.syncType); + this.command = this.cli.getSyncCommand(this.syncType); return this.command; } diff --git a/packages/databricks-vscode/src/cluster/ClusterListDataProvider.test.ts b/packages/databricks-vscode/src/cluster/ClusterListDataProvider.test.ts index a3fb15ddc..010a33230 100644 --- a/packages/databricks-vscode/src/cluster/ClusterListDataProvider.test.ts +++ b/packages/databricks-vscode/src/cluster/ClusterListDataProvider.test.ts @@ -114,9 +114,8 @@ describe(__filename, () => { mockListClustersResponse.clusters![0] ); - const items = await ClusterListDataProvider.clusterNodeToTreeItems( - cluster - ); + const items = + await ClusterListDataProvider.clusterNodeToTreeItems(cluster); assert.deepEqual(items, [ { description: "cluster-id-2", diff --git a/packages/databricks-vscode/src/cluster/ClusterManager.ts b/packages/databricks-vscode/src/cluster/ClusterManager.ts index 5e527d2bd..84ebbed68 100644 --- a/packages/databricks-vscode/src/cluster/ClusterManager.ts +++ b/packages/databricks-vscode/src/cluster/ClusterManager.ts @@ -1,10 +1,12 @@ import {compute, Time, TimeUnits} from "@databricks/databricks-sdk"; import {Cluster} from "../sdk-extensions"; import {CancellationTokenSource, Disposable} from "vscode"; - +import lodash from "lodash"; +import {logging, context, Context} from "@databricks/databricks-sdk"; +import {Loggers} from "../logger"; export class ClusterManager implements Disposable { private cancellationTokenSource?: CancellationTokenSource; - private refreshTimer?: ReturnType; + private refreshTimer?: NodeJS.Timeout; constructor( readonly cluster: Cluster, @@ -14,10 +16,19 @@ export class ClusterManager implements Disposable { this.setInterval(); } - private setInterval() { + @logging.withLogContext(Loggers.Extension) + private setInterval(@context ctx?: Context) { this.refreshTimer = setInterval(async () => { - await this.cluster.refresh(); - this.onChange(this.cluster.state); + const oldState = this.cluster.state; + try { + await this.cluster.refresh(); + } catch (e: any) { + ctx?.logger?.error("Error refreshing cluster", e); + } + + if (!lodash.isEqual(oldState, this.cluster.state)) { + this.onChange(this.cluster.state); + } }, this.refreshTimeout.toMillSeconds().value); } diff --git a/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.test.ts b/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.test.ts deleted file mode 100644 index 79d7cf3f6..000000000 --- a/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.test.ts +++ /dev/null @@ -1,198 +0,0 @@ -/* eslint-disable @typescript-eslint/naming-convention */ - -import assert from "assert"; -import {mock, when, instance, anything} from "ts-mockito"; -import {Disposable} from "vscode"; -import {ConfigurationDataProvider} from "./ConfigurationDataProvider"; -import {ApiClient} from "@databricks/databricks-sdk"; -import {Cluster} from "../sdk-extensions"; -import {ConnectionManager} from "./ConnectionManager"; -import {resolveProviderResult} from "../test/utils"; -import {SyncDestinationMapper} from "../sync/SyncDestination"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; -import {StateStorage} from "../vscode-objs/StateStorage"; -import {WorkspaceFsAccessVerifier} from "../workspace-fs"; -import {FeatureManager} from "../feature-manager/FeatureManager"; -import {Telemetry} from "../telemetry"; - -describe(__filename, () => { - let connectionManagerMock: ConnectionManager; - let disposables: Array; - let onChangeClusterListener: (e: Cluster) => void; - let onChangeSyncDestinationListener: (e: SyncDestinationMapper) => void; - let sync: CodeSynchronizer; - - beforeEach(() => { - disposables = []; - connectionManagerMock = mock(ConnectionManager); - when(connectionManagerMock.state).thenReturn("DISCONNECTED"); - onChangeClusterListener = () => {}; - onChangeSyncDestinationListener = () => {}; - - when(connectionManagerMock.onDidChangeState).thenReturn(() => { - return { - dispose() {}, - }; - }); - when(connectionManagerMock.onDidChangeCluster).thenReturn( - (_handler) => { - onChangeClusterListener = _handler; - return { - dispose() {}, - }; - } - ); - when(connectionManagerMock.onDidChangeSyncDestination).thenReturn( - (_handler) => { - onChangeSyncDestinationListener = _handler; - return { - dispose() {}, - }; - } - ); - - const syncMock = mock(CodeSynchronizer); - when(syncMock.onDidChangeState(anything())).thenReturn({ - dispose() {}, - }); - sync = instance(syncMock); - }); - - afterEach(() => { - disposables.forEach((d) => { - try { - d.dispose(); - } catch (e) {} - }); - }); - - it("should reload tree on cluster change", async () => { - const connectionManager = instance(connectionManagerMock); - const provider = new ConfigurationDataProvider( - connectionManager, - sync, - instance(mock(StateStorage)), - instance(mock(WorkspaceFsAccessVerifier)), - instance(mock(FeatureManager<"debugging.dbconnect">)), - instance(mock(Telemetry)) - ); - disposables.push(provider); - - let called = false; - disposables.push( - provider.onDidChangeTreeData(() => { - called = true; - }) - ); - - assert(!called); - onChangeClusterListener(new Cluster(instance(mock(ApiClient)), {})); - assert(called); - }); - - it("should reload tree on sync destination change", async () => { - const connectionManager = instance(connectionManagerMock); - const provider = new ConfigurationDataProvider( - connectionManager, - sync, - instance(mock(StateStorage)), - instance(mock(WorkspaceFsAccessVerifier)), - instance(mock(FeatureManager<"debugging.dbconnect">)), - instance(mock(Telemetry)) - ); - disposables.push(provider); - - let called = false; - disposables.push( - provider.onDidChangeTreeData(() => { - called = true; - }) - ); - - assert(!called); - onChangeSyncDestinationListener(instance(mock(SyncDestinationMapper))); - assert(called); - }); - - it("should get empty roots", async () => { - const connectionManager = instance(connectionManagerMock); - const provider = new ConfigurationDataProvider( - connectionManager, - sync, - instance(mock(StateStorage)), - instance(mock(WorkspaceFsAccessVerifier)), - instance(mock(FeatureManager<"debugging.dbconnect">)), - instance(mock(Telemetry)) - ); - disposables.push(provider); - - const children = await resolveProviderResult(provider.getChildren()); - assert(children); - assert.equal(children.length, 0); - }); - - it("should return cluster children", async () => { - const mockApiClient = mock(ApiClient); - when(mockApiClient.host).thenResolve( - new URL("https://www.example.com") - ); - const cluster = new Cluster(instance(mockApiClient), { - cluster_id: "cluster-id-2", - cluster_name: "cluster-name-2", - cluster_source: "UI", - creator_user_name: "user-2", - spark_version: "10.4.x-scala2.12", - state: "TERMINATED", - }); - - when(connectionManagerMock.state).thenReturn("CONNECTED"); - when(connectionManagerMock.cluster).thenReturn(cluster); - - const connectionManager = instance(connectionManagerMock); - const provider = new ConfigurationDataProvider( - connectionManager, - sync, - instance(mock(StateStorage)), - instance(mock(WorkspaceFsAccessVerifier)), - instance(mock(FeatureManager<"debugging.dbconnect">)), - instance(mock(Telemetry)) - ); - disposables.push(provider); - - const children = await resolveProviderResult(provider.getChildren()); - assert.deepEqual(children, [ - { - collapsibleState: 2, - contextValue: "workspace", - iconPath: { - color: undefined, - id: "account", - }, - id: "WORKSPACE", - label: "Workspace", - url: undefined, - }, - { - collapsibleState: 2, - contextValue: "databricks.cluster.terminated", - iconPath: { - color: undefined, - id: "server", - }, - id: "CLUSTER", - label: "Cluster", - url: "https://www.example.com/#setting/clusters/cluster-id-2/configuration", - }, - { - collapsibleState: 2, - contextValue: "syncDetached", - iconPath: { - color: undefined, - id: "file-directory", - }, - id: "SYNC-DESTINATION", - label: 'Sync Destination - "None attached"', - }, - ]); - }); -}); diff --git a/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.ts b/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.ts deleted file mode 100644 index 7a76c943e..000000000 --- a/packages/databricks-vscode/src/configuration/ConfigurationDataProvider.ts +++ /dev/null @@ -1,386 +0,0 @@ -import { - Disposable, - Event, - EventEmitter, - ThemeColor, - ThemeIcon, - TreeDataProvider, - TreeItem, - TreeItemCollapsibleState, - window, -} from "vscode"; - -import {ClusterListDataProvider} from "../cluster/ClusterListDataProvider"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; -import {ConnectionManager} from "./ConnectionManager"; -import {StateStorage} from "../vscode-objs/StateStorage"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; -import { - WorkspaceFsAccessVerifier, - switchToWorkspacePrompt, -} from "../workspace-fs"; -import {FeatureManager} from "../feature-manager/FeatureManager"; -import {Telemetry} from "../telemetry"; - -export type ConfigurationTreeItem = TreeItem & { - url?: string; -}; - -/** - * Data provider for the cluster tree view - */ -export class ConfigurationDataProvider - implements TreeDataProvider, Disposable -{ - private _onDidChangeTreeData: EventEmitter< - ConfigurationTreeItem | undefined | void - > = new EventEmitter(); - readonly onDidChangeTreeData: Event< - ConfigurationTreeItem | undefined | void - > = this._onDidChangeTreeData.event; - - private disposables: Array = []; - - constructor( - private connectionManager: ConnectionManager, - private sync: CodeSynchronizer, - private readonly stateStorage: StateStorage, - private readonly wsfsAccessVerifier: WorkspaceFsAccessVerifier, - private readonly featureManager: FeatureManager, - private readonly telemetry: Telemetry - ) { - this.disposables.push( - this.connectionManager.onDidChangeState(() => { - this._onDidChangeTreeData.fire(); - }), - this.connectionManager.onDidChangeCluster(() => { - this._onDidChangeTreeData.fire(); - }), - this.connectionManager.onDidChangeSyncDestination(() => { - this._onDidChangeTreeData.fire(); - }), - this.sync.onDidChangeState(() => { - this._onDidChangeTreeData.fire(); - }), - this.wsfsAccessVerifier.onDidChangeState(() => { - this._onDidChangeTreeData.fire(); - }) - ); - - this.connectionManager; - } - - dispose() { - this.disposables.forEach((d) => d.dispose()); - } - - getTreeItem(element: ConfigurationTreeItem): TreeItem | Thenable { - return element; - } - - async getChildren( - element?: ConfigurationTreeItem | undefined - ): Promise> { - switch (this.connectionManager.state) { - case "CONNECTED": - break; - case "CONNECTING": - await this.connectionManager.waitForConnect(); - break; - case "DISCONNECTED": - return []; - } - - const cluster = this.connectionManager.cluster; - const syncDestination = this.connectionManager.syncDestinationMapper; - - if (!element) { - const children: Array = []; - children.push({ - label: `Workspace`, - iconPath: new ThemeIcon("account"), - id: "WORKSPACE", - collapsibleState: TreeItemCollapsibleState.Expanded, - contextValue: "workspace", - url: this.connectionManager.databricksWorkspace?.host?.toString(), - }); - - if (cluster) { - let contextValue: - | "databricks.cluster.running" - | "databricks.cluster.pending" - | "databricks.cluster.terminating" - | "databricks.cluster.terminated" = - "databricks.cluster.terminated"; - - switch (cluster.state) { - case "RESIZING": - case "RUNNING": - contextValue = "databricks.cluster.running"; - break; - case "PENDING": - case "RESTARTING": - contextValue = "databricks.cluster.pending"; - break; - case "TERMINATING": - contextValue = "databricks.cluster.terminating"; - break; - case "TERMINATED": - contextValue = "databricks.cluster.terminated"; - break; - } - - children.push({ - label: "Cluster", - iconPath: new ThemeIcon("server"), - id: "CLUSTER", - collapsibleState: TreeItemCollapsibleState.Expanded, - contextValue, - url: (await cluster.url).toString(), - }); - } else { - children.push({ - label: `Cluster - "None attached"`, - iconPath: new ThemeIcon("server"), - id: "CLUSTER", - collapsibleState: TreeItemCollapsibleState.Expanded, - contextValue: "clusterDetached", - }); - } - if (syncDestination) { - const url = this.connectionManager.workspaceClient - ? await syncDestination.remoteUri.getUrl( - this.connectionManager.workspaceClient - ) - : undefined; - // TODO: Add another icon over here for in_progress state - // DECO-220 - children.push({ - label: `Sync Destination`, - iconPath: new ThemeIcon("file-directory"), - id: "SYNC-DESTINATION", - collapsibleState: TreeItemCollapsibleState.Expanded, - url: url, - contextValue: - this.sync.state === "WATCHING_FOR_CHANGES" || - this.sync.state === "IN_PROGRESS" - ? "syncRunning" - : "syncStopped", - }); - } else { - children.push({ - label: `Sync Destination - "None attached"`, - iconPath: new ThemeIcon("file-directory"), - id: "SYNC-DESTINATION", - collapsibleState: TreeItemCollapsibleState.Expanded, - contextValue: "syncDetached", - }); - } - - return children; - } - - const dbWorkspace = this.connectionManager.databricksWorkspace; - if (element.id === "WORKSPACE" && dbWorkspace) { - return [ - { - label: "Auth", - description: dbWorkspace.authProvider.describe(), - collapsibleState: TreeItemCollapsibleState.None, - }, - { - label: "User", - description: dbWorkspace.userName, - collapsibleState: TreeItemCollapsibleState.None, - }, - { - label: "Host", - description: dbWorkspace.host.toString(), - collapsibleState: TreeItemCollapsibleState.None, - contextValue: "databricks-link", - }, - ]; - } - - if (element.id?.startsWith("CLUSTER") && cluster) { - const clusterItem = - ClusterListDataProvider.clusterNodeToTreeItem(cluster); - - const children: ConfigurationTreeItem[] = [ - { - label: "Name", - description: cluster.name, - iconPath: clusterItem.iconPath, - collapsibleState: TreeItemCollapsibleState.None, - }, - ]; - - let runPerms: - | "CAN_RUN" - | "MIGHT_RUN" - | "UNABLE_TO_RUN" - | "MIGHT_NOT_RUN" = "MIGHT_RUN"; - if ( - cluster.state === "RUNNING" && - cluster?.canExecuteCached !== undefined - ) { - runPerms = cluster.canExecuteCached - ? "CAN_RUN" - : "UNABLE_TO_RUN"; - } else { - runPerms = - cluster.hasExecutePermsCached ?? true - ? "MIGHT_RUN" - : "MIGHT_NOT_RUN"; - } - - switch (runPerms) { - case "CAN_RUN": - children.push({ - label: "You can run code on this cluster", - iconPath: new ThemeIcon( - "testing-passed-icon", - new ThemeColor("testing.iconPassed") - ), - }); - break; - - case "MIGHT_NOT_RUN": - children.push({ - label: "You might not have permissions to run code on this cluster", - iconPath: new ThemeIcon( - "warning", - new ThemeColor("problemsWarningIcon.foreground") - ), - }); - break; - - case "UNABLE_TO_RUN": - children.push({ - label: "You do not have permissions to run code on this cluster", - iconPath: new ThemeIcon( - "alert", - new ThemeColor("testing.iconFailed") - ), - }); - break; - } - - children.push( - ...(await ClusterListDataProvider.clusterNodeToTreeItems( - cluster - )) - ); - const dbconnectReason = await this.getDbConnectDisabledReason(); - if (dbconnectReason) { - children.push(dbconnectReason); - } - return children; - } - - if (element.id === "SYNC-DESTINATION" && syncDestination) { - const children: Array = [ - { - label: `Name`, - description: syncDestination.remoteUri.name, - iconPath: - this.sync.state === "WATCHING_FOR_CHANGES" || - this.sync.state === "IN_PROGRESS" - ? new ThemeIcon("debug-start") - : new ThemeIcon("debug-stop"), - collapsibleState: TreeItemCollapsibleState.None, - }, - ]; - - if ( - workspaceConfigs.syncDestinationType === "repo" && - this.wsfsAccessVerifier.isEnabled - ) { - const label = "Switch to workspace"; - children.push({ - label: { - highlights: [[0, label.length]], - label, - }, - tooltip: "Click to switch to workspace", - iconPath: new ThemeIcon( - "warning", - new ThemeColor("problemsWarningIcon.foreground") - ), - command: { - title: "Call", - command: "databricks.call", - arguments: [ - () => { - switchToWorkspacePrompt( - this.stateStorage, - this.telemetry - ); - }, - ], - }, - }); - } - - const errorOverrides: TreeItem = - this.sync.state === "ERROR" && this.sync.reason - ? { - description: "Error - Click for more details", - iconPath: new ThemeIcon( - "alert", - new ThemeColor("errorForeground") - ), - tooltip: "Click for more details", - - command: { - title: "Call", - command: "databricks.call", - arguments: [ - () => { - window.showErrorMessage( - `Sync Error: ${this.sync.reason}` - ); - }, - ], - }, - } - : {}; - children.push( - { - label: `State`, - description: this.sync.state, - collapsibleState: TreeItemCollapsibleState.None, - ...errorOverrides, - }, - { - label: `Path`, - description: syncDestination.remoteUri.path, - collapsibleState: TreeItemCollapsibleState.None, - } - ); - - return children; - } - - return []; - } - - async getDbConnectDisabledReason(): Promise< - ConfigurationTreeItem | undefined - > { - const isDbConnectEnabled = await this.featureManager.isEnabled( - "debugging.dbconnect" - ); - if (isDbConnectEnabled.isDisabledByFf || isDbConnectEnabled.avaliable) { - return undefined; - } - - return isDbConnectEnabled.reason && - isDbConnectEnabled.reason.toLowerCase().includes("cluster") - ? { - label: "Debug", - description: isDbConnectEnabled.reason, - } - : undefined; - } -} diff --git a/packages/databricks-vscode/src/configuration/ConnectionCommands.ts b/packages/databricks-vscode/src/configuration/ConnectionCommands.ts index c2c2ef100..98c377b62 100644 --- a/packages/databricks-vscode/src/configuration/ConnectionCommands.ts +++ b/packages/databricks-vscode/src/configuration/ConnectionCommands.ts @@ -1,22 +1,28 @@ -import {Cluster, WorkspaceFsEntity, WorkspaceFsUtils} from "../sdk-extensions"; +import {Cluster} from "../sdk-extensions"; import { Disposable, - FileSystemError, QuickPickItem, QuickPickItemKind, ThemeIcon, - Uri, window, - workspace, + commands, } from "vscode"; import {ClusterListDataProvider} from "../cluster/ClusterListDataProvider"; import {ClusterModel} from "../cluster/ClusterModel"; import {ConnectionManager} from "./ConnectionManager"; -import {FileUtils, UrlUtils} from "../utils"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; +import {UrlUtils} from "../utils"; import {WorkspaceFsCommands} from "../workspace-fs"; -import path from "node:path"; -import {RemoteUri, REPO_NAME_SUFFIX} from "../sync/SyncDestination"; +import {ConfigModel} from "./models/ConfigModel"; +import {saveNewProfile} from "./LoginWizard"; +import {PersonalAccessTokenAuthProvider} from "./auth/AuthProvider"; +import {normalizeHost} from "../utils/urlUtils"; +import {CliWrapper, ProcessError} from "../cli/CliWrapper"; +import { + AUTH_TYPE_SWITCH_ID, + AUTH_TYPE_LOGIN_ID, +} from "../ui/configuration-view/AuthTypeComponent"; +import {ManualLoginSource} from "../telemetry/constants"; +import {onError} from "../utils/onErrorDecorator"; function formatQuickPickClusterSize(sizeInMB: number): string { if (sizeInMB > 1024) { @@ -55,7 +61,9 @@ export class ConnectionCommands implements Disposable { constructor( private wsfsCommands: WorkspaceFsCommands, private connectionManager: ConnectionManager, - private readonly clusterModel: ClusterModel + private readonly clusterModel: ClusterModel, + private readonly configModel: ConfigModel, + private readonly cli: CliWrapper ) {} /** @@ -65,36 +73,40 @@ export class ConnectionCommands implements Disposable { this.connectionManager.logout(); } - async configureWorkspaceCommand() { - await this.connectionManager.configureWorkspace(); - } - - openDatabricksConfigFileCommand() { - return async () => { - const homeDir = FileUtils.getHomedir(); - let filePath = - workspaceConfigs.databrickscfgLocation ?? - process.env.DATABRICKS_CONFIG_FILE ?? - path.join(homeDir, ".databrickscfg"); - - if (filePath.startsWith("~/")) { - filePath = path.join(homeDir, filePath.slice(2)); - } - const uri = Uri.file(path.normalize(filePath)); - - try { - await workspace.fs.stat(uri); - } catch (e) { - if (e instanceof FileSystemError && e.code === "FileNotFound") { - await workspace.fs.writeFile(uri, Buffer.from("")); - } else { - throw e; - } + async configureLoginCommand(arg?: {id: string}) { + commands.executeCommand("configurationView.focus"); + let source: ManualLoginSource = "command"; + if (arg?.id === AUTH_TYPE_SWITCH_ID) { + source = "authTypeSwitch"; + } else if (arg?.id === AUTH_TYPE_LOGIN_ID) { + source = "authTypeLogin"; + } + await window.withProgress( + { + location: {viewId: "configurationView"}, + title: "Configuring Databricks login", + }, + async () => { + await this.connectionManager.configureLogin(source); } + ); + } - const doc = await workspace.openTextDocument(uri); - await window.showTextDocument(doc); - }; + // This command is not exposed to users. + // We use it to test new profile flow in e2e tests. + async saveNewProfileCommand(name: string) { + const host = this.connectionManager.workspaceClient?.config.host; + const token = this.connectionManager.workspaceClient?.config.token; + if (!host || !token) { + throw new Error("Must login first"); + } + const hostUrl = normalizeHost(host); + const provider = new PersonalAccessTokenAuthProvider( + hostUrl, + token, + this.cli + ); + await saveNewProfile(name, provider, this.cli); } /** @@ -104,12 +116,12 @@ export class ConnectionCommands implements Disposable { */ attachClusterCommand() { return async (cluster: Cluster) => { - await this.connectionManager.attachCluster(cluster); + await this.connectionManager.attachCluster(cluster.id); }; } attachClusterQuickPickCommand() { - return async () => { + return async (title?: string) => { const workspaceClient = this.connectionManager.workspaceClient; const me = this.connectionManager.databricksWorkspace?.userName; if (!workspaceClient || !me) { @@ -120,6 +132,8 @@ export class ConnectionCommands implements Disposable { const quickPick = window.createQuickPick< ClusterItem | QuickPickItem >(); + quickPick.title = + typeof title === "string" ? title : "Select Cluster"; quickPick.keepScrollPosition = true; quickPick.busy = true; @@ -168,7 +182,7 @@ export class ConnectionCommands implements Disposable { const selectedItem = quickPick.selectedItems[0]; if ("cluster" in selectedItem) { const cluster = selectedItem.cluster; - await this.connectionManager.attachCluster(cluster); + await this.connectionManager.attachCluster(cluster.id); } else { await UrlUtils.openExternal( `${ @@ -198,129 +212,37 @@ export class ConnectionCommands implements Disposable { }; } - attachSyncDestinationCommand() { - return async () => { - const wsClient = this.connectionManager.workspaceClient; - const me = this.connectionManager.databricksWorkspace?.userName; - const rootDirPath = - this.connectionManager.databricksWorkspace?.currentFsRoot; - if (!wsClient || !me || !rootDirPath) { - // TODO - return; - } - - const rootDir = await WorkspaceFsEntity.fromPath( - wsClient, - rootDirPath.path - ); - - type WorkspaceFsQuickPickItem = QuickPickItem & { - path?: string; - }; - const children: WorkspaceFsQuickPickItem[] = [ - { - label: "Create New Sync Destination", - alwaysShow: true, - detail: workspaceConfigs.enableFilesInWorkspace - ? `Create a new folder under /Workspace/${me}/.ide as sync destination` - : `Create a new Repo under /Repos/${me} as sync destination`, - }, - { - label: "Sync Destinations", - kind: QuickPickItemKind.Separator, - }, - ]; - - const input = window.createQuickPick(); - input.busy = true; - input.show(); - input.items = children; - if (workspaceConfigs.enableFilesInWorkspace) { - children.push( - ...((await rootDir?.children) ?? []) - .filter((entity) => - WorkspaceFsUtils.isDirectory(entity) - ) - .map((entity) => { - return { - label: entity.basename, - detail: entity.path, - path: entity.path, - }; - }) - ); - } else { - const repos = (await rootDir?.children) ?? []; - - children.push( - ...repos - .filter((entity) => { - return entity.basename.endsWith(REPO_NAME_SUFFIX); - }) - .map((entity) => { - return { - label: entity.basename.slice( - 0, - -REPO_NAME_SUFFIX.length - ), - detail: entity.path, - path: entity.path, - }; - }) - ); - } - input.items = children; - input.busy = false; - - const disposables = [ - input, - input.onDidAccept(async () => { - const fn = async () => { - const selection = input - .selectedItems[0] as WorkspaceFsQuickPickItem; - if ( - selection.label !== "Create New Sync Destination" && - selection.path - ) { - this.connectionManager.attachSyncDestination( - new RemoteUri(selection.path) - ); - return; - } - const created = await this.wsfsCommands.createFolder( - rootDir - ); - if (created === undefined) { - return; - } - this.connectionManager.attachSyncDestination( - new RemoteUri(created.path) - ); + @onError({popup: {prefix: "Error selecting target."}}) + async selectTarget() { + const targets = await this.configModel.targets; + const currentTarget = this.configModel.target; + if (targets === undefined) { + return; + } + + const selectedTarget = await window.showQuickPick( + Object.keys(targets) + .map((t) => { + return { + label: t, + description: targets[t].mode ?? "dev", + detail: targets[t].workspace?.host, }; - try { - await fn(); - } catch (e: unknown) { - if (e instanceof Error) { - window.showErrorMessage( - `Error while creating a new directory: ${e.message}` - ); - } - } finally { - disposables.forEach((i) => i.dispose()); - } - }), - input.onDidHide(() => { - disposables.forEach((i) => i.dispose()); - }), - ]; - }; - } - - /** - * Set workspace to undefined and remove workspace path from settings file. - */ - async detachWorkspaceCommand() { - this.connectionManager.detachSyncDestination(); + }) + .sort((a) => (a.label === currentTarget ? -1 : 1)), + {title: "Select bundle target"} + ); + if (selectedTarget === undefined) { + return; + } + try { + await this.configModel.setTarget(selectedTarget.label); + } catch (e) { + if (e instanceof ProcessError) { + e.showErrorMessage("Error selecting target"); + } + throw e; + } } dispose() { diff --git a/packages/databricks-vscode/src/configuration/ConnectionManager.ts b/packages/databricks-vscode/src/configuration/ConnectionManager.ts index 689f75d76..f5a584255 100644 --- a/packages/databricks-vscode/src/configuration/ConnectionManager.ts +++ b/packages/databricks-vscode/src/configuration/ConnectionManager.ts @@ -2,34 +2,30 @@ import { WorkspaceClient, ApiClient, logging, - Headers, + AuthType as SdkAuthType, } from "@databricks/databricks-sdk"; -import {Cluster, WorkspaceFsEntity, WorkspaceFsUtils} from "../sdk-extensions"; -import { - env, - EventEmitter, - Uri, - window, - workspace as vscodeWorkspace, -} from "vscode"; -import {CliWrapper} from "../cli/CliWrapper"; +import {Cluster} from "../sdk-extensions"; +import {EventEmitter, window, Disposable} from "vscode"; +import {CliWrapper, ProcessError} from "../cli/CliWrapper"; import { SyncDestinationMapper, RemoteUri, LocalUri, } from "../sync/SyncDestination"; -import { - ConfigFileError, - ProjectConfig, - ProjectConfigFile, -} from "../file-managers/ProjectConfigFile"; -import {configureWorkspaceWizard} from "./configureWorkspaceWizard"; +import {LoginWizard, getProfilesForHost} from "./LoginWizard"; import {ClusterManager} from "../cluster/ClusterManager"; import {DatabricksWorkspace} from "./DatabricksWorkspace"; -import {Loggers} from "../logger"; import {CustomWhenContext} from "../vscode-objs/CustomWhenContext"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; +import {ConfigModel} from "./models/ConfigModel"; +import {onError, withOnErrorHandler} from "../utils/onErrorDecorator"; +import {AuthProvider, ProfileAuthProvider} from "./auth/AuthProvider"; +import {Mutex} from "../locking"; import {MetadataService} from "./auth/MetadataService"; +import {Events, Telemetry} from "../telemetry"; +import {AutoLoginSource, ManualLoginSource} from "../telemetry/constants"; +import {Barrier} from "../locking/Barrier"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; +import {ProjectConfigFile} from "../file-managers/ProjectConfigFile"; // eslint-disable-next-line @typescript-eslint/naming-convention const {NamedLogger} = logging; @@ -41,11 +37,15 @@ export type ConnectionState = "CONNECTED" | "CONNECTING" | "DISCONNECTED"; * It's responsible for reading and validating the project configuration * and for providing instances of the APIClient, Cluster and Workspace classes */ -export class ConnectionManager { +export class ConnectionManager implements Disposable { + private disposables: Disposable[] = []; private _state: ConnectionState = "DISCONNECTED"; + private loginLogoutMutex: Mutex = new Mutex(); + private savedAuthMutex: Mutex = new Mutex(); + private configureLoginMutex: Mutex = new Mutex(); + private _workspaceClient?: WorkspaceClient; private _syncDestinationMapper?: SyncDestinationMapper; - private _projectConfigFile?: ProjectConfigFile; private _clusterManager?: ClusterManager; private _databricksWorkspace?: DatabricksWorkspace; private _metadataService: MetadataService; @@ -64,26 +64,139 @@ export class ConnectionManager { public readonly onDidChangeSyncDestination = this.onDidChangeSyncDestinationEmitter.event; - constructor(private cli: CliWrapper) { + private readonly initialization = new Barrier(); + + get workspaceUri() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private cli: CliWrapper, + private readonly configModel: ConfigModel, + private readonly workspaceFolderManager: WorkspaceFolderManager, + private readonly customWhenContext: CustomWhenContext, + private readonly telemetry: Telemetry + ) { this._metadataService = new MetadataService( undefined, NamedLogger.getOrCreate("Extension") ); } + @onError({ + popup: {prefix: "Error attaching sync destination: "}, + }) + private async updateSyncDestinationMapper() { + const workspacePath = await this.configModel.get("remoteRootPath"); + const remoteUri = workspacePath + ? new RemoteUri(workspacePath) + : undefined; + if (remoteUri?.path === this._syncDestinationMapper?.remoteUri.path) { + return; + } + if (remoteUri === undefined) { + this._syncDestinationMapper = undefined; + this.onDidChangeSyncDestinationEmitter.fire( + this._syncDestinationMapper + ); + return; + } + this._syncDestinationMapper = new SyncDestinationMapper( + new LocalUri(this.workspaceUri), + remoteUri + ); + } + + @onError({ + popup: {prefix: "Error attaching cluster: "}, + }) + private async updateClusterManager() { + try { + const clusterId = await this.configModel.get("clusterId"); + if (clusterId === this._clusterManager?.cluster?.id) { + return; + } + this._clusterManager?.dispose(); + this._clusterManager = + clusterId !== undefined && this.apiClient !== undefined + ? new ClusterManager( + await Cluster.fromClusterId( + this.apiClient, + clusterId + ), + () => { + this.onDidChangeClusterEmitter.fire(this.cluster); + } + ) + : undefined; + + if ( + (await this.configModel.get("useClusterOverride")) || + clusterId === undefined + ) { + this.cli.setClusterId(clusterId); + } + this.onDidChangeClusterEmitter.fire(this.cluster); + } catch (e) { + this.configModel.set("clusterId", undefined); + throw e; + } + } + get metadataServiceUrl() { return this._metadataService.url; } + public async init() { + try { + await this.loginWithSavedAuth("init"); + } finally { + this.disposables.push( + this.configModel.onDidChangeKey("remoteRootPath")( + this.updateSyncDestinationMapper.bind(this) + ), + this.configModel.onDidChangeKey("clusterId")( + this.updateClusterManager.bind(this) + ), + this.configModel.onDidChangeKey("useClusterOverride")( + async () => { + const useClusterOverride = + await this.configModel.get("useClusterOverride"); + this.cli.setClusterId( + useClusterOverride + ? this._clusterManager?.cluster?.id + : undefined + ); + } + ), + // Don't just listen to target change for logging in. Also explictly listen for changes in the keys we care about. + // We don't have to listen to changes in authProfile as it's set by the login method and we don't respect other + // user changes. + // TODO: start listening to changes in authParams + this.configModel.onDidChangeKey("host")( + this.loginWithSavedAuth.bind(this, "hostChange") + ), + this.configModel.onDidChangeTarget( + this.loginWithSavedAuth.bind(this, "targetChange") + ), + this.workspaceFolderManager.onDidChangeActiveWorkspaceFolder( + withOnErrorHandler( + async () => { + await this.configModel.setTarget(undefined); + }, + {log: true} + ) + ) + ); + this.initialization.resolve(); + } + } + get state(): ConnectionState { return this._state; } get cluster(): Cluster | undefined { - if (this.state !== "CONNECTED") { - return; - } - return this._clusterManager?.cluster; } @@ -108,421 +221,250 @@ export class ConnectionManager { return this._workspaceClient?.apiClient; } - async login(interactive = false, force = false): Promise { - try { - await this._login(interactive, force); - } catch (e) { - NamedLogger.getOrCreate("Extension").error("Login Error:", e); - if (interactive && e instanceof Error) { - window.showErrorMessage(`Login error: ${e.message}`); - } - this.updateState("DISCONNECTED"); - await this.logout(); - } + get authType(): SdkAuthType | undefined { + return this.apiClient?.config.authType; } - private async _login(interactive = false, force = false): Promise { - if (force) { - await this.logout(); + // Only used through public API + public async login(interactive?: boolean, force?: boolean) { + await this.initialization.promise; + if (this.state !== "CONNECTED" || force) { + await this.configureLogin("api"); } - if (this.state !== "DISCONNECTED") { + } + + private async loginWithSavedAuth(source: AutoLoginSource) { + if (this.savedAuthMutex.locked) { return; } - this.updateState("CONNECTING"); - let projectConfigFile: ProjectConfigFile; - let workspaceClient: WorkspaceClient; - - try { + await this.savedAuthMutex.synchronise(async () => { + const recordEvent = this.telemetry.start(Events.AUTO_LOGIN); try { - projectConfigFile = await ProjectConfigFile.load( - vscodeWorkspace.rootPath!, - this.cli.cliPath - ); - } catch (e) { - if ( - e instanceof ConfigFileError && - e.message.startsWith("Project config file does not exist") - ) { - this.updateState("DISCONNECTED"); - await this.logout(); - return; + await this.disconnect(); + const authProvider = await this.resolveAuth(); + if (authProvider) { + await this.connect(authProvider); } else { - throw e; + await this.logout(); } + recordEvent({success: this.state === "CONNECTED", source}); + } catch (e) { + await this.disconnect(); + recordEvent({success: false, source}); + throw e; } + }); + } - if (!(await projectConfigFile.authProvider.check(true))) { - throw new Error( - `Can't login with ${projectConfigFile.authProvider.describe()}.` - ); - } - - workspaceClient = - projectConfigFile.authProvider.getWorkspaceClient(); - - await workspaceClient.config.authenticate(new Headers()); - - this._databricksWorkspace = await DatabricksWorkspace.load( - workspaceClient, - projectConfigFile.authProvider - ); - } catch (e: any) { - const message = `Can't login to Databricks: ${e.message}`; - NamedLogger.getOrCreate("Extension").error(message, e); - window.showErrorMessage(message); - - this.updateState("DISCONNECTED"); - await this.logout(); - return; + private async loadLegacyProjectConfig() { + try { + return await ProjectConfigFile.loadConfig(this.workspaceUri.fsPath); + } catch (error) { + const logger = NamedLogger.getOrCreate("Extension"); + logger.error(`Error loading legacy config`, error); + return undefined; } + } - if ( - workspaceConfigs.syncDestinationType === "repo" && - (!this._databricksWorkspace.isReposEnabled || - !this._databricksWorkspace.isFilesInReposEnabled) - ) { - let message = ""; - if (!this._databricksWorkspace.isReposEnabled) { - message = - "Repos are not enabled for this workspace. Please enable it in the Databricks UI."; - } else if (!this._databricksWorkspace.isFilesInReposEnabled) { - message = - "Files in Repos is not enabled for this workspace. Please enable it in the Databricks UI."; - } - NamedLogger.getOrCreate("Extension").error(message); - if (interactive) { - const result = await window.showWarningMessage( - message, - "Open Databricks UI" - ); - if (result === "Open Databricks UI") { - const host = await workspaceClient.apiClient.host; - await env.openExternal( - Uri.parse( - host.toString() + - "#setting/accounts/workspace-settings" - ) - ); - } - } + @onError({popup: {prefix: "Failed to login."}}) + @Mutex.synchronise("loginLogoutMutex") + private async resolveAuth() { + this.updateState("CONNECTING"); + const host = await this.configModel.get("host"); + const target = this.configModel.target; + if (host === undefined || target === undefined) { + return; } - this._workspaceClient = workspaceClient; - this._projectConfigFile = projectConfigFile; - - await this._metadataService.setApiClient(workspaceClient?.apiClient); - - if (projectConfigFile.clusterId) { - await this.attachCluster(projectConfigFile.clusterId, true); - } else { - this.updateCluster(undefined); + // Try to load a profile user had previously selected for this target + let savedProfile = (await this.configModel.get("overrides")) + ?.authProfile; + // Check if the profile is saved in the legacy project.json file + if (!savedProfile) { + const legacyConfig = await this.loadLegacyProjectConfig(); + savedProfile = legacyConfig?.profile; } - - if (projectConfigFile.workspacePath) { - await this.attachSyncDestination( - new RemoteUri(projectConfigFile.workspacePath), - true + if (savedProfile !== undefined) { + const authProvider = await ProfileAuthProvider.from( + savedProfile, + this.cli ); - } else { - this.updateSyncDestination(undefined); + if ( + authProvider.host.toString() === host.toString() && + (await authProvider.check()) + ) { + return authProvider; + } } - await this.createWsFsRootDirectory(workspaceClient); - this.updateState("CONNECTED"); - } - - async createWsFsRootDirectory(wsClient: WorkspaceClient) { - if ( - !this.databricksWorkspace || - !workspaceConfigs.enableFilesInWorkspace - ) { - return; + // Try to load any parameters that are hard coded in the bundle + const bundleAuthParams = + await this.configModel.get("preValidateConfig"); + if (bundleAuthParams?.authParams !== undefined) { + throw new Error("Bundle auth params not implemented"); } - const rootDirPath = this.databricksWorkspace.workspaceFsRoot; - const me = this.databricksWorkspace.userName; - let rootDir = await WorkspaceFsEntity.fromPath( - wsClient, - rootDirPath.path - ); - if (rootDir) { + + // Try to load a unique profile that matches the host + const profiles = await getProfilesForHost(host, this.cli); + if (profiles.length !== 1) { return; } - const meDir = await WorkspaceFsEntity.fromPath( - wsClient, - `/Users/${me}` + const authProvider = await ProfileAuthProvider.from( + profiles[0].name, + this.cli ); - if (WorkspaceFsUtils.isDirectory(meDir)) { - rootDir = await meDir.mkdir(rootDirPath.path); - } - if (!rootDir) { - window.showErrorMessage(`Can't find or create ${rootDirPath.path}`); - return; + if (await authProvider.check()) { + return authProvider; } } - async logout() { - if (this._state === "DISCONNECTED") { - return; - } else { - await this.waitForConnect(); - } - - this._projectConfigFile = undefined; - this._workspaceClient = undefined; - this._databricksWorkspace = undefined; - this.updateCluster(undefined); - this.updateSyncDestination(undefined); - this.updateState("DISCONNECTED"); - } - - async configureWorkspace() { - let config: ProjectConfig | undefined; - while (true) { - config = await configureWorkspaceWizard( - this.cli, - this.databricksWorkspace?.host?.toString() || - config?.authProvider?.host.toString() + private async connect(authProvider: AuthProvider): Promise { + try { + await window.withProgress( + { + location: {viewId: "configurationView"}, + title: "Connecting to the workspace", + }, + () => this._connect(authProvider) ); - - if (!config) { - return; - } - - if (!(await config.authProvider.check(false))) { - return; - } - - try { - const workspaceClient = - config.authProvider.getWorkspaceClient(); - - await workspaceClient.config.authenticate(new Headers()); - - await DatabricksWorkspace.load( - workspaceClient, - config.authProvider - ); - } catch (e: any) { - NamedLogger.getOrCreate("Extension").error( - `Connection using "${config.authProvider.describe()}" failed`, - e - ); - - const response = await window.showWarningMessage( - `Connection using "${config.authProvider.describe()}" failed with error: "${ - e.message - }"."`, - "Retry", - "Cancel" + } catch (e) { + NamedLogger.getOrCreate("Extension").error( + `Error connecting to the workspace`, + e + ); + if (e instanceof ProcessError) { + e.showErrorMessage("Error connecting to the workspace."); + } else if (e instanceof Error) { + window.showErrorMessage( + `Error connecting to the workspace: "${e.message}"."` ); - - switch (response) { - case "Retry": - continue; - - case "Cancel": - return; - } } - - break; } - - await this.writeConfigFile(config); - window.showInformationMessage( - `connected to: ${config.authProvider.host}` - ); - - await this.login(true, true); } - private async writeConfigFile(config: ProjectConfig) { - const projectConfigFile = new ProjectConfigFile( - config, - vscodeWorkspace.rootPath!, - this.cli.cliPath + @Mutex.synchronise("loginLogoutMutex") + private async _connect(authProvider: AuthProvider) { + this.updateState("CONNECTING"); + this._workspaceClient = await authProvider.getWorkspaceClient(); + this._databricksWorkspace = await DatabricksWorkspace.load( + this._workspaceClient, + authProvider + ); + await this.configModel.set( + "authProfile", + authProvider.toJSON().profile as string | undefined ); - await projectConfigFile.write(); - } - - async attachCluster( - cluster: Cluster | string, - skipWrite = false - ): Promise { + await this.updateSyncDestinationMapper(); + await this.updateClusterManager(); + await this._metadataService.setApiClient(this.apiClient); try { - if (typeof cluster === "string") { - cluster = await Cluster.fromClusterId( - this._workspaceClient!.apiClient, - cluster - ); - } - - if ( - JSON.stringify(this.cluster?.details) === - JSON.stringify(cluster.details) - ) { - return; - } + await this.configModel.setAuthProvider(authProvider); + } finally { + this.updateState("CONNECTED"); + } + } - if (!skipWrite) { - this._projectConfigFile!.clusterId = cluster.id; - await this._projectConfigFile!.write(); - } + @Mutex.synchronise("loginLogoutMutex") + private async disconnect() { + this._workspaceClient = undefined; + this._databricksWorkspace = undefined; + await this.updateClusterManager(); + await this.updateSyncDestinationMapper(); + this.updateState("DISCONNECTED"); + } - if (cluster.state === "RUNNING") { - cluster - .canExecute() - .then(() => { - this.onDidChangeClusterEmitter.fire(this.cluster); - }) - .catch((e) => { - NamedLogger.getOrCreate(Loggers.Extension).error( - `Error while running code on cluster ${ - (cluster as Cluster).id - }`, - e - ); - }); - } + @onError({popup: {prefix: "Can't logout."}}) + async logout() { + await this.disconnect(); + if (this.configModel.target !== undefined) { + await Promise.all([ + this.configModel.set("authProfile", undefined), + this.configModel.setAuthProvider(undefined), + ]); + } + } - cluster - .hasExecutePerms(this.databricksWorkspace?.user) - .then(() => { - this.onDidChangeClusterEmitter.fire(this.cluster); - }) - .catch((e) => { - NamedLogger.getOrCreate(Loggers.Extension).error( - `Error while fetching permission for cluster ${ - (cluster as Cluster).id - }`, - e - ); - }); - - this.updateCluster(cluster); - } catch (e) { - NamedLogger.getOrCreate("Extension").error( - "Attach Cluster error", - e - ); + @onError({ + popup: {prefix: "Can't configure workspace. "}, + }) + async configureLogin(source: ManualLoginSource) { + if (this.configureLoginMutex.locked) { window.showErrorMessage( - `Error in attaching cluster ${ - typeof cluster === "string" ? cluster : cluster.id - }` + "Databricks: sign in is already in progress" ); - await this.detachCluster(); + return; } + await this.configureLoginMutex.synchronise(async () => { + const recordEvent = this.telemetry.start(Events.MANUAL_LOGIN); + try { + const authProvider = await LoginWizard.run( + this.cli, + this.configModel.target, + await this.configModel.get("host") + ); + if (authProvider) { + await this.connect(authProvider); + } + recordEvent({success: this.state === "CONNECTED", source}); + } catch (e) { + recordEvent({success: false, source}); + throw e; + } + }); } - async detachCluster(): Promise { - if (!this.cluster && this._projectConfigFile?.clusterId === undefined) { + @onError({ + popup: {prefix: "Can't attach cluster. "}, + }) + async attachCluster(clusterId: string): Promise { + if (this.cluster?.id === clusterId) { return; } - - if (this._projectConfigFile) { - this._projectConfigFile.clusterId = undefined; - await this._projectConfigFile.write(); - } - - this.updateCluster(undefined); + await this.configModel.set("clusterId", clusterId); } - async attachSyncDestination( - remoteWorkspace: RemoteUri, - skipWrite = false - ): Promise { - try { - if ( - !vscodeWorkspace.workspaceFolders || - !vscodeWorkspace.workspaceFolders.length - ) { - // TODO how do we handle this? - return; - } - if ( - this.workspaceClient === undefined || - this.databricksWorkspace === undefined - ) { - throw new Error( - "Can't attach a Sync Destination when profile is not connected" - ); - } - if (!(await remoteWorkspace.validate(this))) { - await this.detachSyncDestination(); - return; - } - - if (!skipWrite) { - this._projectConfigFile!.workspacePath = remoteWorkspace.uri; - await this._projectConfigFile!.write(); - } + @onError({ + popup: {prefix: "Can't detach cluster. "}, + }) + async detachCluster(): Promise { + await this.configModel.set("clusterId", undefined); + } - const wsUri = vscodeWorkspace.workspaceFolders[0].uri; - this.updateSyncDestination( - new SyncDestinationMapper(new LocalUri(wsUri), remoteWorkspace) - ); - } catch (e) { - NamedLogger.getOrCreate("Extension").error( - "Attach Sync Destination error", - e - ); + @onError({ + popup: {prefix: "Can't attach sync destination. "}, + }) + async attachSyncDestination(remoteWorkspace: RemoteUri): Promise { + if (!(await remoteWorkspace.validate(this))) { + await this.detachSyncDestination(); window.showErrorMessage( - `Error in attaching sync destination ${remoteWorkspace.path}` + `Can't attach sync destination ${remoteWorkspace.path}` ); - await this.detachSyncDestination(); + return; } + await this.configModel.set("remoteRootPath", remoteWorkspace.path); + await this.configModel.set("remoteRootPath", remoteWorkspace.path); } + @onError({ + popup: {prefix: "Can't detach sync destination. "}, + }) async detachSyncDestination(): Promise { - if ( - !this._syncDestinationMapper && - this._projectConfigFile?.workspacePath === undefined - ) { - return; - } - - if (this._projectConfigFile) { - this._projectConfigFile.workspacePath = undefined; - await this._projectConfigFile.write(); - } - - this.updateSyncDestination(undefined); + await this.configModel.set("remoteRootPath", undefined); } private updateState(newState: ConnectionState) { - if (newState === "DISCONNECTED") { - this._databricksWorkspace = undefined; + if (!this.loginLogoutMutex.locked) { + throw new Error( + "updateState must be called after aquireing the state mutex" + ); } if (this._state !== newState) { this._state = newState; this.onDidChangeStateEmitter.fire(this._state); } - CustomWhenContext.setLoggedIn(this._state === "CONNECTED"); - } - - private updateCluster(newCluster: Cluster | undefined) { - if (this.cluster !== newCluster) { - this._clusterManager?.dispose(); - this._clusterManager = newCluster - ? new ClusterManager(newCluster, () => { - this.onDidChangeClusterEmitter.fire(this.cluster); - }) - : undefined; - this.onDidChangeClusterEmitter.fire(this.cluster); - } - } - - private updateSyncDestination( - newSyncDestination: SyncDestinationMapper | undefined - ) { - if (this._syncDestinationMapper !== newSyncDestination) { - this._syncDestinationMapper = newSyncDestination; - this.onDidChangeSyncDestinationEmitter.fire( - this._syncDestinationMapper - ); - } + this.customWhenContext.setLoggedIn(this._state === "CONNECTED"); } async startCluster() { @@ -554,4 +496,8 @@ export class ConnectionManager { }); } } + + async dispose() { + this.disposables.forEach((d) => d.dispose()); + } } diff --git a/packages/databricks-vscode/src/configuration/DatabricksWorkspace.test.ts b/packages/databricks-vscode/src/configuration/DatabricksWorkspace.test.ts index a51b5e6d2..08b74e7d5 100644 --- a/packages/databricks-vscode/src/configuration/DatabricksWorkspace.test.ts +++ b/packages/databricks-vscode/src/configuration/DatabricksWorkspace.test.ts @@ -4,6 +4,8 @@ import {Uri} from "vscode"; import {ProfileAuthProvider} from "./auth/AuthProvider"; import {DatabricksWorkspace} from "./DatabricksWorkspace"; import {iam} from "@databricks/databricks-sdk"; +import {instance, mock} from "ts-mockito"; +import {CliWrapper} from "../cli/CliWrapper"; describe(__filename, () => { it("create an instance", () => { @@ -17,7 +19,8 @@ describe(__filename, () => { } as const; const authProvider = new ProfileAuthProvider( new URL("https://fabian.databricks.com"), - "DEFAULT" + "DEFAULT", + instance(mock(CliWrapper)) ); const dbWorkspace: DatabricksWorkspace = new DatabricksWorkspace( authProvider, diff --git a/packages/databricks-vscode/src/configuration/DatabricksWorkspace.ts b/packages/databricks-vscode/src/configuration/DatabricksWorkspace.ts index 37fe410ec..38a989d34 100644 --- a/packages/databricks-vscode/src/configuration/DatabricksWorkspace.ts +++ b/packages/databricks-vscode/src/configuration/DatabricksWorkspace.ts @@ -1,9 +1,8 @@ import {WorkspaceClient, iam, logging} from "@databricks/databricks-sdk"; import {Cluster, WorkspaceConf, WorkspaceConfProps} from "../sdk-extensions"; -import {Context, context} from "@databricks/databricks-sdk/dist/context"; +import {context, Context} from "@databricks/databricks-sdk"; import {Uri} from "vscode"; import {Loggers} from "../logger"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {AuthProvider} from "./auth/AuthProvider"; import {RemoteUri} from "../sync/SyncDestination"; @@ -15,13 +14,10 @@ export class DatabricksWorkspace { ) {} /** - * The current root for sync destination folders. Return a Workspace path or a Repo path - * depending on whether files in workspace is enabled for VSCode UI. + * The current root for sync destination folders. */ get currentFsRoot(): RemoteUri { - return workspaceConfigs.enableFilesInWorkspace - ? this.workspaceFsRoot - : this.repoRoot; + return this.workspaceFsRoot; } get workspaceFsRoot(): RemoteUri { @@ -36,8 +32,8 @@ export class DatabricksWorkspace { ); } - get host(): Uri { - return Uri.parse(this._authProvider.host.toString()); + get host(): URL { + return this._authProvider.host; } get authProvider(): AuthProvider { diff --git a/packages/databricks-vscode/src/configuration/LoginWizard.ts b/packages/databricks-vscode/src/configuration/LoginWizard.ts new file mode 100644 index 000000000..3aa95ea50 --- /dev/null +++ b/packages/databricks-vscode/src/configuration/LoginWizard.ts @@ -0,0 +1,556 @@ +import { + commands, + QuickPickItem, + QuickPickItemKind, + window, + ProgressLocation, +} from "vscode"; +import { + InputFlowAction, + InputStep, + MultiStepInput, + ValidationMessageType, +} from "../ui/MultiStepInputWizard"; +import {CliWrapper, ConfigEntry} from "../cli/CliWrapper"; +import { + AuthProvider, + AuthType, + AzureCliAuthProvider, + DatabricksCliAuthProvider, + PersonalAccessTokenAuthProvider, + ProfileAuthProvider, +} from "./auth/AuthProvider"; +import {FileUtils, UrlUtils} from "../utils"; +import {AuthType as SdkAuthType} from "@databricks/databricks-sdk"; +import {randomUUID} from "crypto"; +import ini from "ini"; +import {appendFile, copyFile} from "fs/promises"; +import path from "path"; +import os from "os"; +import {createFile} from "fs-extra"; +import {getDatabricksConfigFilePath} from "../utils/fileUtils"; +import {stat} from "node:fs/promises"; + +interface AuthTypeQuickPickItem extends QuickPickItem { + authType?: SdkAuthType; + profile?: string; + openDatabricksConfigFile?: boolean; +} + +interface State { + host: URL; + authProvider?: AuthProvider; +} + +export class LoginWizard { + private state = {} as Partial; + private readonly title = "Configure Databricks Workspace"; + private _profiles: Array = []; + async getProfiles() { + if (this._profiles.length === 0) { + this._profiles = await listProfiles(this.cliWrapper); + } + return this._profiles; + } + constructor( + private readonly cliWrapper: CliWrapper, + private readonly target?: string + ) {} + + private async inputHost(input: MultiStepInput) { + const items: Array = []; + + if (this.state.host) { + return this.selectAuthMethod.bind(this); + } + + if (process.env.DATABRICKS_HOST) { + items.push({ + label: process.env.DATABRICKS_HOST, + detail: "DATABRICKS_HOST environment variable", + }); + } + + const hostToProfilesMap = new Map(); + (await this.getProfiles()).forEach((profile) => { + hostToProfilesMap.set( + profile.host!.toString(), + (hostToProfilesMap.get(profile.host!.toString()) ?? []).concat( + profile.name + ) + ); + }); + + items.push( + ...Array.from(hostToProfilesMap.entries()).map( + ([host, profiles]) => { + return { + label: host, + detail: `Profiles: ${profiles.join(", ")}`, + }; + } + ) + ); + + const host = await input.showQuickAutoComplete({ + title: this.title, + step: 1, + totalSteps: 2, + placeholder: "Databricks Host (should begin with https://)", + validate: validateDatabricksHost, + shouldResume: async () => { + return false; + }, + items, + ignoreFocusOut: true, + }); + + this.state.host = UrlUtils.normalizeHost(host); + return this.selectAuthMethod.bind(this); + } + + private async checkAuthProvider( + authProvider: AuthProvider, + input: MultiStepInput + ): Promise { + //Hide the input and let the check show it's own messages and UI. + input.hide(); + if (await authProvider.check()) { + input.show(); + return; + } + + const choice = await window.showInformationMessage( + `Authentication using ${authProvider.describe()} failed.`, + {modal: true}, + "Select a different auth method" + ); + if (choice === "Select a different auth method") { + //Show input again with the select auth step. + input.show(); + return this.selectAuthMethod.bind(this); + } + throw InputFlowAction.cancel; + } + + private async getProfileQuickPickItems() { + const items: Array = []; + + const profiles = (await this.getProfiles()) + .filter((profile) => { + return profile.host?.hostname === this.state.host!.hostname; + }) + .map((profile) => { + const humanisedAuthType = humaniseSdkAuthType(profile.authType); + const detail = humanisedAuthType + ? `Authenticate using ${humaniseSdkAuthType( + profile.authType + )}` + : `Authenticate using profile ${profile.name}`; + + return { + label: profile.name, + detail, + authType: profile.authType as SdkAuthType, + profile: profile.name, + }; + }); + + if (profiles.length !== 0) { + items.push( + { + label: "Existing Databricks CLI Profiles", + kind: QuickPickItemKind.Separator, + }, + ...profiles + ); + } + return items; + } + private async selectAuthMethod( + input: MultiStepInput + ): Promise { + const items: Array = []; + items.push(...(await this.getProfileQuickPickItems())); + + const availableAuthMethods = authMethodsForHostname(this.state.host!); + if (availableAuthMethods.length !== 0) { + items.push({ + label: "Create New Databricks CLI Profile", + kind: QuickPickItemKind.Separator, + }); + } + + for (const authMethod of availableAuthMethods) { + switch (authMethod) { + case "pat": + items.push({ + label: "Personal Access Token", + detail: "Create a profile and authenticate using a Personal Access Token", + authType: "pat", + }); + break; + + case "azure-cli": + items.push({ + label: "Azure CLI", + detail: "Create a profile and authenticate using the 'az' command line tool", + authType: "azure-cli", + }); + break; + + case "databricks-cli": + items.push({ + label: "OAuth (user to machine)", + detail: "Create a profile and authenticate using OAuth", + authType: "databricks-cli", + }); + break; + + default: + break; + } + } + + items.push( + { + label: "", + kind: QuickPickItemKind.Separator, + }, + { + label: "Edit Databricks profiles", + detail: "Open ~/.databrickscfg to create or edit profiles", + openDatabricksConfigFile: true, + } + ); + + const pick: AuthTypeQuickPickItem = await input.showQuickPick({ + title: this.title, + step: 2, + totalSteps: 2, + placeholder: "Select authentication method", + items, + ignoreFocusOut: true, + shouldResume: async () => { + return false; + }, + }); + + if (pick.openDatabricksConfigFile) { + await FileUtils.openDatabricksConfigFile(); + return; + } + + if (pick.profile !== undefined) { + const authProvider = await ProfileAuthProvider.from( + pick.profile, + this.cliWrapper + ); + const nextStep = await this.checkAuthProvider(authProvider, input); + if (nextStep) { + return nextStep; + } + this.state.authProvider = authProvider; + return; + } + + return (input: MultiStepInput) => this.createNewProfile(input, pick); + } + + private async createNewProfile( + input: MultiStepInput, + pick: AuthTypeQuickPickItem + ) { + let initialValue = this.target ?? ""; + + // If the initialValue profile already exists, then create a unique name. + const profiles = await this.getProfiles(); + if (profiles.find((profile) => profile.name === initialValue)) { + const suffix = randomUUID().slice(0, 8); + initialValue = `${this.target ?? "dev"}-${suffix}`; + } + + const profileName = await input.showInputBox({ + title: "Enter a name for the new profile", + step: 3, + totalSteps: 3, + placeholder: "Enter a name for the new profile", + initialValue, + validate: async (value) => { + if (value.length === 0) { + return { + message: "Profile name cannot be empty", + type: "error", + }; + } + if (profiles.find((profile) => profile.name === value)) { + return { + message: `Profile ${value} already exists`, + type: "error", + }; + } + }, + ignoreFocusOut: true, + }); + + if (profileName === undefined) { + return; + } + + let authProvider: + | AzureCliAuthProvider + | DatabricksCliAuthProvider + | PersonalAccessTokenAuthProvider; + switch (pick.authType) { + case "azure-cli": + authProvider = new AzureCliAuthProvider( + this.state.host!, + this.cliWrapper + ); + break; + + case "databricks-cli": + authProvider = new DatabricksCliAuthProvider( + this.state.host!, + this.cliWrapper.cliPath, + this.cliWrapper + ); + break; + + case "pat": + { + const token = await collectTokenForPatAuth( + this.state.host!, + input, + 4, + 4 + ); + if (token === undefined) { + // Token can never be undefined unless the users cancels the whole process. + // Therefore, we can safely return here. + return; + } + authProvider = new PersonalAccessTokenAuthProvider( + this.state.host!, + token, + this.cliWrapper + ); + } + break; + default: + throw new Error( + `Unknown auth type: ${pick.authType} for profile creation` + ); + } + + const checkResult = await this.checkAuthProvider(authProvider, input); + if (checkResult) { + return checkResult; + } + + this.state.authProvider = await saveNewProfile( + profileName, + authProvider, + this.cliWrapper + ); + } + + static async run( + cliWrapper: CliWrapper, + target?: string, + host?: URL + ): Promise { + const wizard = new LoginWizard(cliWrapper, target); + if (host) { + wizard.state.host = host; + } + await MultiStepInput.run(wizard.inputHost.bind(wizard)); + if (!wizard.state.host || !wizard.state.authProvider) { + return; + } + + return wizard.state.authProvider; + } +} + +export async function saveNewProfile( + profileName: string, + authProvider: AuthProvider, + cli: CliWrapper +) { + const iniData = authProvider.toIni(); + if (!iniData) { + throw new Error("Can't save empty auth provider to a profile"); + } + + const configFilePath: string = getDatabricksConfigFilePath().fsPath; + let shouldBackup = true; + try { + await stat(configFilePath); + } catch (e) { + shouldBackup = false; + await createFile(configFilePath); + window.showInformationMessage( + `Created a new .databrickscfg file at ${configFilePath}` + ); + } + + const profile: any = {}; + profile[profileName] = Object.fromEntries( + Object.entries(iniData).filter((kv) => kv[1] !== undefined) + ); + const iniStr = ini.stringify(profile); + const finalStr = `${os.EOL};This profile is autogenerated by the Databricks Extension for VS Code${os.EOL}${iniStr}`; + + if (shouldBackup) { + // Create a backup for .databrickscfg + const backup = path.join( + path.dirname(configFilePath), + `.databrickscfg.${Date.now()}.bak` + ); + await copyFile(configFilePath, backup); + window.showInformationMessage( + `Created a backup for .databrickscfg at ${backup}` + ); + } + + // Write the new profile to .databrickscfg + await appendFile(configFilePath, finalStr); + + return await ProfileAuthProvider.from(profileName, cli, true); +} + +function humaniseSdkAuthType(sdkAuthType: string) { + switch (sdkAuthType) { + case "pat": + return "Personal Access Token"; + case "basic": + return "Username and Password"; + case "azure-cli": + return "Azure CLI"; + case "azure-client-secret": + return "Azure Client Secret"; + case "google-id": + return "Google Service Account"; + case "databricks-cli": + return "OAuth (User to Machine)"; + case "oauth-m2m": + return "OAuth (Machine to Machine)"; + default: + return sdkAuthType; + } +} + +export async function listProfiles(cliWrapper: CliWrapper) { + return await window.withProgress( + { + location: ProgressLocation.Notification, + title: "Loading Databricks profiles", + }, + async () => { + const cfgPath = FileUtils.getDatabricksConfigFilePath().fsPath; + try { + await stat(cfgPath); + } catch (e) { + return []; + } + const allProfiles = await cliWrapper.listProfiles(cfgPath); + const profiles = allProfiles.filter((profile) => { + try { + UrlUtils.normalizeHost(profile.host!.toString()); + return true; + } catch (e) { + return false; + } + }); + return profiles; + } + ); +} + +export async function getProfilesForHost(host: URL, cliWrapper: CliWrapper) { + return (await listProfiles(cliWrapper)).filter( + (profile) => profile.host?.toString() === host.toString() + ); +} + +async function validateDatabricksHost( + host: string +): Promise { + try { + const url = UrlUtils.normalizeHost(host); + if ( + !url.hostname.match( + /(\.databricks\.azure\.us|\.databricks\.azure\.cn|\.azuredatabricks\.net|\.gcp\.databricks\.com|\.cloud\.databricks\.com|\.dev\.databricks\.com)$/ + ) + ) { + return { + message: + "This is not a standard Databricks URL. Some features may not work as expected.", + type: "warning", + }; + } + } catch (e: any) { + return e.message; + } +} + +function authMethodsForHostname(host: URL): Array { + if (UrlUtils.isAzureHost(host)) { + return ["databricks-cli", "azure-cli", "pat"]; + } + + if (UrlUtils.isGcpHost(host)) { + return ["databricks-cli", "google-id", "pat"]; + } + + if (UrlUtils.isAwsHost(host)) { + return ["databricks-cli", "pat"]; + } + + return ["pat"]; +} + +async function collectTokenForPatAuth( + host: URL, + input: MultiStepInput, + step: number, + totalSteps: number +) { + const token = await input.showQuickAutoComplete({ + title: "Enter Personal Access Token", + step, + totalSteps, + validate: async (value) => { + if (value.length === 0) { + return { + message: "Token cannot be empty", + type: "error", + }; + } + }, + placeholder: "Enter Personal Access Token", + ignoreFocusOut: true, + shouldResume: async () => false, + items: [ + { + label: "Create a new Personal Access Token", + detail: "Open the Databricks UI to create a new Personal Access Token", + alwaysShow: true, + }, + ], + }); + + if (token === undefined) { + return; + } + + if (token === "Create a new Personal Access Token") { + commands.executeCommand("databricks.utils.openExternal", { + url: `${host.toString()}settings/user/developer/access-tokens`, + }); + return collectTokenForPatAuth(host, input, step, totalSteps); + } + + return token; +} diff --git a/packages/databricks-vscode/src/configuration/auth/AuthProvider.ts b/packages/databricks-vscode/src/configuration/auth/AuthProvider.ts index a9ec660e6..37b816a78 100644 --- a/packages/databricks-vscode/src/configuration/auth/AuthProvider.ts +++ b/packages/databricks-vscode/src/configuration/auth/AuthProvider.ts @@ -3,7 +3,9 @@ import { Config, ProductVersion, WorkspaceClient, + logging, } from "@databricks/databricks-sdk"; +import {CancellationToken, ProgressLocation, window} from "vscode"; import {normalizeHost} from "../../utils/urlUtils"; import {workspaceConfigs} from "../../vscode-objs/WorkspaceConfigs"; @@ -13,14 +15,23 @@ const extensionVersion = require("../../../package.json") import {AzureCliCheck} from "./AzureCliCheck"; import {DatabricksCliCheck} from "./DatabricksCliCheck"; +import {Loggers} from "../../logger"; +import {CliWrapper} from "../../cli/CliWrapper"; // TODO: Resolve this with SDK's AuthType. -export type AuthType = "azure-cli" | "google-id" | "databricks-cli" | "profile"; +export type AuthType = + | "azure-cli" + | "databricks-cli" + | "google-id" + | "profile" + | "pat"; export abstract class AuthProvider { constructor( private readonly _host: URL, - private readonly _authType: AuthType + private readonly _authType: AuthType, + private readonly _cli: CliWrapper, + private checked: boolean = false ) {} get host(): URL { @@ -35,11 +46,12 @@ export abstract class AuthProvider { * Used to display the auth method in the UI */ abstract describe(): string; - abstract toJSON(): Record; + abstract toJSON(): Record; abstract toEnv(): Record; + abstract toIni(): Record | undefined; - getWorkspaceClient(): WorkspaceClient { - const config = this.getSdkConfig(); + async getWorkspaceClient(): Promise { + const config = await this.getSdkConfig(); return new WorkspaceClient(config, { product: "databricks-vscode", @@ -47,17 +59,88 @@ export abstract class AuthProvider { }); } - // eslint-disable-next-line @typescript-eslint/no-unused-vars - async check(silent: boolean): Promise { - return true; + /** + * Check if the currently selected auth method can be used to login to Databricks. + * This function should not throw an error and each implementing class must + * handle it's own error messages and retry loops. + */ + protected abstract _check(token?: CancellationToken): Promise; + + public async check( + force = false, + showProgress = true, + cancellationToken?: CancellationToken + ): Promise { + if (force) { + this.checked = false; + } + if (this.checked) { + return true; + } + + const checkFn = async (token?: CancellationToken) => { + this.checked = await this._check(token); + }; + + if (!showProgress) { + await checkFn(cancellationToken); + return this.checked; + } + + let cancellationRequested = false; + let task: Promise = Promise.resolve(); + await window.withProgress( + { + location: ProgressLocation.Notification, + title: `Databricks: Logging in using ${this.describe()}`, + cancellable: true, + }, + async (progress, token) => { + task = checkFn(token); + await Promise.race([ + task, + new Promise((resolve) => + token.onCancellationRequested(resolve) + ), + ]); + cancellationRequested = token.isCancellationRequested; + } + ); + if (cancellationRequested) { + await window.withProgress( + { + location: ProgressLocation.Notification, + title: `Databricks: Cancelling login using ${this.describe()}`, + }, + async () => { + await task; + } + ); + window.showErrorMessage("Databricks: Login cancelled"); + this.checked = false; + } + + if (this.checked) { + window.showInformationMessage( + `Databricks: Successfully logged in using ${this.describe()}` + ); + } + + return this.checked; + } + async getSdkConfig(): Promise { + const config = this._getSdkConfig(); + await config.ensureResolved(); + if (config.databricksCliPath === undefined) { + config.databricksCliPath = this._cli.cliPath; + } + + return config; } - protected abstract getSdkConfig(): Config; + protected abstract _getSdkConfig(): Config; - static fromJSON( - json: Record, - databricksPath: string - ): AuthProvider { + static fromJSON(json: Record, cli: CliWrapper): AuthProvider { const host = json.host instanceof URL ? json.host @@ -79,33 +162,74 @@ export abstract class AuthProvider { ); case "databricks-cli": - return new DatabricksCliAuthProvider(host, databricksPath); + return new DatabricksCliAuthProvider( + host, + json.databricksPath ?? cli.cliPath, + cli + ); case "profile": if (!json.profile) { throw new Error("Missing profile"); } - return new ProfileAuthProvider(host, json.profile); + return new ProfileAuthProvider(host, json.profile, cli); default: throw new Error(`Unknown auth type: ${json.authType}`); } } + + static fromSdkConfig(config: Config, cli: CliWrapper): AuthProvider { + if (!config.host) { + throw new Error("Missing host"); + } + const host = normalizeHost(config.host); + + switch (config.authType) { + case "azure-cli": + return new AzureCliAuthProvider( + host, + cli, + config.azureTenantId, + config.azureLoginAppId + ); + + case "databricks-cli": + return new DatabricksCliAuthProvider( + host, + config.databricksCliPath ?? cli.cliPath, + cli + ); + + default: + if (config.profile) { + return new ProfileAuthProvider(host, config.profile, cli); + } + throw new Error(`Unknown auth type: ${config.authType}`); + } + } } export class ProfileAuthProvider extends AuthProvider { + static async from(profile: string, cli: CliWrapper, checked = false) { + const host = await ProfileAuthProvider.getSdkConfig(profile).getHost(); + return new ProfileAuthProvider(host, profile, cli, checked); + } + constructor( host: URL, - private readonly profile: string + readonly profile: string, + private readonly cli: CliWrapper, + checked = false ) { - super(host, "profile"); + super(host, "profile", cli, checked); } describe(): string { return `Profile '${this.profile}'`; } - toJSON(): Record { + toJSON() { return { host: this.host.toString(), authType: this.authType, @@ -120,42 +244,92 @@ export class ProfileAuthProvider extends AuthProvider { }; } - getSdkConfig(): Config { + toIni() { + return undefined; + } + + private static getSdkConfig(profile: string): Config { return new Config({ - profile: this.profile, - configFile: - workspaceConfigs.databrickscfgLocation ?? - process.env.DATABRICKS_CONFIG_FILE, + profile: profile, + configFile: workspaceConfigs.databrickscfgLocation, env: {}, }); } + + protected _getSdkConfig(): Config { + return ProfileAuthProvider.getSdkConfig(this.profile); + } + + protected async _check(cancellationToken?: CancellationToken) { + while (cancellationToken?.isCancellationRequested !== true) { + try { + const sdkConfig = await this.getSdkConfig(); + const authProvider = AuthProvider.fromSdkConfig( + sdkConfig, + this.cli + ); + + if (authProvider instanceof ProfileAuthProvider) { + const workspaceClient = await this.getWorkspaceClient(); + await workspaceClient.currentUser.me(); + return true; + } + + return await authProvider.check( + false, + false, + cancellationToken + ); + } catch (e) { + let message: string = `Can't login with config profile ${this.profile}`; + if (e instanceof Error) { + message = `Can't login with config profile ${this.profile}: ${e.message}`; + } + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + message, + e + ); + const choice = await window.showErrorMessage( + message, + "Retry", + "Cancel" + ); + if (choice === "Retry") { + continue; + } + return false; + } + } + return false; + } } export class DatabricksCliAuthProvider extends AuthProvider { constructor( host: URL, - readonly databricksPath: string + readonly cliPath: string, + cli: CliWrapper ) { - super(host, "databricks-cli"); + super(host, "databricks-cli", cli); } describe(): string { return "OAuth U2M"; } - toJSON(): Record { + toJSON() { return { host: this.host.toString(), authType: this.authType, - databricksPath: this.databricksPath, + databricksPath: this.cliPath, }; } - getSdkConfig(): Config { + _getSdkConfig(): Config { return new Config({ host: this.host.toString(), authType: "databricks-cli", - databricksCliPath: this.databricksPath, + databricksCliPath: this.cliPath, }); } @@ -163,13 +337,21 @@ export class DatabricksCliAuthProvider extends AuthProvider { return { DATABRICKS_HOST: this.host.toString(), DATABRICKS_AUTH_TYPE: "databricks-cli", - DATABRICKS_CLI_PATH: this.databricksPath, }; } - async check(silent: boolean): Promise { + toIni() { + return { + host: this.host.toString(), + auth_type: "databricks-cli", + }; + } + + protected async _check( + cancellationToken?: CancellationToken + ): Promise { const databricksCliCheck = new DatabricksCliCheck(this); - return databricksCliCheck.check(silent); + return databricksCliCheck.check(cancellationToken); } } @@ -177,8 +359,8 @@ export class AzureCliAuthProvider extends AuthProvider { private _tenantId?: string; private _appId?: string; - constructor(host: URL, tenantId?: string, appId?: string) { - super(host, "azure-cli"); + constructor(host: URL, cli: CliWrapper, tenantId?: string, appId?: string) { + super(host, "azure-cli", cli); this._tenantId = tenantId; this._appId = appId; @@ -196,7 +378,7 @@ export class AzureCliAuthProvider extends AuthProvider { return "Azure CLI"; } - toJSON(): Record { + toJSON() { return { host: this.host.toString(), authType: this.authType, @@ -205,7 +387,7 @@ export class AzureCliAuthProvider extends AuthProvider { }; } - getSdkConfig(): Config { + _getSdkConfig(): Config { return new Config({ host: this.host.toString(), authType: "azure-cli", @@ -214,6 +396,14 @@ export class AzureCliAuthProvider extends AuthProvider { }); } + toIni() { + return { + host: this.host.toString(), + auth_type: "azure-cli", + azure_login_app_id: this.appId, + }; + } + toEnv(): Record { const envVars: Record = { DATABRICKS_HOST: this.host.toString(), @@ -225,11 +415,84 @@ export class AzureCliAuthProvider extends AuthProvider { return envVars; } - async check(silent: boolean): Promise { + protected async _check( + cancellationToken?: CancellationToken + ): Promise { const cliCheck = new AzureCliCheck(this); - const result = await cliCheck.check(silent); + const result = await cliCheck.check(cancellationToken); this._tenantId = cliCheck.tenantId; this._appId = cliCheck.azureLoginAppId; return result; } } + +export class PersonalAccessTokenAuthProvider extends AuthProvider { + constructor( + host: URL, + private readonly token: string, + cli: CliWrapper + ) { + super(host, "pat", cli); + } + + describe(): string { + return "Personal Access Token"; + } + toJSON(): Record { + return { + host: this.host.toString(), + authType: this.authType, + token: this.token, + }; + } + toEnv(): Record { + return { + DATABRICKS_HOST: this.host.toString(), + DATABRICKS_AUTH_TYPE: this.authType, + DATABRICKS_TOKEN: this.token, + }; + } + toIni(): Record | undefined { + return { + host: this.host.toString(), + token: this.token, + }; + } + protected async _check( + cancellationToken?: CancellationToken + ): Promise { + while (cancellationToken?.isCancellationRequested !== true) { + try { + const workspaceClient = await this.getWorkspaceClient(); + await workspaceClient.currentUser.me(); + return true; + } catch (e) { + let message: string = `Can't login with the provided Personal Access Token`; + if (e instanceof Error) { + message = `Can't login with the provided Personal Access Token: ${e.message}`; + } + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + message, + e + ); + const choice = await window.showErrorMessage( + message, + "Retry", + "Cancel" + ); + if (choice === "Retry") { + continue; + } + return false; + } + } + return false; + } + protected _getSdkConfig(): Config { + return new Config({ + host: this.host.toString(), + authType: "pat", + token: this.token, + }); + } +} diff --git a/packages/databricks-vscode/src/configuration/auth/AzureCliCheck.ts b/packages/databricks-vscode/src/configuration/auth/AzureCliCheck.ts index 52e85751f..e67726b40 100644 --- a/packages/databricks-vscode/src/configuration/auth/AzureCliCheck.ts +++ b/packages/databricks-vscode/src/configuration/auth/AzureCliCheck.ts @@ -1,13 +1,19 @@ import { - ExecUtils, + Context, ProductVersion, WorkspaceClient, logging, } from "@databricks/databricks-sdk"; -import {commands, Disposable, Uri, window} from "vscode"; +import {CancellationToken, commands, Disposable, Uri, window} from "vscode"; import {Loggers} from "../../logger"; import {AzureCliAuthProvider} from "./AuthProvider"; import {orchestrate, OrchestrationLoopError, Step} from "./orchestrate"; +import {ShellUtils} from "../../utils"; +import {execFile} from "../../cli/CliWrapper"; +import { + FileNotFoundException, + isFileNotFound, +} from "@databricks/databricks-sdk/dist/config/execUtils"; // eslint-disable-next-line @typescript-eslint/naming-convention const {NamedLogger} = logging; @@ -25,6 +31,25 @@ type AzureStepName = | "isLoggedIn" | "loginAzureCli"; +async function execFileWithShell( + cmd: string, + args: Array, + cancellationToken?: CancellationToken +): Promise<{ + stdout: string; + stderr: string; +}> { + try { + return await execFile(cmd, args, {shell: true}, cancellationToken); + } catch (e) { + if (isFileNotFound(e)) { + throw new FileNotFoundException(e.message); + } else { + throw e; + } + } +} + export class AzureCliCheck implements Disposable { private disposables: Disposable[] = []; private isCodeSpaces: boolean; @@ -46,7 +71,9 @@ export class AzureCliCheck implements Disposable { this.disposables = []; } - public async check(silent = false): Promise { + public async check( + cancellationToken?: CancellationToken + ): Promise { this.tenantId = this.authProvider.tenantId; let loginAttempts = 0; @@ -54,7 +81,10 @@ export class AzureCliCheck implements Disposable { const steps: Record> = { tryLogin: async () => { loginAttempts += 1; - const result = await this.tryLogin(this.authProvider.host); + const result = await this.tryLogin( + this.authProvider.host, + cancellationToken + ); if (result.iss) { this.tenantId = result.iss; return { @@ -94,7 +124,7 @@ export class AzureCliCheck implements Disposable { } }, findCli: async () => { - if (await this.hasAzureCli()) { + if (await this.hasAzureCli(cancellationToken)) { return { type: "next", next: "isLoggedIn", @@ -114,7 +144,7 @@ export class AzureCliCheck implements Disposable { }; }, isLoggedIn: async () => { - if (await this.isAzureCliLoggedIn()) { + if (await this.isAzureCliLoggedIn(cancellationToken)) { return { type: "next", next: "tryLogin", @@ -126,7 +156,9 @@ export class AzureCliCheck implements Disposable { }; }, loginAzureCli: async () => { - if (await this.loginAzureCli(this.tenantId)) { + if ( + await this.loginAzureCli(this.tenantId, cancellationToken) + ) { return { type: "next", next: "tryLogin", @@ -146,7 +178,8 @@ export class AzureCliCheck implements Disposable { steps, "findCli", 20, - this.logger + this.logger, + cancellationToken ); } catch (e: any) { let message: string; @@ -156,19 +189,18 @@ export class AzureCliCheck implements Disposable { message = e.message; } + NamedLogger.getOrCreate(Loggers.Extension).error(message, e); window.showErrorMessage(message); return false; } - if (result && !silent) { - window.showInformationMessage( - "Databricks: Successfully logged in with Azure CLI" - ); - } return result; } - private async tryLogin(host: URL): Promise<{ + private async tryLogin( + host: URL, + cancellationToken?: CancellationToken + ): Promise<{ iss?: string; aud?: string; canLogin: boolean; @@ -187,7 +219,9 @@ export class AzureCliCheck implements Disposable { } ); try { - await workspaceClient.currentUser.me(); + await workspaceClient.currentUser.me( + new Context({cancellationToken}) + ); } catch (e: any) { // parse error message let m = e.message.match( @@ -229,11 +263,15 @@ export class AzureCliCheck implements Disposable { } // check if Azure CLI is installed - public async hasAzureCli(): Promise { + public async hasAzureCli( + cancellationToken?: CancellationToken + ): Promise { try { - const {stdout} = await ExecUtils.execFileWithShell(this.azBinPath, [ - "--version", - ]); + const {stdout} = await execFileWithShell( + this.azBinPath, + ["--version"], + cancellationToken + ); if (stdout.indexOf("azure-cli") !== -1) { return true; } @@ -262,18 +300,25 @@ export class AzureCliCheck implements Disposable { } // check if Azure CLI is logged in - public async isAzureCliLoggedIn(): Promise { + public async isAzureCliLoggedIn( + cancellationToken?: CancellationToken + ): Promise { try { - await ExecUtils.execFileWithShell(this.azBinPath, [ - "cloud", - "set", - "--name", - this.getAzureCloud(this.authProvider.host), - ]); + await execFileWithShell( + this.azBinPath, + [ + "cloud", + "set", + "--name", + this.getAzureCloud(this.authProvider.host), + ], + cancellationToken + ); - const {stdout, stderr} = await ExecUtils.execFileWithShell( + const {stdout, stderr} = await execFileWithShell( this.azBinPath, - ["account", "list"] + ["account", "list"], + cancellationToken ); if (stdout === "[]") { return false; @@ -298,7 +343,10 @@ export class AzureCliCheck implements Disposable { } // login using azure CLI - public async loginAzureCli(tenant = ""): Promise { + public async loginAzureCli( + tenant = "", + cancellationToken?: CancellationToken + ): Promise { let message = 'You need to run "az login" to login with Azure.'; if (tenant) { message = `You need to tun "az login --allow-no-subscriptions -t ${tenant}" to login with Azure.`; @@ -321,7 +369,11 @@ export class AzureCliCheck implements Disposable { this.azBinPath } login --allow-no-subscriptions ${useDeviceCode} ${ tenant ? "-t " + tenant : "" - }; echo "Press any key to close the terminal and continue ..."; read; exit` + }; echo "Press any key to close the terminal and continue ..."; ${ShellUtils.readCmd()}; exit` + ); + + cancellationToken?.onCancellationRequested(() => + terminal.dispose() ); return await Promise.race([ @@ -335,7 +387,10 @@ export class AzureCliCheck implements Disposable { this.disposables.push( window.onDidCloseTerminal((t) => { if (t === terminal) { - resolve(true); + resolve( + cancellationToken?.isCancellationRequested !== + true + ); this.dispose(); } }) diff --git a/packages/databricks-vscode/src/configuration/auth/DatabricksCliCheck.ts b/packages/databricks-vscode/src/configuration/auth/DatabricksCliCheck.ts index a190b7086..1daab0628 100644 --- a/packages/databricks-vscode/src/configuration/auth/DatabricksCliCheck.ts +++ b/packages/databricks-vscode/src/configuration/auth/DatabricksCliCheck.ts @@ -1,11 +1,15 @@ import { - ExecUtils, + CancellationToken, + Context, ProductVersion, WorkspaceClient, + logging, } from "@databricks/databricks-sdk"; import {Disposable, window} from "vscode"; import {DatabricksCliAuthProvider} from "./AuthProvider"; import {orchestrate, OrchestrationLoopError, Step} from "./orchestrate"; +import {Loggers} from "../../logger"; +import {execFile} from "../../cli/CliWrapper"; // eslint-disable-next-line @typescript-eslint/no-var-requires const extensionVersion = require("../../../package.json") @@ -23,10 +27,10 @@ export class DatabricksCliCheck implements Disposable { this.disposables = []; } - async check(silent: boolean): Promise { + async check(cancellationToken?: CancellationToken): Promise { const steps: Record> = { tryLogin: async () => { - if (await this.tryLogin()) { + if (await this.tryLogin(cancellationToken)) { return {type: "success", result: true}; } else { return {type: "next", next: "login"}; @@ -34,7 +38,7 @@ export class DatabricksCliCheck implements Disposable { }, login: async () => { try { - await this.login(); + await this.login(cancellationToken); } catch (e: any) { return { type: "error", @@ -47,7 +51,13 @@ export class DatabricksCliCheck implements Disposable { let result: boolean; try { - result = await orchestrate(steps, "tryLogin", 6); + result = await orchestrate( + steps, + "tryLogin", + 6, + undefined, + cancellationToken + ); } catch (e: any) { let message: string; if (e instanceof OrchestrationLoopError) { @@ -55,26 +65,25 @@ export class DatabricksCliCheck implements Disposable { } else { message = e.message; } - + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + message, + e + ); window.showErrorMessage(message); return false; } - if (result && !silent) { - window.showInformationMessage( - "Databricks: Successfully logged in with Databricks CLI" - ); - } - return result; } - private async tryLogin(): Promise { + private async tryLogin( + cancellationToken?: CancellationToken + ): Promise { const workspaceClient = new WorkspaceClient( { host: this.authProvider.host.toString(), authType: "databricks-cli", - databricksCliPath: this.authProvider.databricksPath, + databricksCliPath: this.authProvider.cliPath, }, { product: "databricks-vscode", @@ -83,7 +92,9 @@ export class DatabricksCliCheck implements Disposable { ); try { - await workspaceClient.currentUser.me(); + await workspaceClient.currentUser.me( + new Context({cancellationToken}) + ); } catch (e: any) { return false; } @@ -91,19 +102,17 @@ export class DatabricksCliCheck implements Disposable { return true; } - private async login(): Promise { + private async login(cancellationToken?: CancellationToken): Promise { try { - await ExecUtils.execFile(this.authProvider.databricksPath, [ - "auth", - "login", - "--host", - this.authProvider.host.toString(), - ]); + await execFile( + this.authProvider.cliPath, + ["auth", "login", "--host", this.authProvider.host.toString()], + {}, + cancellationToken + ); } catch (e: any) { throw new Error( - `Login failed with Databricks CLI failed: ${ - e.stderr || e.message - }` + `Login failed with Databricks CLI: ${e.stderr || e.message}` ); } } diff --git a/packages/databricks-vscode/src/configuration/auth/orchestrate.ts b/packages/databricks-vscode/src/configuration/auth/orchestrate.ts index 1f262f0d4..ef9421990 100644 --- a/packages/databricks-vscode/src/configuration/auth/orchestrate.ts +++ b/packages/databricks-vscode/src/configuration/auth/orchestrate.ts @@ -1,10 +1,8 @@ import {logging} from "@databricks/databricks-sdk"; - -export type Step = () => Promise< - SuccessResult | NextResult | ErrorResult ->; +import {CancellationToken} from "vscode"; type StepResult = SuccessResult | NextResult | ErrorResult; +export type Step = () => Promise>; export interface SuccessResult { type: "success"; @@ -31,18 +29,44 @@ export async function orchestrate( steps: Record>, start: KEYS, maxSteps = 20, - logger?: logging.NamedLogger + logger?: logging.NamedLogger, + cancellationToken?: CancellationToken ): Promise { let counter = 0; let step: KEYS | undefined = start; - while (step && steps[step]) { + function isCancelled() { + return cancellationToken?.isCancellationRequested === true; + } + while (step && steps[step] && !isCancelled()) { counter += 1; if (counter > maxSteps) { throw new OrchestrationLoopError(); } - const result: StepResult = await steps[step](); - logger?.info(`Azire CLI check: ${step}`, result); + + let result: StepResult | undefined = undefined; + const task: Promise | undefined> = (async () => { + return await steps[step!](); + })().catch((e) => { + if (!isCancelled()) { + throw e; + } + return undefined; + }); + + result = await Promise.race([ + task, + new Promise((resolve) => { + cancellationToken?.onCancellationRequested(() => + resolve(undefined) + ); + }), + ]); + if (result === undefined || isCancelled()) { + throw new OrchestrationLoopError(); + } + + logger?.info(`Auth check: ${step}`, result); if (result.type === "error") { throw result.error; @@ -56,5 +80,5 @@ export async function orchestrate( step = result.next; } } - throw new Error("Missing return step"); + throw new OrchestrationLoopError(); } diff --git a/packages/databricks-vscode/src/configuration/configureWorkspaceWizard.ts b/packages/databricks-vscode/src/configuration/configureWorkspaceWizard.ts deleted file mode 100644 index 367598444..000000000 --- a/packages/databricks-vscode/src/configuration/configureWorkspaceWizard.ts +++ /dev/null @@ -1,250 +0,0 @@ -import {commands, QuickPickItem, QuickPickItemKind} from "vscode"; -import {CliWrapper, ConfigEntry} from "../cli/CliWrapper"; -import {MultiStepInput, ValidationMessageType} from "../ui/wizard"; -import { - isAwsHost, - isAzureHost, - isGcpHost, - normalizeHost, -} from "../utils/urlUtils"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; -import {AuthProvider, AuthType} from "./auth/AuthProvider"; -import {ProjectConfig} from "../file-managers/ProjectConfigFile"; - -interface AuthTypeQuickPickItem extends QuickPickItem { - authType: AuthType | "new-profile" | "none"; - profile?: string; -} - -interface State { - host: URL; - authType: AuthType; - profile?: string; - token?: string; - databricksPath?: string; -} - -export async function configureWorkspaceWizard( - cliWrapper: CliWrapper, - host?: string -): Promise { - const title = "Configure Databricks Workspace"; - - async function collectInputs(): Promise { - const state = { - host, - } as Partial; - await MultiStepInput.run((input) => inputHost(input, state)); - return state as State; - } - - async function inputHost(input: MultiStepInput, state: Partial) { - const items: Array = []; - - if (state.host) { - items.push({ - label: state.host.toString(), - detail: "Currently selected host", - }); - } - - if (process.env.DATABRICKS_HOST) { - items.push({ - label: process.env.DATABRICKS_HOST, - detail: "DATABRICKS_HOST environment variable", - }); - } - - const profiles = await listProfiles(cliWrapper); - items.push( - ...profiles.map((profile) => { - return { - label: profile.host!.toString(), - detail: `Profile: ${profile.name}`, - }; - }) - ); - - const host = await input.showQuickAutoComplete({ - title, - step: 1, - totalSteps: 2, - prompt: "Databricks Host (should begin with https://)", - validate: validateDatabricksHost, - shouldResume: async () => { - return false; - }, - items, - ignoreFocusOut: true, - }); - - state.host = normalizeHost(host); - return (input: MultiStepInput) => selectAuthMethod(input, state); - } - - async function selectAuthMethod( - input: MultiStepInput, - state: Partial - ) { - const items: Array = []; - let profiles: Array = []; - - for (const authMethod of authMethodsForHostname(state.host!)) { - switch (authMethod) { - case "azure-cli": - items.push({ - label: "Azure CLI", - detail: "Authenticate using the 'az' command line tool", - authType: "azure-cli", - }); - break; - - case "databricks-cli": - items.push({ - label: "OAuth (user to machine)", - detail: "Authenticate using OAuth", - authType: "databricks-cli", - }); - break; - - case "profile": - items.push({ - label: "Databricks CLI Profiles", - kind: QuickPickItemKind.Separator, - authType: "none", - }); - - profiles = await listProfiles(cliWrapper); - - items.push( - ...profiles - .filter((profile) => { - return ( - profile.host?.hostname === - state.host!.hostname - ); - }) - .map((profile) => { - return { - label: profile.name, - detail: `Authenticate using the ${profile.name} profile`, - authType: "profile" as const, - profile: profile.name, - }; - }) - ); - - items.push({ - label: "", - kind: QuickPickItemKind.Separator, - authType: "none", - }); - - items.push({ - label: "Edit Databricks profiles", - detail: "Open ~/.databrickscfg to create a new profile", - authType: "new-profile", - }); - - break; - - default: - break; - } - } - - const pick: AuthTypeQuickPickItem = await input.showQuickPick({ - title, - step: 2, - totalSteps: 2, - placeholder: "Select authentication method", - items, - ignoreFocusOut: true, - shouldResume: async () => { - return false; - }, - }); - - switch (pick.authType) { - case "azure-cli": - state.authType = pick.authType; - break; - - case "databricks-cli": - state.authType = pick.authType; - state.databricksPath = cliWrapper.cliPath; - break; - - case "profile": - state.authType = pick.authType; - state.profile = pick.profile; - break; - - case "new-profile": - await commands.executeCommand( - "databricks.connection.openDatabricksConfigFile" - ); - } - } - - const state = await collectInputs(); - if (!state.host || !state.authType) { - return; - } - - return { - authProvider: AuthProvider.fromJSON(state, cliWrapper.cliPath), - }; -} - -async function listProfiles(cliWrapper: CliWrapper) { - const profiles = ( - await cliWrapper.listProfiles(workspaceConfigs.databrickscfgLocation) - ).filter((profile) => { - try { - normalizeHost(profile.host!.toString()); - return true; - } catch (e) { - return false; - } - }); - - return profiles; -} - -async function validateDatabricksHost( - host: string -): Promise { - try { - const url = normalizeHost(host); - if ( - !url.hostname.match( - /(\.databricks\.azure\.us|\.databricks\.azure\.cn|\.azuredatabricks\.net|\.gcp\.databricks\.com|\.cloud\.databricks\.com|\.dev\.databricks\.com)$/ - ) - ) { - return { - message: - "This is not a standard Databricks URL. Some features may not work as expected.", - type: "warning", - }; - } - } catch (e: any) { - return e.message; - } -} - -function authMethodsForHostname(host: URL): Array { - if (isAzureHost(host)) { - return ["databricks-cli", "azure-cli", "profile"]; - } - - if (isGcpHost(host)) { - return ["databricks-cli", "google-id", "profile"]; - } - - if (isAwsHost(host)) { - return ["databricks-cli", "profile"]; - } - - return ["profile"]; -} diff --git a/packages/databricks-vscode/src/configuration/models/BaseModelWithStateCache.ts b/packages/databricks-vscode/src/configuration/models/BaseModelWithStateCache.ts new file mode 100644 index 000000000..0cbf46213 --- /dev/null +++ b/packages/databricks-vscode/src/configuration/models/BaseModelWithStateCache.ts @@ -0,0 +1,59 @@ +import {Disposable} from "vscode"; +import {CachedValue} from "../../locking/CachedValue"; +import {Mutex} from "../../locking"; + +export abstract class BaseModelWithStateCache + implements Disposable +{ + protected disposables: Disposable[] = []; + protected abstract mutex: Mutex; + + constructor() { + this.disposables.push(this.stateCache); + } + + protected readonly stateCache: CachedValue = new CachedValue( + this.readState.bind(this) + ); + + public onDidChange = this.stateCache.onDidChange.bind(this.stateCache); + public onDidChangeKey = this.stateCache.onDidChangeKey.bind( + this.stateCache + ); + + protected abstract readState(): Promise; + + @Mutex.synchronise("mutex") + public async get( + key: T + ): Promise { + return (await this.stateCache.value)[key]; + } + + @Mutex.synchronise("mutex") + public async load( + keys: T[] = [] + ): Promise>> { + if (keys.length === 0) { + return await this.stateCache.value; + } + + const stateValue = await this.stateCache.value; + return Object.fromEntries( + Object.entries(stateValue).filter(([key]) => { + return keys.includes(key as T); + }) + ) as Partial<{ + [K in T]: StateType[K]; + }>; + } + + public refresh() { + this.stateCache.refresh(); + } + + public abstract resetCache(): void; + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/configuration/models/ConfigModel.ts b/packages/databricks-vscode/src/configuration/models/ConfigModel.ts new file mode 100644 index 000000000..1e5270da2 --- /dev/null +++ b/packages/databricks-vscode/src/configuration/models/ConfigModel.ts @@ -0,0 +1,300 @@ +import {Disposable, EventEmitter, Uri, Event} from "vscode"; +import {Mutex} from "../../locking"; +import {CachedValue} from "../../locking/CachedValue"; +import {StateStorage} from "../../vscode-objs/StateStorage"; +import {onError} from "../../utils/onErrorDecorator"; +import {AuthProvider} from "../auth/AuthProvider"; +import { + OverrideableConfigModel, + OverrideableConfigState, + isOverrideableConfigKey, +} from "./OverrideableConfigModel"; +import { + BundlePreValidateModel, + BundlePreValidateState, +} from "../../bundle/models/BundlePreValidateModel"; +import { + BundleValidateModel, + BundleValidateState, +} from "../../bundle/models/BundleValidateModel"; +import {CustomWhenContext} from "../../vscode-objs/CustomWhenContext"; +import { + BundleRemoteState, + BundleRemoteStateModel, +} from "../../bundle/models/BundleRemoteStateModel"; + +const defaults: ConfigState = { + mode: "development", +}; + +const TOP_LEVEL_VALIDATE_CONFIG_KEYS = ["clusterId", "remoteRootPath"] as const; + +const TOP_LEVEL_PRE_VALIDATE_CONFIG_KEYS = [ + "host", + "mode", + "authParams", +] as const; + +type ConfigState = Pick< + BundleValidateState, + (typeof TOP_LEVEL_VALIDATE_CONFIG_KEYS)[number] +> & + Pick< + BundlePreValidateState, + (typeof TOP_LEVEL_PRE_VALIDATE_CONFIG_KEYS)[number] + > & + OverrideableConfigState & { + preValidateConfig?: BundlePreValidateState; + validateConfig?: BundleValidateState; + remoteStateConfig?: BundleRemoteState; + overrides?: OverrideableConfigState; + }; + +function selectTopLevelKeys( + obj: any, + keys: readonly string[] +): Record { + return keys.reduce((prev: any, key) => { + prev[key] = obj[key]; + return prev; + }, {}); +} +/** + * In memory view of the databricks configs loaded from overrides and bundle. + */ +export class ConfigModel implements Disposable { + private disposables: Disposable[] = []; + + /** + * Used to protect local configs (target, authProvider, configCache) from being updated + * concurrently. + */ + private readonly configsMutex = new Mutex(); + /** Used to lock state updates until certain actions complete. Aquire this always + * after configsMutex to avoid deadlocks. + */ + private readonly readStateMutex = new Mutex(); + private readonly configCache = new CachedValue( + this.readState.bind(this) + ); + + @onError({throw: false}) + @Mutex.synchronise("readStateMutex") + async readState() { + if (this.target === undefined) { + return {}; + } + const bundleValidateConfig = await this.bundleValidateModel.load(); + const overrides = await this.overrideableConfigModel.load(); + const bundlePreValidateConfig = + await this.bundlePreValidateModel.load(); + + return { + ...selectTopLevelKeys( + bundlePreValidateConfig, + TOP_LEVEL_PRE_VALIDATE_CONFIG_KEYS + ), + ...selectTopLevelKeys( + bundleValidateConfig, + TOP_LEVEL_VALIDATE_CONFIG_KEYS + ), + ...overrides, + preValidateConfig: bundlePreValidateConfig, + validateConfig: bundleValidateConfig, + overrides, + remoteStateConfig: await this.bundleRemoteStateModel.load(), + }; + } + + public onDidChange = this.configCache.onDidChange.bind(this.configCache); + public onDidChangeKey = this.configCache.onDidChangeKey.bind( + this.configCache + ); + + private onDidChangeTargetEmitter = new EventEmitter(); + public readonly onDidChangeTarget: Event = + this.onDidChangeTargetEmitter.event; + private onDidChangeAuthProviderEmitter = new EventEmitter(); + public readonly onDidChangeAuthProvider: Event = + this.onDidChangeAuthProviderEmitter.event; + + private _target: string | undefined; + private _authProvider: AuthProvider | undefined; + + constructor( + private readonly bundleValidateModel: BundleValidateModel, + private readonly overrideableConfigModel: OverrideableConfigModel, + private readonly bundlePreValidateModel: BundlePreValidateModel, + private readonly bundleRemoteStateModel: BundleRemoteStateModel, + private readonly vscodeWhenContext: CustomWhenContext, + private readonly stateStorage: StateStorage + ) { + this.disposables.push( + this.overrideableConfigModel.onDidChange(async () => { + //refresh cache to trigger onDidChange event + await this.configCache.refresh(); + }), + this.bundlePreValidateModel.onDidChange(async () => { + await this.readTarget(); + //refresh cache to trigger onDidChange event + await this.configCache.refresh(); + }), + ...TOP_LEVEL_VALIDATE_CONFIG_KEYS.map((key) => + this.bundleValidateModel.onDidChangeKey(key)(async () => { + //refresh cache to trigger onDidChange event + await this.configCache.refresh(); + }) + ), + this.bundleRemoteStateModel.onDidChange(async () => { + await this.configCache.refresh(); + }), + this.onDidChangeKey("mode")(async () => { + this.vscodeWhenContext.isDevTarget( + (await this.configCache.value).mode === "development" + ); + }) + ); + } + + @onError({popup: true}) + public async init() { + await this.readTarget(); + } + + get targets() { + return this.bundlePreValidateModel.targets; + } + /** + * Try to read target from bundle config. + * If not found, try to read from state storage. + * If not found, try to read the default target from bundle. + */ + private async readTarget() { + const targets = Object.keys( + (await this.bundlePreValidateModel.targets) ?? {} + ); + if (targets.includes(this.target ?? "")) { + return; + } + + let savedTarget: string | undefined; + await this.configsMutex.synchronise(async () => { + savedTarget = this.stateStorage.get("databricks.bundle.target"); + + if (savedTarget !== undefined && targets.includes(savedTarget)) { + return; + } + savedTarget = await this.bundlePreValidateModel.defaultTarget; + }); + + try { + await this.setTarget(savedTarget); + } catch (e: any) { + let message: string = String(e); + if (e instanceof Error) { + message = e.message; + } + throw new Error( + `Failed to initialize target ${savedTarget}: ${message}` + ); + } + } + + public get target() { + return this._target; + } + + /** + * Set target in the state storage and invalidate the configs cache. + */ + public async setTarget(target: string | undefined) { + if (target === this._target) { + return; + } + + if ( + target !== undefined && + !(target in ((await this.bundlePreValidateModel.targets) ?? {})) + ) { + throw new Error(`Target '${target}' doesn't exist in the bundle`); + } + + try { + await this.configsMutex.synchronise(async () => { + this._target = target; + await this.stateStorage.set("databricks.bundle.target", target); + // We want to wait for all the configs to be loaded before we emit any change events from the + // configStateCache. + this.bundlePreValidateModel.setTarget(target); + this.bundleValidateModel.setTarget(target); + this.overrideableConfigModel.setTarget(target); + this.bundleRemoteStateModel.setTarget(target); + await Promise.all([ + this.bundlePreValidateModel.refresh(), + this.bundleValidateModel.refresh(), + this.overrideableConfigModel.refresh(), + this.bundleRemoteStateModel.refresh(), + ]); + }); + } catch (e) { + this.configCache.set({}); // clear the cache + throw e; + } finally { + this.onDidChangeTargetEmitter.fire(); + await this.setAuthProvider(undefined); + this.vscodeWhenContext.isTargetSet(this._target !== undefined); + } + } + + @Mutex.synchronise("configsMutex") + public async setAuthProvider(authProvider: AuthProvider | undefined) { + this._authProvider = authProvider; + this.bundleRemoteStateModel.setAuthProvider(authProvider); + this.bundleValidateModel.setAuthProvider(authProvider); + this.onDidChangeAuthProviderEmitter.fire(); + await Promise.all([ + this.bundleRemoteStateModel.refresh(), + this.bundleValidateModel.refresh(), + ]); + } + + get authProvider(): AuthProvider | undefined { + return this._authProvider; + } + + @Mutex.synchronise("configsMutex") + public async get( + key: T + ): Promise { + return (await this.configCache.value)[key] ?? defaults[key]; + } + + @Mutex.synchronise("configsMutex") + public async set( + key: T, + value?: ConfigState[T], + handleInteractiveWrite?: (file: Uri) => Promise + ) { + if (this.target === undefined) { + throw new Error( + `Can't set configuration '${key}' without selecting a target` + ); + } + if (isOverrideableConfigKey(key)) { + return this.overrideableConfigModel.write( + key, + this.target, + value as any + ); + } + if (handleInteractiveWrite) { + await handleInteractiveWrite( + await this.bundlePreValidateModel.getFileToWrite(key) + ); + } + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/configuration/models/OverrideableConfigModel.ts b/packages/databricks-vscode/src/configuration/models/OverrideableConfigModel.ts new file mode 100644 index 000000000..14a381576 --- /dev/null +++ b/packages/databricks-vscode/src/configuration/models/OverrideableConfigModel.ts @@ -0,0 +1,144 @@ +import {copyFile, mkdir, readFile, rm, stat, writeFile} from "fs/promises"; +import {Mutex} from "../../locking"; +import {BaseModelWithStateCache} from "./BaseModelWithStateCache"; +import {Uri} from "vscode"; +import path from "path"; +import {existsSync} from "fs"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; + +export type OverrideableConfigState = { + authProfile?: string; + clusterId?: string; + useClusterOverride?: boolean; +}; + +export function isOverrideableConfigKey( + key: string +): key is keyof OverrideableConfigState { + return ["authProfile", "clusterId", "useClusterOverride"].includes(key); +} + +async function safeRead(filePath: Uri) { + try { + await stat(filePath.fsPath); + } catch (e: any) { + if (e.code === "ENOENT") { + return "{}"; + } + throw e; + } + + return await readFile(filePath.fsPath, "utf-8"); +} + +export class OverrideableConfigModel extends BaseModelWithStateCache { + protected mutex = new Mutex(); + private target: string | undefined; + + static getRootOverrideFile(workspaceRoot: Uri) { + return Uri.joinPath( + workspaceRoot, + ".databricks", + "bundle", + "vscode.overrides.json" + ); + } + + get storageFile() { + if (this.target === undefined) { + return undefined; + } + + return Uri.joinPath( + this.workspaceRoot, + ".databricks", + "bundle", + this.target, + "vscode.overrides.json" + ); + } + + get workspaceRoot() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } + + constructor( + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + super(); + } + + public setTarget(target: string | undefined) { + this.target = target; + this.resetCache(); + } + + protected async readState() { + if (this.storageFile === undefined) { + return {}; + } + + const rootOverrideFile = OverrideableConfigModel.getRootOverrideFile( + this.workspaceRoot + ); + // If root override file exists, use it to initialise the configs for the first selected target + if ( + existsSync(rootOverrideFile.fsPath) && + !existsSync(this.storageFile.fsPath) + ) { + await mkdir(path.dirname(this.storageFile.fsPath), { + recursive: true, + }); + await copyFile(rootOverrideFile.fsPath, this.storageFile.fsPath); + await rm(rootOverrideFile.fsPath); + } + + return JSON.parse(await safeRead(this.storageFile)); + } + + /** + * Write the config as an override to the bundle. + * @param key the key to write + * @param target the bundle target to write to + * @param value the value to write. If undefined, the override is removed. + * @returns status of the write + */ + @Mutex.synchronise("mutex") + async write( + key: T, + target: string, + value?: OverrideableConfigState[T] + ) { + if (this.storageFile === undefined) { + return; + } + + await OverrideableConfigModel._write( + this.storageFile, + key, + target, + value + ); + await this.stateCache.refresh(); + } + + static async _write( + storageFile: Uri, + key: T, + target: string, + value?: OverrideableConfigState[T] + ) { + const data = JSON.parse(await safeRead(storageFile)); + data[key] = value; + await mkdir(path.dirname(storageFile.fsPath), {recursive: true}); + await writeFile(storageFile.fsPath, JSON.stringify(data, null, 2)); + } + + public resetCache(): void { + this.stateCache.set({}); + } + + public dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/extension.ts b/packages/databricks-vscode/src/extension.ts index 69868c8e6..48ad17c19 100644 --- a/packages/databricks-vscode/src/extension.ts +++ b/packages/databricks-vscode/src/extension.ts @@ -12,97 +12,203 @@ import {ConnectionManager} from "./configuration/ConnectionManager"; import {ClusterListDataProvider} from "./cluster/ClusterListDataProvider"; import {ClusterModel} from "./cluster/ClusterModel"; import {ClusterCommands} from "./cluster/ClusterCommands"; -import {ConfigurationDataProvider} from "./configuration/ConfigurationDataProvider"; +import {ConfigurationDataProvider} from "./ui/configuration-view/ConfigurationDataProvider"; import {RunCommands} from "./run/RunCommands"; import {DatabricksDebugAdapterFactory} from "./run/DatabricksDebugAdapter"; import {DatabricksWorkflowDebugAdapterFactory} from "./run/DatabricksWorkflowDebugAdapter"; -import {SyncCommands} from "./sync/SyncCommands"; -import {CodeSynchronizer} from "./sync/CodeSynchronizer"; -import {ProjectConfigFileWatcher} from "./file-managers/ProjectConfigFileWatcher"; import {QuickstartCommands} from "./quickstart/QuickstartCommands"; import {showQuickStartOnFirstUse} from "./quickstart/QuickStart"; import {PublicApi} from "@databricks/databricks-vscode-types"; import {LoggerManager, Loggers} from "./logger"; import {logging} from "@databricks/databricks-sdk"; import {workspaceConfigs} from "./vscode-objs/WorkspaceConfigs"; -import {PackageJsonUtils, UtilsCommands} from "./utils"; -import {ConfigureAutocomplete} from "./language/ConfigureAutocomplete"; import { - WorkspaceFsAccessVerifier, - WorkspaceFsCommands, - WorkspaceFsDataProvider, -} from "./workspace-fs"; -import {generateBundleSchema} from "./bundle/GenerateBundle"; + FileUtils, + PackageJsonUtils, + TerraformUtils, + UtilsCommands, +} from "./utils"; +import {ConfigureAutocomplete} from "./language/ConfigureAutocomplete"; +import {WorkspaceFsCommands, WorkspaceFsDataProvider} from "./workspace-fs"; import {CustomWhenContext} from "./vscode-objs/CustomWhenContext"; import {StateStorage} from "./vscode-objs/StateStorage"; import path from "node:path"; import {FeatureId, FeatureManager} from "./feature-manager/FeatureManager"; -import {DbConnectAccessVerifier} from "./language/DbConnectAccessVerifier"; +import {EnvironmentDependenciesVerifier} from "./language/EnvironmentDependenciesVerifier"; import {MsPythonExtensionWrapper} from "./language/MsPythonExtensionWrapper"; import {DatabricksEnvFileManager} from "./file-managers/DatabricksEnvFileManager"; import {getContextMetadata, Telemetry, toUserMetadata} from "./telemetry"; import "./telemetry/commandExtensions"; import {Events, Metadata} from "./telemetry/constants"; -import {DbConnectInstallPrompt} from "./language/DbConnectInstallPrompt"; +import {EnvironmentDependenciesInstaller} from "./language/EnvironmentDependenciesInstaller"; import {setDbnbCellLimits} from "./language/notebooks/DatabricksNbCellLimits"; import {DbConnectStatusBarButton} from "./language/DbConnectStatusBarButton"; -import {NotebookAccessVerifier} from "./language/notebooks/NotebookAccessVerifier"; import {NotebookInitScriptManager} from "./language/notebooks/NotebookInitScriptManager"; import {showRestartNotebookDialogue} from "./language/notebooks/restartNotebookDialogue"; +import { + BundleWatcher, + BundleFileSet, + registerBundleAutocompleteProvider, +} from "./bundle"; import {showWhatsNewPopup} from "./whatsNewPopup"; +import {BundleValidateModel} from "./bundle/models/BundleValidateModel"; +import {ConfigModel} from "./configuration/models/ConfigModel"; +import {OverrideableConfigModel} from "./configuration/models/OverrideableConfigModel"; +import {BundlePreValidateModel} from "./bundle/models/BundlePreValidateModel"; +import {BundleRemoteStateModel} from "./bundle/models/BundleRemoteStateModel"; +import {BundleResourceExplorerTreeDataProvider} from "./ui/bundle-resource-explorer/BundleResourceExplorerTreeDataProvider"; +import {BundleCommands} from "./ui/bundle-resource-explorer/BundleCommands"; +import {BundleRunTerminalManager} from "./bundle/run/BundleRunTerminalManager"; +import {BundleRunStatusManager} from "./bundle/run/BundleRunStatusManager"; +import {BundleProjectManager} from "./bundle/BundleProjectManager"; +import {TreeItemDecorationProvider} from "./ui/DecorationProvider"; +import {BundleInitWizard} from "./bundle/BundleInitWizard"; +import {DatabricksDebugConfigurationProvider} from "./run/DatabricksDebugConfigurationProvider"; +import {BundleVariableModel} from "./bundle/models/BundleVariableModel"; +import {BundleVariableTreeDataProvider} from "./ui/bundle-variables/BundleVariableTreeDataProvider"; +import {ConfigurationTreeViewManager} from "./ui/configuration-view/ConfigurationTreeViewManager"; +import {getCLIDependenciesEnvVars} from "./utils/envVarGenerators"; +import {EnvironmentCommands} from "./language/EnvironmentCommands"; +import {WorkspaceFolderManager} from "./vscode-objs/WorkspaceFolderManager"; +import {SyncCommands} from "./sync/SyncCommands"; +import {CodeSynchronizer} from "./sync"; + +// eslint-disable-next-line @typescript-eslint/no-var-requires +const packageJson = require("../package.json"); + +const customWhenContext = new CustomWhenContext(); export async function activate( context: ExtensionContext ): Promise { - CustomWhenContext.setActivated(false); - - if (extensions.getExtension("databricks.databricks-vscode") !== undefined) { - await commands.executeCommand( - "workbench.extensions.uninstallExtension", - "databricks.databricks-vscode" - ); + customWhenContext.setActivated(false); + customWhenContext.setDeploymentState("idle"); - await commands.executeCommand("workbench.action.reloadWindow"); - } + const stateStorage = new StateStorage(context); + const packageMetadata = await PackageJsonUtils.getMetadata(context); if (!(await PackageJsonUtils.checkArchCompat(context))) { return undefined; } + const telemetry = Telemetry.createDefault(); + telemetry.setMetadata(Metadata.CONTEXT, getContextMetadata()); + + const loggerManager = new LoggerManager(context); + if (workspaceConfigs.loggingEnabled) { + loggerManager.initLoggers(); + } + + let cliLogFilePath; + try { + cliLogFilePath = await loggerManager.getLogFile("databricks-cli"); + } catch (e) { + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + "Failed to create a log file for the CLI", + e + ); + } + + const cli = new CliWrapper(context, loggerManager, cliLogFilePath); + + // Loggers + context.subscriptions.push( + telemetry.registerCommand( + "databricks.logs.openFolder", + loggerManager.openLogFolder, + loggerManager + ), + telemetry.registerCommand( + "databricks.bundle.showLogs", + () => loggerManager.showOutputChannel("Databricks Bundle Logs"), + loggerManager + ) + ); + + // Quickstart + const quickstartCommands = new QuickstartCommands(context); + context.subscriptions.push( + telemetry.registerCommand( + "databricks.quickstart.open", + quickstartCommands.openQuickstartCommand(), + quickstartCommands + ) + ); + if ( workspace.workspaceFolders === undefined || workspace.workspaceFolders?.length === 0 ) { - window.showErrorMessage("Open a folder to use Databricks extension"); - /* - We force the user to open a folder from the databricks sidebar view. Returning - here blocks all other commands from running. - Since the workspace is reloaded when a folder is opened, the activation function - is called again. Therefore this won't block the activation of the extension on a - valid workspace. - */ + context.subscriptions.push( + telemetry.registerCommand( + "databricks.bundle.initNewProject", + async () => { + const bundleInitWizard = new BundleInitWizard( + cli, + telemetry + ); + await bundleInitWizard.initNewProject(); + } + ) + ); + // We show a welcome view when there's no workspace folders, prompting users + // to either open a new folder or to initialize a new databricks project. + // In both cases we expect the workspace to be reloaded and the extension will + // be activated again. return undefined; } - const stateStorage = new StateStorage(context); + const workspaceFolderManager = new WorkspaceFolderManager( + customWhenContext + ); + + context.subscriptions.push( + telemetry.registerCommand( + "databricks.selectWorkspaceFolder", + workspaceFolderManager.selectDatabricksWorkspaceFolderCommand, + workspaceFolderManager + ) + ); // Add the databricks binary to the PATH environment variable in terminals context.environmentVariableCollection.clear(); context.environmentVariableCollection.persistent = false; - context.environmentVariableCollection.prepend( + context.environmentVariableCollection.append( "PATH", - `${context.asAbsolutePath("./bin")}${path.delimiter}` + `${path.delimiter}${context.asAbsolutePath("./bin")}` ); - const loggerManager = new LoggerManager(context); - if (workspaceConfigs.loggingEnabled) { - loggerManager.initLoggers(); - } + // Export CLI_UPSTREAM vars to the terminal to see if extension users use the CLI directly + context.environmentVariableCollection.replace( + "DATABRICKS_CLI_UPSTREAM", + "databricks-vscode-terminal" + ); + context.environmentVariableCollection.replace( + "DATABRICKS_CLI_UPSTREAM_VERSION", + packageMetadata.version + ); - const telemetry = Telemetry.createDefault(); - telemetry.setMetadata(Metadata.CONTEXT, getContextMetadata()); + // We always use bundled terraform and databricks provider. + // Updating environment collection means that the variables will be set in all terminals. + // If users use different CLI version in their terminal it will only pick the variables if + // the dependency versions (that we set together with bin and config paths) match the internal versions of the CLI. + const cliDeps = getCLIDependenciesEnvVars(context); + for (const [key, value] of Object.entries(cliDeps)) { + logging.NamedLogger.getOrCreate(Loggers.Extension).debug( + `Setting env var ${key}=${value}` + ); + context.environmentVariableCollection.replace(key, value); + } + TerraformUtils.updateTerraformCliConfig( + context, + packageJson.terraformMetadata + ).catch((e) => { + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + "Failed to update terraform cli config", + e + ); + }); - const packageMetadata = await PackageJsonUtils.getMetadata(context); logging.NamedLogger.getOrCreate(Loggers.Extension).debug("Metadata", { metadata: packageMetadata, }); @@ -120,55 +226,75 @@ export async function activate( const pythonExtensionWrapper = new MsPythonExtensionWrapper( pythonExtension, - workspace.workspaceFolders[0].uri, + workspaceFolderManager, stateStorage ); - context.subscriptions.push( - telemetry.registerCommand( - "databricks.logs.openFolder", - loggerManager.openLogFolder, - loggerManager - ) - ); + cli.setPythonExtension(pythonExtensionWrapper); // manage contexts for experimental features function updateFeatureContexts() { - CustomWhenContext.updateShowClusterView(); - CustomWhenContext.updateShowWorkspaceView(); - } - - function updateStrictSsl() { - const httpConfig = workspace.getConfiguration("http"); - const proxyStrictSSL = httpConfig.get("proxyStrictSSL"); - process.env["NODE_TLS_REJECT_UNAUTHORIZED"] = proxyStrictSSL - ? "1" - : "0"; + customWhenContext.updateShowClusterView(); + customWhenContext.updateShowWorkspaceView(); } updateFeatureContexts(); - updateStrictSsl(); context.subscriptions.push( - workspace.onDidChangeConfiguration(() => { - updateFeatureContexts(); - updateStrictSsl(); - }) + workspace.onDidChangeConfiguration(updateFeatureContexts) ); // Configuration group - let cliLogFilePath; - try { - cliLogFilePath = await loggerManager.getLogFile("databricks-cli"); - } catch (e) { - logging.NamedLogger.getOrCreate(Loggers.Extension).error( - "Failed to create a log file for the CLI", - e - ); - } - const cli = new CliWrapper(context, cliLogFilePath); - const connectionManager = new ConnectionManager(cli); + const bundleFileSet = new BundleFileSet(workspaceFolderManager); + const bundleFileWatcher = new BundleWatcher( + bundleFileSet, + workspaceFolderManager + ); + const bundleValidateModel = new BundleValidateModel( + bundleFileWatcher, + cli, + workspaceFolderManager + ); + + const overrideableConfigModel = new OverrideableConfigModel( + workspaceFolderManager + ); + const bundlePreValidateModel = new BundlePreValidateModel( + bundleFileSet, + bundleFileWatcher + ); + const bundleRemoteStateModel = new BundleRemoteStateModel( + cli, + workspaceFolderManager, + workspaceConfigs + ); + const configModel = new ConfigModel( + bundleValidateModel, + overrideableConfigModel, + bundlePreValidateModel, + bundleRemoteStateModel, + customWhenContext, + stateStorage + ); + + const connectionManager = new ConnectionManager( + cli, + configModel, + workspaceFolderManager, + customWhenContext, + telemetry + ); context.subscriptions.push( - connectionManager.onDidChangeState(async (state) => { + bundleFileWatcher, + bundleValidateModel, + overrideableConfigModel, + bundlePreValidateModel, + bundleRemoteStateModel, + configModel, + connectionManager, + commands.registerCommand("databricks.internal.showOutput", () => { + loggerManager.showOutputChannel("Databricks Logs"); + }), + connectionManager.onDidChangeState(async () => { telemetry.setMetadata( Metadata.USER, await toUserMetadata(connectionManager) @@ -176,23 +302,46 @@ export async function activate( telemetry.recordEvent(Events.CONNECTION_STATE_CHANGED, { newState: connectionManager.state, }); - if (state === "CONNECTED") { - telemetry.recordEvent(Events.SYNC_DESTINATION, { - destination: workspaceConfigs.syncDestinationType, - }); - } }) ); const metadataService = await connectionManager.startMetadataService(); context.subscriptions.push(metadataService); + const bundleProjectManager = new BundleProjectManager( + context, + cli, + customWhenContext, + connectionManager, + configModel, + bundleFileSet, + workspaceFolderManager, + telemetry + ); + context.subscriptions.push( + bundleProjectManager, + telemetry.registerCommand( + "databricks.bundle.openSubProject", + bundleProjectManager.openSubProjects, + bundleProjectManager + ), + telemetry.registerCommand( + "databricks.bundle.initNewProject", + bundleProjectManager.initNewProject, + bundleProjectManager + ), + telemetry.registerCommand( + "databricks.bundle.startManualMigration", + bundleProjectManager.startManualMigration, + bundleProjectManager + ) + ); + const workspaceFsDataProvider = new WorkspaceFsDataProvider( connectionManager ); const workspaceFsCommands = new WorkspaceFsCommands( - workspace.workspaceFolders[0].uri, - stateStorage, + workspaceFolderManager, connectionManager, workspaceFsDataProvider ); @@ -214,66 +363,72 @@ export async function activate( ) ); - const synchronizer = new CodeSynchronizer( - connectionManager, - cli, - packageMetadata - ); const clusterModel = new ClusterModel(connectionManager); - const connectionCommands = new ConnectionCommands( - workspaceFsCommands, - connectionManager, - clusterModel - ); - - const wsfsAccessVerifier = new WorkspaceFsAccessVerifier( - connectionManager, - stateStorage, - synchronizer, - telemetry - ); - - context.subscriptions.push(wsfsAccessVerifier); - - const dbConnectInstallPrompt = new DbConnectInstallPrompt( - stateStorage, - pythonExtensionWrapper - ); + const environmentDependenciesInstaller = + new EnvironmentDependenciesInstaller(pythonExtensionWrapper); const featureManager = new FeatureManager([]); featureManager.registerFeature( - "debugging.dbconnect", + "environment.dependencies", () => - new DbConnectAccessVerifier( + new EnvironmentDependenciesVerifier( connectionManager, pythonExtensionWrapper, - dbConnectInstallPrompt + environmentDependenciesInstaller ) ); - - featureManager.registerFeature( - "notebooks.dbconnect", - () => - new NotebookAccessVerifier( - featureManager, - pythonExtensionWrapper, - stateStorage - ) + const environmentCommands = new EnvironmentCommands( + featureManager, + pythonExtensionWrapper, + environmentDependenciesInstaller + ); + context.subscriptions.push( + telemetry.registerCommand( + "databricks.environment.setup", + environmentCommands.setup, + environmentCommands + ), + telemetry.registerCommand( + "databricks.environment.refresh", + environmentCommands.refresh, + environmentCommands + ), + telemetry.registerCommand( + "databricks.environment.selectPythonInterpreter", + environmentCommands.selectPythonInterpreter, + environmentCommands + ), + telemetry.registerCommand( + "databricks.environment.reinstallDBConnect", + async () => + environmentCommands.reinstallDBConnect( + connectionManager.cluster + ) + ) ); const dbConnectStatusBarButton = new DbConnectStatusBarButton( featureManager ); + const databricksEnvFileManager = new DatabricksEnvFileManager( + workspaceFolderManager, + featureManager, + connectionManager, + configModel + ); + const notebookInitScriptManager = new NotebookInitScriptManager( - workspace.workspaceFolders[0].uri, + workspaceFolderManager, context, connectionManager, featureManager, - pythonExtensionWrapper + pythonExtensionWrapper, + databricksEnvFileManager ); context.subscriptions.push( + dbConnectStatusBarButton, notebookInitScriptManager, telemetry.registerCommand( "databricks.notebookInitScript.verify", @@ -282,42 +437,6 @@ export async function activate( ) ); - const databricksEnvFileManager = new DatabricksEnvFileManager( - workspace.workspaceFolders[0].uri, - featureManager, - dbConnectStatusBarButton, - connectionManager, - context, - notebookInitScriptManager - ); - - context.subscriptions.push( - workspace.onDidOpenNotebookDocument(() => - featureManager.isEnabled("notebooks.dbconnect") - ), - featureManager.onDidChangeState( - "notebooks.dbconnect", - async (featureState) => { - const dbconnectState = await featureManager.isEnabled( - "debugging.dbconnect" - ); - if (!dbconnectState.avaliable) { - return; // Only take action of notebook errors, when dbconnect is avaliable - } - if (featureState.action) { - featureState.action(); - } else if ( - !featureState.isDisabledByFf && - featureState.reason - ) { - window.showErrorMessage( - `Error while trying to initialise Databricks Notebooks. Some features may not work. Reason: ${featureState.reason}` - ); - } - } - ) - ); - notebookInitScriptManager.updateInitScript().catch((e) => { logging.NamedLogger.getOrCreate(Loggers.Extension).error( "Failed to update init script", @@ -334,16 +453,20 @@ export async function activate( databricksEnvFileManager.init(); context.subscriptions.push( databricksEnvFileManager, + workspaceFolderManager.onDidChangeActiveWorkspaceFolder(() => { + databricksEnvFileManager.dispose(); + databricksEnvFileManager.init(); + }), showRestartNotebookDialogue(databricksEnvFileManager) ); - featureManager.isEnabled("debugging.dbconnect"); + featureManager.isEnabled("environment.dependencies"); const configureAutocomplete = new ConfigureAutocomplete( context, stateStorage, - workspace.workspaceFolders[0].uri.fsPath, + workspaceFolderManager, pythonExtensionWrapper, - dbConnectInstallPrompt + environmentDependenciesInstaller ); context.subscriptions.push( configureAutocomplete, @@ -354,22 +477,65 @@ export async function activate( ) ); + const codeSynchroniser = new CodeSynchronizer( + connectionManager, + configModel, + cli, + packageMetadata + ); + + const syncCommands = new SyncCommands(codeSynchroniser); + context.subscriptions.push( + telemetry.registerCommand( + "databricks.sync.start", + syncCommands.startCommand("incremental"), + syncCommands + ), + telemetry.registerCommand( + "databricks.sync.startFull", + syncCommands.startCommand("full"), + syncCommands + ), + telemetry.registerCommand( + "databricks.sync.stop", + syncCommands.stopCommand(), + syncCommands + ) + ); const configurationDataProvider = new ConfigurationDataProvider( connectionManager, - synchronizer, - stateStorage, - wsfsAccessVerifier, + codeSynchroniser, + bundleProjectManager, + configModel, + cli, featureManager, - telemetry + workspaceFolderManager + ); + const configurationView = window.createTreeView("configurationView", { + treeDataProvider: configurationDataProvider, + }); + + const configurationTreeViewManager = new ConfigurationTreeViewManager( + configurationView, + configModel + ); + + const connectionCommands = new ConnectionCommands( + workspaceFsCommands, + connectionManager, + clusterModel, + configModel, + cli ); context.subscriptions.push( configurationDataProvider, - synchronizer, - - window.registerTreeDataProvider( - "configurationView", - configurationDataProvider + configurationView, + configurationTreeViewManager, + telemetry.registerCommand( + "databricks.connection.bundle.selectTarget", + connectionCommands.selectTarget, + connectionCommands ), telemetry.registerCommand( "databricks.connection.logout", @@ -377,14 +543,13 @@ export async function activate( connectionCommands ), telemetry.registerCommand( - "databricks.connection.configureWorkspace", - connectionCommands.configureWorkspaceCommand, + "databricks.connection.configureLogin", + connectionCommands.configureLoginCommand, connectionCommands ), telemetry.registerCommand( "databricks.connection.openDatabricksConfigFile", - connectionCommands.openDatabricksConfigFileCommand(), - connectionCommands + FileUtils.openDatabricksConfigFile ), telemetry.registerCommand( "databricks.connection.attachCluster", @@ -402,52 +567,12 @@ export async function activate( connectionCommands ), telemetry.registerCommand( - "databricks.connection.attachSyncDestination", - connectionCommands.attachSyncDestinationCommand(), - connectionCommands - ), - telemetry.registerCommand( - "databricks.connection.detachSyncDestination", - connectionCommands.detachWorkspaceCommand, + "databricks.connection.saveNewProfile", + connectionCommands.saveNewProfileCommand, connectionCommands ) ); - // Run/debug group - const runCommands = new RunCommands(connectionManager); - const debugFactory = new DatabricksDebugAdapterFactory( - connectionManager, - synchronizer, - context, - wsfsAccessVerifier - ); - const debugWorkflowFactory = new DatabricksWorkflowDebugAdapterFactory( - connectionManager, - wsfsAccessVerifier, - context, - synchronizer - ); - - context.subscriptions.push( - telemetry.registerCommand( - "databricks.run.runEditorContents", - runCommands.runEditorContentsCommand(), - runCommands - ), - telemetry.registerCommand( - "databricks.run.runEditorContentsAsWorkflow", - runCommands.runEditorContentsAsWorkflowCommand(), - runCommands - ), - debug.registerDebugAdapterDescriptorFactory("databricks", debugFactory), - debugFactory, - debug.registerDebugAdapterDescriptorFactory( - "databricks-workflow", - debugWorkflowFactory - ), - debugWorkflowFactory - ); - // Cluster group const clusterTreeDataProvider = new ClusterListDataProvider(clusterModel); const clusterCommands = new ClusterCommands( @@ -492,42 +617,173 @@ export async function activate( ) ); - // Sync - const syncCommands = new SyncCommands(synchronizer); + // Bundle resource explorer + const bundleRunTerminalManager = new BundleRunTerminalManager( + bundleRemoteStateModel + ); + const bundleRunStatusManager = new BundleRunStatusManager( + configModel, + bundleRunTerminalManager + ); + const bundleResourceExplorerTreeDataProvider = + new BundleResourceExplorerTreeDataProvider( + configModel, + bundleRunStatusManager, + context, + connectionManager + ); + + const bundleCommands = new BundleCommands( + bundleRemoteStateModel, + bundleRunStatusManager, + bundleValidateModel, + configModel, + customWhenContext, + telemetry + ); + const decorationProvider = new TreeItemDecorationProvider( + bundleResourceExplorerTreeDataProvider, + configurationDataProvider + ); context.subscriptions.push( + bundleResourceExplorerTreeDataProvider, + bundleCommands, + bundleRunTerminalManager, + decorationProvider, + window.registerFileDecorationProvider(decorationProvider), + window.registerTreeDataProvider( + "dabsResourceExplorerView", + bundleResourceExplorerTreeDataProvider + ), telemetry.registerCommand( - "databricks.sync.start", - syncCommands.startCommand("incremental"), - syncCommands + "databricks.bundle.refreshRemoteState", + bundleCommands.refreshCommand, + bundleCommands ), telemetry.registerCommand( - "databricks.sync.startFull", - syncCommands.startCommand("full"), - syncCommands + "databricks.bundle.deploy", + bundleCommands.deployCommand, + bundleCommands ), telemetry.registerCommand( - "databricks.sync.stop", - syncCommands.stopCommand(), - syncCommands + "databricks.bundle.forceDeploy", + bundleCommands.forceDeployCommand, + bundleCommands + ), + telemetry.registerCommand( + "databricks.bundle.forceDestroy", + bundleCommands.forceDestroyCommand, + bundleCommands + ), + telemetry.registerCommand( + "databricks.bundle.deployAndRun", + bundleCommands.deployAndRun, + bundleCommands + ), + telemetry.registerCommand( + "databricks.bundle.cancelRun", + bundleCommands.cancelRun, + bundleCommands + ), + telemetry.registerCommand( + "databricks.bundle.destroy", + bundleCommands.destroy, + bundleCommands ) ); + // Bundle variables + const bundleVariableModel = new BundleVariableModel( + configModel, + bundleValidateModel, + workspaceFolderManager + ); + cli.bundleVariableModel = bundleVariableModel; + const bundleVariableTreeDataProvider = new BundleVariableTreeDataProvider( + bundleVariableModel + ); context.subscriptions.push( - new ProjectConfigFileWatcher( - connectionManager, - workspace.rootPath!, - cli.cliPath + bundleVariableModel, + window.registerTreeDataProvider( + "dabsVariableView", + bundleVariableTreeDataProvider + ), + telemetry.registerCommand( + "databricks.bundle.variable.openFile", + bundleVariableModel.openBundleVariableFile, + bundleVariableModel + ), + telemetry.registerCommand( + "databricks.bundle.variable.reset", + bundleVariableModel.deleteBundleVariableFile, + bundleVariableModel ) ); - // Quickstart - const quickstartCommands = new QuickstartCommands(context); + // Run/debug group + const databricksDebugConfigurationProvider = + new DatabricksDebugConfigurationProvider( + context, + databricksEnvFileManager + ); + + const runCommands = new RunCommands( + connectionManager, + workspaceFolderManager, + pythonExtensionWrapper, + featureManager, + context, + customWhenContext + ); + const debugFactory = new DatabricksDebugAdapterFactory( + connectionManager, + configModel, + bundleCommands, + context + ); + const debugWorkflowFactory = new DatabricksWorkflowDebugAdapterFactory( + connectionManager, + configModel, + context, + bundleCommands + ); + context.subscriptions.push( + debug.registerDebugConfigurationProvider( + "python", + databricksDebugConfigurationProvider + ), + debug.registerDebugConfigurationProvider( + "debugpy", + databricksDebugConfigurationProvider + ), telemetry.registerCommand( - "databricks.quickstart.open", - quickstartCommands.openQuickstartCommand(), - quickstartCommands - ) + "databricks.run.dbconnect.debug", + runCommands.debugFileUsingDbconnect, + runCommands + ), + telemetry.registerCommand( + "databricks.run.dbconnect.run", + runCommands.runFileUsingDbconnect, + runCommands + ), + telemetry.registerCommand( + "databricks.run.runEditorContents", + runCommands.runEditorContentsCommand(), + runCommands + ), + telemetry.registerCommand( + "databricks.run.runEditorContentsAsWorkflow", + runCommands.runEditorContentsAsWorkflowCommand(), + runCommands + ), + debug.registerDebugAdapterDescriptorFactory("databricks", debugFactory), + debugFactory, + debug.registerDebugAdapterDescriptorFactory( + "databricks-workflow", + debugWorkflowFactory + ), + debugWorkflowFactory ); showQuickStartOnFirstUse(context).catch((e) => { @@ -545,6 +801,11 @@ export async function activate( utilCommands.openExternalCommand(), utilCommands ), + telemetry.registerCommand( + "databricks.utils.copy", + utilCommands.copyToClipboardCommand(), + utilCommands + ), telemetry.registerCommand("databricks.call", (fn) => { if (fn) { fn(); @@ -554,24 +815,19 @@ export async function activate( // generate a json schema for bundle root and load a custom provider into // redhat.vscode-yaml extension to validate bundle config files with this schema - generateBundleSchema(cli).catch((e) => { + registerBundleAutocompleteProvider( + cli, + bundleFileSet, + bundleFileWatcher, + context + ).catch((e) => { logging.NamedLogger.getOrCreate("Extension").error( "Failed to load bundle schema: ", e ); }); - connectionManager.login(false).catch((e) => { - logging.NamedLogger.getOrCreate(Loggers.Extension).error( - "Login error", - e - ); - }); - - setDbnbCellLimits( - workspace.workspaceFolders[0].uri, - connectionManager - ).catch((e) => { + setDbnbCellLimits(workspaceFolderManager, connectionManager).catch((e) => { logging.NamedLogger.getOrCreate(Loggers.Extension).error( "Error while setting jupyter configs for parsing databricks notebooks", e @@ -592,8 +848,39 @@ export async function activate( ); }); - CustomWhenContext.setActivated(true); - telemetry.recordEvent(Events.EXTENSION_ACTIVATED); + context.subscriptions.push( + commands.registerCommand("databricks.internal.clearOverrides", () => { + stateStorage.set("databricks.bundle.overrides", undefined); + configModel.setTarget(undefined); + configModel.setAuthProvider(undefined); + }) + ); + + const recordInitializationEvent = telemetry.start( + Events.EXTENSION_INITIALIZATION + ); + + const configureWorkspace = () => { + bundleProjectManager + .configureWorkspace() + .catch((e) => { + recordInitializationEvent({success: false}); + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + "Failed to configure workspace", + e + ); + window.showErrorMessage(e); + }) + .finally(() => { + customWhenContext.setInitialized(); + }); + }; + + configureWorkspace(); + workspaceFolderManager.onDidChangeActiveWorkspaceFolder(configureWorkspace); + + customWhenContext.setActivated(true); + telemetry.recordEvent(Events.EXTENSION_ACTIVATION); const publicApi: PublicApi = { version: 1, @@ -604,5 +891,5 @@ export async function activate( // this method is called when your extension is deactivated export function deactivate() { - CustomWhenContext.setActivated(false); + customWhenContext.setActivated(false); } diff --git a/packages/databricks-vscode/src/feature-manager/DisabledFeature.ts b/packages/databricks-vscode/src/feature-manager/DisabledFeature.ts index fa97d3daf..225449d1f 100644 --- a/packages/databricks-vscode/src/feature-manager/DisabledFeature.ts +++ b/packages/databricks-vscode/src/feature-manager/DisabledFeature.ts @@ -6,6 +6,12 @@ export class DisabledFeature extends MultiStepAccessVerifier { } async check() { - this.rejectStep("disabled", "feature is disabled", undefined, true); + this.rejectStep( + "disabled", + "feature is disabled", + undefined, + undefined, + true + ); } } diff --git a/packages/databricks-vscode/src/feature-manager/FeatureManager.test.ts b/packages/databricks-vscode/src/feature-manager/FeatureManager.test.ts index 8ea398a60..94d93225a 100644 --- a/packages/databricks-vscode/src/feature-manager/FeatureManager.test.ts +++ b/packages/databricks-vscode/src/feature-manager/FeatureManager.test.ts @@ -1,5 +1,5 @@ import {spy, verify} from "ts-mockito"; -import {FeatureManager, FeatureState} from "./FeatureManager"; +import {FeatureManager, FeatureStepState} from "./FeatureManager"; import {MultiStepAccessVerifier} from "./MultiStepAccessVerfier"; import * as assert from "assert"; class TestAccessVerifier extends MultiStepAccessVerifier { @@ -27,11 +27,8 @@ class TestAccessVerifier extends MultiStepAccessVerifier { } } -function isAvailable(state: boolean | FeatureState) { - if (typeof state === "boolean") { - return state; - } - return state.avaliable; +function isAvailable(state: FeatureStepState) { + return state.available; } describe(__filename, async () => { @@ -41,8 +38,8 @@ describe(__filename, async () => { const spyTestVerifier = spy(testVerifier); fm.registerFeature("test", () => testVerifier); - assert.ok(!(await fm.isEnabled("test")).avaliable); - assert.ok(!(await fm.isEnabled("test")).avaliable); + assert.ok(!(await fm.isEnabled("test")).available); + assert.ok(!(await fm.isEnabled("test")).available); verify(spyTestVerifier.check()).once(); verify(spyTestVerifier.check1()).once(); verify(spyTestVerifier.check2()).once(); @@ -55,26 +52,29 @@ describe(__filename, async () => { fm.registerFeature("test", () => testVerifier); //check value is picked from cache - assert.ok(!(await fm.isEnabled("test")).avaliable); - assert.ok(!(await fm.isEnabled("test")).avaliable); + assert.ok(!(await fm.isEnabled("test")).available); + assert.ok(!(await fm.isEnabled("test")).available); verify(spyTestVerifier.check()).once(); verify(spyTestVerifier.check1()).once(); verify(spyTestVerifier.check2()).once(); //cache should be true only when both values are true assert.ok(isAvailable(await testVerifier.check1(true))); - assert.ok(!(await fm.isEnabled("test")).avaliable); + assert.ok(!(await fm.isEnabled("test")).available); assert.ok(isAvailable(await testVerifier.check2(true))); - assert.ok((await fm.isEnabled("test")).avaliable); + assert.ok((await fm.isEnabled("test")).available); //cache should be false if even 1 value is false assert.ok(!isAvailable(await testVerifier.check2(false))); - assert.ok(!(await fm.isEnabled("test")).avaliable); - assert.ok((await fm.isEnabled("test")).reason === "reason2"); + assert.ok(!(await fm.isEnabled("test")).available); + assert.strictEqual( + (await fm.isEnabled("test")).steps.get("check2")?.title, + "reason2" + ); //cache should be reset to true if both values are true assert.ok(isAvailable(await testVerifier.check2(true))); - assert.ok((await fm.isEnabled("test")).avaliable); + assert.ok((await fm.isEnabled("test")).available); }); it("disabled features should always return false", async () => { @@ -83,14 +83,15 @@ describe(__filename, async () => { const spyTestVerifier = spy(testVerifier); fm.registerFeature("test", () => testVerifier); - assert.ok(!(await fm.isEnabled("test")).avaliable); - assert.ok(!(await fm.isEnabled("test")).avaliable); + assert.ok(!(await fm.isEnabled("test")).available); + assert.ok(!(await fm.isEnabled("test")).available); verify(spyTestVerifier.check()).never(); verify(spyTestVerifier.check1()).never(); verify(spyTestVerifier.check2()).never(); - assert.ok( - (await fm.isEnabled("test")).reason === "feature is disabled" + assert.strictEqual( + (await fm.isEnabled("test")).message, + "Feature is disabled" ); }); }); diff --git a/packages/databricks-vscode/src/feature-manager/FeatureManager.ts b/packages/databricks-vscode/src/feature-manager/FeatureManager.ts index cc35e4970..39c37fc81 100644 --- a/packages/databricks-vscode/src/feature-manager/FeatureManager.ts +++ b/packages/databricks-vscode/src/feature-manager/FeatureManager.ts @@ -1,4 +1,4 @@ -import {Event, EventEmitter, Disposable} from "vscode"; +import {Event, Disposable} from "vscode"; import {Mutex} from "../locking"; import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {DisabledFeature} from "./DisabledFeature"; @@ -7,26 +7,27 @@ import {logging} from "@databricks/databricks-sdk"; import {Loggers} from "../logger"; export type FeatureEnableAction = (...args: any[]) => Promise; -export type FeatureId = "debugging.dbconnect" | "notebooks.dbconnect"; -/** - * The state of a feature. - * *available*: If feature is enabled. - * *reason*: If feature is disabled, this is the human readable reason for feature being disabled. - * *action*: If feature is disabled, this optionally contains the function which tries to solve the issue - * and enable the feature. - */ +export type FeatureId = "environment.dependencies"; + export interface FeatureState { - avaliable: boolean; - reason?: string; + available: boolean; + message?: string; + steps: Map; +} + +export interface FeatureStepState { + id: string; + available: boolean; + title?: string; + message?: string; + warning?: string; action?: FeatureEnableAction; isDisabledByFf?: boolean; - // Dirty is expected to only ever be et by featureManager. - // This forces a refresh of the cache because any incoming feature state will - // be different from the cached value, by not having this flag set. - _dirty?: boolean; } export interface Feature extends Disposable { + mutex: Mutex; + state: FeatureState; check: () => Promise; onDidChangeState: Event; } @@ -41,18 +42,9 @@ export interface Feature extends Disposable { */ export class FeatureManager implements Disposable { private disposables: Disposable[] = []; - - private features: Map< - T, - { - feature: Feature; - onDidChangeStateEmitter: EventEmitter; - onDidChangeState: Event; - mutex: Mutex; - } - > = new Map(); - + private features: Map = new Map(); private stateCache: Map = new Map(); + constructor(private readonly disabledFeatures: (T | FeatureId)[]) {} registerFeature( @@ -67,28 +59,12 @@ export class FeatureManager implements Disposable { !workspaceConfigs.experimetalFeatureOverides.includes(id as string) ? new DisabledFeature() : featureFactory(); - - const eventEmitter = new EventEmitter(); this.disposables.push( - feature, - feature.onDidChangeState((e) => { - if ( - !this.stateCache.has(id) || - (this.stateCache.has(id) && - JSON.stringify(this.stateCache.get(id)) !== - JSON.stringify(e)) - ) { - this.stateCache.set(id, e); - eventEmitter.fire(e); - } - }, this) + feature.onDidChangeState((state) => { + this.stateCache.set(id, state); + }) ); - this.features.set(id, { - feature, - onDidChangeStateEmitter: eventEmitter, - onDidChangeState: eventEmitter.event, - mutex: new Mutex(), - }); + this.features.set(id, feature); } onDidChangeState(id: T, f: (state: FeatureState) => any, thisArgs?: any) { @@ -107,49 +83,30 @@ export class FeatureManager implements Disposable { async isEnabled(id: T, force = false): Promise { const feature = this.features.get(id); if (!feature) { + throw new Error(`Feature ${id} has not been registered`); + } + if (this.disabledFeatures.includes(id)) { return { - avaliable: false, - reason: `Feature ${id} has not been registered`, + available: false, + steps: new Map(), + message: "Feature is disabled", }; } - await feature.mutex.wait(); - try { + return await feature.mutex.synchronise(async () => { const cachedState = this.stateCache.get(id); - if (cachedState) { - if (!force) { - return cachedState; - } - cachedState._dirty = true; + if (cachedState && !force) { + return cachedState; } - - const state = await new Promise((resolve, reject) => { - const changeListener = this.onDidChangeState( - id, - (state) => { - changeListener.dispose(); - resolve(state); - }, - this - ); - feature.feature.check().catch((e) => { - changeListener.dispose(); - reject(e); - }); - }).catch((e) => { + try { + await feature.check(); + } catch (e) { logging.NamedLogger.getOrCreate(Loggers.Extension).error( `Error checking feature state ${id}`, e ); - }); - - if (state !== undefined) { - return state; } - - throw new Error(`Feature ${id} is not available`); - } finally { - feature.mutex.signal(); - } + return feature.state; + }); } dispose() { diff --git a/packages/databricks-vscode/src/feature-manager/MultiStepAccessVerfier.ts b/packages/databricks-vscode/src/feature-manager/MultiStepAccessVerfier.ts index c6ac31451..d41b9ac2d 100644 --- a/packages/databricks-vscode/src/feature-manager/MultiStepAccessVerfier.ts +++ b/packages/databricks-vscode/src/feature-manager/MultiStepAccessVerfier.ts @@ -1,108 +1,88 @@ import {Disposable, EventEmitter} from "vscode"; -import {Feature, FeatureEnableAction, FeatureState} from "./FeatureManager"; +import { + Feature, + FeatureEnableAction, + FeatureState, + FeatureStepState, +} from "./FeatureManager"; +import lodash from "lodash"; +import {Mutex} from "../locking"; export type AccessVerifierStep = (...args: any) => Promise; export abstract class MultiStepAccessVerifier implements Feature { + public mutex = new Mutex(); protected disposables: Disposable[] = []; - // Fired when the state of the entire feature changes (all steps are accepted, or >=1 steps are rejected) protected onDidChangeStateEmitter = new EventEmitter(); public onDidChangeState = this.onDidChangeStateEmitter.event; - // Fired when the state of a single step changes (accepted or rejected) - protected onDidChangeStepStateEmitter = new EventEmitter<{ - id: string; - value: boolean; - }>(); - public onDidChangeStepState = this.onDidChangeStepStateEmitter.event; - - public readonly stepValues: Record = {}; + public readonly state: FeatureState = {available: false, steps: new Map()}; constructor(steps: string[]) { - steps.forEach((step) => (this.stepValues[step] = false)); + steps.forEach((step) => + this.state.steps.set(step, {id: step, available: false}) + ); } - private stepValuesHas(key: string) { - if (!Object.keys(this.stepValues).includes(key)) { + private assertStep(key: string) { + if (!this.state.steps.has(key)) { throw Error(`Verification step ${key} is not registered.`); } } - private checkAllStepValues() { - const combinedValue = Object.values(this.stepValues).reduce( - (prev, current) => prev && current, + private updateStep(stepState: FeatureStepState) { + this.assertStep(stepState.id); + const oldStepState = this.state.steps.get(stepState.id); + this.state.steps.set(stepState.id, stepState); + const oldAvailability = this.state.available; + this.state.available = Array.from(this.state.steps).reduce( + (result, current) => result && current[1].available, true ); - if (combinedValue) { - this.accept(); + const nonComparableFields: Array = ["action"]; + if ( + oldAvailability !== this.state.available || + !lodash.isEqual( + lodash.omit(oldStepState, nonComparableFields), + lodash.omit(stepState, nonComparableFields) + ) + ) { + this.onDidChangeStateEmitter.fire(this.state); } - return combinedValue; + return stepState; } + /** * Reject the current step in the verification process. * @param id of the step - * @param reason reason for rejection + * @param title reason for rejection * @param action action to take that can resolve the rejection * @param isDisabledByFf if the rejection is caused by a feature flag then set this to true. * @returns */ rejectStep( id: string, - reason?: string, + title: string, + message?: string, action?: FeatureEnableAction, isDisabledByFf?: boolean ) { - this.stepValuesHas(id); - if (this.stepValues[id]) { - this.onDidChangeStepStateEmitter.fire({ - id, - value: false, - }); - } - this.stepValues[id] = false; - const state: FeatureState = { - avaliable: false, - reason, + return this.updateStep({ + id: id, + available: false, + title, + message, action, isDisabledByFf: isDisabledByFf === true, - }; - - this.onDidChangeStateEmitter.fire(state); - return state; - } - - acceptStep(id: string) { - this.stepValuesHas(id); - if (!this.stepValues[id]) { - this.onDidChangeStepStateEmitter.fire({ - id, - value: true, - }); - } - this.stepValues[id] = true; - this.checkAllStepValues(); - return true; - } - - private accept() { - const state = { - avaliable: true, - }; - this.onDidChangeStateEmitter.fire(state); - return state; + }); } - protected async waitForStep(id: string) { - this.stepValuesHas(id); - if (this.stepValues[id]) { - return true; - } - await new Promise((resolve) => { - const changeListener = this.onDidChangeStepState((e) => { - if (e.id === id && e.value === true) { - resolve(); - changeListener.dispose(); - } - }); + acceptStep(id: string, title?: string, message?: string, warning?: string) { + return this.updateStep({ + id: id, + available: true, + title, + message, + warning, }); } diff --git a/packages/databricks-vscode/src/file-managers/DatabricksEnvFileManager.ts b/packages/databricks-vscode/src/file-managers/DatabricksEnvFileManager.ts index 3af5837dd..360deb580 100644 --- a/packages/databricks-vscode/src/file-managers/DatabricksEnvFileManager.ts +++ b/packages/databricks-vscode/src/file-managers/DatabricksEnvFileManager.ts @@ -1,38 +1,39 @@ -import { - Disposable, - Uri, - workspace, - ExtensionContext, - EventEmitter, -} from "vscode"; -import {writeFile, readFile} from "fs/promises"; +import {Disposable, Uri, workspace, EventEmitter} from "vscode"; +import {writeFile, readFile, stat} from "fs/promises"; import {FeatureManager} from "../feature-manager/FeatureManager"; import {ConnectionManager} from "../configuration/ConnectionManager"; import os from "node:os"; -import * as path from "node:path"; import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {SystemVariables} from "../vscode-objs/SystemVariables"; import {logging} from "@databricks/databricks-sdk"; import {Loggers} from "../logger"; import {Context, context} from "@databricks/databricks-sdk/dist/context"; -import {DbConnectStatusBarButton} from "../language/DbConnectStatusBarButton"; import {EnvVarGenerators, FileUtils} from "../utils"; -import {NotebookInitScriptManager} from "../language/notebooks/NotebookInitScriptManager"; import {Mutex} from "../locking/Mutex"; +import {ConfigModel} from "../configuration/models/ConfigModel"; +import path from "path"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; -function isValidUserEnvPath( - path: string | undefined, - excludes: string[] -): path is string { - return path !== undefined && !excludes.includes(path); -} export class DatabricksEnvFileManager implements Disposable { private disposables: Disposable[] = []; + private userEnvFileWatcherDisposables: Disposable[] = []; private mutex = new Mutex(); - private readonly unresolvedDatabricksEnvFile: string; - private readonly databricksEnvPath: Uri; - private readonly unresolvedUserEnvFile: string; - private readonly userEnvPath: Uri; + private userEnvPath?: Uri; + private showDatabricksConnectProgess = true; + + get databricksEnvPath() { + return Uri.joinPath( + this.workspacePath, + ".databricks", + ".databricks.env" + ); + } + private get systemVariableResolver() { + return new SystemVariables(this.workspacePath); + } + private get workspacePath() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri; + } private readonly onDidChangeEnvironmentVariablesEmitter = new EventEmitter(); @@ -40,62 +41,51 @@ export class DatabricksEnvFileManager implements Disposable { this.onDidChangeEnvironmentVariablesEmitter.event; constructor( - private readonly workspacePath: Uri, + private readonly workspaceFolderManager: WorkspaceFolderManager, private readonly featureManager: FeatureManager, - private readonly dbConnectStatusBarButton: DbConnectStatusBarButton, private readonly connectionManager: ConnectionManager, - private readonly extensionContext: ExtensionContext, - private readonly notebookInitScriptManager: NotebookInitScriptManager + private readonly configModel: ConfigModel ) { - const systemVariableResolver = new SystemVariables(workspacePath); - this.unresolvedDatabricksEnvFile = path.join( - "${workspaceFolder}", - ".databricks", - ".databricks.env" - ); - this.databricksEnvPath = Uri.file( - systemVariableResolver.resolve(this.unresolvedDatabricksEnvFile) - ); - //Try to get user specified .env file fron databricks.python.envFile config - //If that is not found, then try to read python.envFile config - //Default to ${workspaceFolder}/.env. - this.unresolvedUserEnvFile = isValidUserEnvPath( - workspaceConfigs.userEnvFile, - [this.unresolvedDatabricksEnvFile, this.databricksEnvPath.fsPath] - ) - ? workspaceConfigs.userEnvFile - : isValidUserEnvPath(workspaceConfigs.msPythonEnvFile, [ - this.unresolvedDatabricksEnvFile, - this.databricksEnvPath.fsPath, - ]) - ? workspaceConfigs.msPythonEnvFile - : path.join("${workspaceFolder}", ".env"); - this.userEnvPath = Uri.file( - systemVariableResolver.resolve(this.unresolvedUserEnvFile) - ); - logging.NamedLogger.getOrCreate(Loggers.Extension).debug( - "Env file locations", - { - unresolvedDatabricksEnvFile: this.unresolvedDatabricksEnvFile, - unresolvedUserEnvFile: this.unresolvedUserEnvFile, - msEnvFile: workspaceConfigs.msPythonEnvFile, - } - ); + this.showDatabricksConnectProgess = + workspaceConfigs.showDatabricksConnectProgress; } - public async init() { - await FileUtils.waitForDatabricksProject( - this.workspacePath, - this.connectionManager - ); - workspaceConfigs.msPythonEnvFile = this.unresolvedDatabricksEnvFile; - workspaceConfigs.userEnvFile = this.unresolvedUserEnvFile; + private async updateShowDatabricksConnectProgessWatcher() { + if ( + this.showDatabricksConnectProgess === + workspaceConfigs.showDatabricksConnectProgress + ) { + return; + } + + this.showDatabricksConnectProgess = + workspaceConfigs.showDatabricksConnectProgress; + await this.writeFile(); + } + + private updateUserEnvFileWatcher() { + const userEnvPath = workspaceConfigs.msPythonEnvFile + ? Uri.file( + this.systemVariableResolver.resolve( + workspaceConfigs.msPythonEnvFile + ) + ) + : undefined; + if (userEnvPath?.fsPath !== this.userEnvPath?.fsPath) { + this.userEnvPath = userEnvPath; + } + + this.userEnvFileWatcherDisposables.forEach((i) => i.dispose()); + + if (this.userEnvPath === undefined) { + return; + } const userEnvFileWatcher = workspace.createFileSystemWatcher( this.userEnvPath.fsPath ); - this.disposables.push( + this.userEnvFileWatcherDisposables.push( userEnvFileWatcher, userEnvFileWatcher.onDidChange(async () => { await this.writeFile(); @@ -105,24 +95,55 @@ export class DatabricksEnvFileManager implements Disposable { }, this), userEnvFileWatcher.onDidCreate(async () => { await this.writeFile(); - }, this), - this.featureManager.onDidChangeState( - "notebooks.dbconnect", - async () => { - await this.writeFile(); - } + }, this) + ); + } + + public async init() { + await FileUtils.waitForDatabricksProject( + this.workspacePath, + this.connectionManager + ); + + const userEnvPath = workspaceConfigs.msPythonEnvFile + ? Uri.file( + this.systemVariableResolver.resolve( + workspaceConfigs.msPythonEnvFile + ) + ) + : undefined; + + if (userEnvPath?.fsPath === this.databricksEnvPath.fsPath) { + workspaceConfigs.msPythonEnvFile = path.join( + "${workspaceRoot}", + ".env" + ); + } + + this.updateUserEnvFileWatcher(); + + this.disposables.push( + workspace.onDidChangeConfiguration( + this.updateUserEnvFileWatcher, + this, + this.disposables + ), + workspace.onDidChangeConfiguration( + this.updateShowDatabricksConnectProgessWatcher, + this, + this.disposables ), this.featureManager.onDidChangeState( - "debugging.dbconnect", + "environment.dependencies", () => { this.writeFile(); }, this ), - this.connectionManager.onDidChangeCluster(async () => { + this.connectionManager.onDidChangeCluster(() => { this.writeFile(); }, this), - this.connectionManager.onDidChangeState(async () => { + this.connectionManager.onDidChangeState(() => { this.writeFile(); }, this) ); @@ -130,7 +151,8 @@ export class DatabricksEnvFileManager implements Disposable { private getDatabrickseEnvVars() { return EnvVarGenerators.getCommonDatabricksEnvVars( - this.connectionManager + this.connectionManager, + this.configModel ); } @@ -140,26 +162,44 @@ export class DatabricksEnvFileManager implements Disposable { //Get env variables from user's .env file private async getUserEnvVars() { + if (this.userEnvPath === undefined) { + return; + } + try { + await stat(this.userEnvPath.fsPath); + } catch (err) { + logging.NamedLogger.getOrCreate(Loggers.Extension).debug( + `${this.userEnvPath.fsPath} does not exist. Not loading user env vars and continuing.` + ); + return; + } return await EnvVarGenerators.getUserEnvVars(this.userEnvPath); } - @logging.withLogContext(Loggers.Extension) - async writeFile(@context ctx?: Context) { - await this.connectionManager.waitForConnect(); - - await this.mutex.wait(); - try { - const data = Object.entries({ + async getEnv() { + return Object.fromEntries( + Object.entries({ ...(this.getDatabrickseEnvVars() || {}), ...((await EnvVarGenerators.getDbConnectEnvVars( this.connectionManager, - this.workspacePath + this.workspacePath, + this.showDatabricksConnectProgess )) || {}), ...this.getIdeEnvVars(), ...((await this.getUserEnvVars()) || {}), - }) - .filter(([, value]) => value !== undefined) - .map(([key, value]) => `${key}=${value}`); + }).filter(([, value]) => value !== undefined) as [string, string][] + ); + } + + @logging.withLogContext(Loggers.Extension) + async writeFile(@context ctx?: Context) { + await this.connectionManager.waitForConnect(); + + await this.mutex.wait(); + try { + const data = Object.entries(await this.getEnv()).map( + ([key, value]) => `${key}=${value}` + ); data.sort(); try { const oldData = await readFile( @@ -172,15 +212,13 @@ export class DatabricksEnvFileManager implements Disposable { } catch (e) { ctx?.logger?.info("Error reading old databricks.env file", e); } - this.onDidChangeEnvironmentVariablesEmitter.fire(); try { await writeFile( this.databricksEnvPath.fsPath, data.join(os.EOL), "utf-8" ); - this.dbConnectStatusBarButton.update(); - await this.emitToTerminal(); + this.onDidChangeEnvironmentVariablesEmitter.fire(); } catch (e) { ctx?.logger?.info("Error writing databricks.env file", e); } @@ -189,37 +227,7 @@ export class DatabricksEnvFileManager implements Disposable { } } - async emitToTerminal() { - this.clearTerminalEnv(); - this.extensionContext.environmentVariableCollection.persistent = false; - Object.entries({ - ...(this.getDatabrickseEnvVars() || {}), - ...this.getIdeEnvVars(), - ...((await EnvVarGenerators.getDbConnectEnvVars( - this.connectionManager, - this.workspacePath - )) || {}), - }).forEach(([key, value]) => { - if (value === undefined) { - return; - } - this.extensionContext.environmentVariableCollection.replace( - key, - value - ); - }); - this.extensionContext.environmentVariableCollection.prepend( - "PATH", - `${this.extensionContext.asAbsolutePath("./bin")}${path.delimiter}` - ); - } - - async clearTerminalEnv() { - this.extensionContext.environmentVariableCollection.clear(); - } - dispose() { - this.clearTerminalEnv(); this.disposables.forEach((i) => i.dispose()); } } diff --git a/packages/databricks-vscode/src/file-managers/ProjectConfigFile.test.ts b/packages/databricks-vscode/src/file-managers/ProjectConfigFile.test.ts index 5c72f8606..0c52d3dd6 100644 --- a/packages/databricks-vscode/src/file-managers/ProjectConfigFile.test.ts +++ b/packages/databricks-vscode/src/file-managers/ProjectConfigFile.test.ts @@ -1,12 +1,14 @@ /* eslint-disable @typescript-eslint/naming-convention */ -import {mkdir, mkdtemp, readFile, writeFile} from "fs/promises"; -import {ProjectConfig, ProjectConfigFile} from "./ProjectConfigFile"; +import {mkdir, mkdtemp, writeFile} from "fs/promises"; +import {ProjectConfigFile} from "./ProjectConfigFile"; import * as assert from "assert"; import path from "path"; import * as os from "os"; import {ProfileAuthProvider} from "../configuration/auth/AuthProvider"; import {Uri} from "vscode"; +import {instance, mock, when} from "ts-mockito"; +import {CliWrapper} from "../cli/CliWrapper"; describe(__filename, () => { let tempDir: string; @@ -14,32 +16,6 @@ describe(__filename, () => { tempDir = await mkdtemp(path.join(os.tmpdir(), "ProjectConfTests-")); }); - it("should write config file", async () => { - const authProvider = new ProfileAuthProvider( - new URL("https://000000000000.00.azuredatabricks.net/"), - "testProfile" - ); - const expected: ProjectConfig = { - authProvider: authProvider, - clusterId: "testClusterId", - workspacePath: Uri.from({scheme: "wsfs", path: "workspacePath"}), - }; - await new ProjectConfigFile(expected, tempDir, "databricks").write(); - - const rawData = await readFile( - ProjectConfigFile.getProjectConfigFilePath(tempDir), - {encoding: "utf-8"} - ); - const actual = JSON.parse(rawData); - assert.deepEqual(actual, { - host: "https://000000000000.00.azuredatabricks.net/", - authType: "profile", - profile: "testProfile", - workspacePath: "workspacePath", - clusterId: "testClusterId", - }); - }); - it("should load config file", async () => { const configFile = ProjectConfigFile.getProjectConfigFilePath(tempDir); await mkdir(path.dirname(configFile), {recursive: true}); @@ -55,7 +31,12 @@ describe(__filename, () => { encoding: "utf-8", }); - const actual = await ProjectConfigFile.load(tempDir, "databricks"); + const mockCliWrapper = mock(CliWrapper); + when(mockCliWrapper.cliPath).thenReturn("databricks"); + const actual = (await ProjectConfigFile.load( + tempDir, + instance(mockCliWrapper) + ))!; assert.equal(actual.host.toString(), config.host); assert.ok(actual.authProvider instanceof ProfileAuthProvider); assert.equal(actual.authProvider.authType, config.authType); @@ -99,7 +80,12 @@ token = testToken`, tempDir, ".databrickscfg" ); - const actual = await ProjectConfigFile.load(tempDir, "databricks"); + const mockCliWrapper = mock(CliWrapper); + when(mockCliWrapper.cliPath).thenReturn("databricks"); + const actual = (await ProjectConfigFile.load( + tempDir, + instance(mockCliWrapper) + ))!; assert.equal( actual.host.toString(), "https://000000000000.00.azuredatabricks.net/" diff --git a/packages/databricks-vscode/src/file-managers/ProjectConfigFile.ts b/packages/databricks-vscode/src/file-managers/ProjectConfigFile.ts index 6d7ea89fa..234685d55 100644 --- a/packages/databricks-vscode/src/file-managers/ProjectConfigFile.ts +++ b/packages/databricks-vscode/src/file-managers/ProjectConfigFile.ts @@ -5,9 +5,7 @@ import { ProfileAuthProvider, } from "../configuration/auth/AuthProvider"; import {Uri} from "vscode"; -import {Loggers} from "../logger"; -import {Config, logging} from "@databricks/databricks-sdk"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; +import {CliWrapper} from "../cli/CliWrapper"; export interface ProjectConfig { authProvider: AuthProvider; @@ -36,18 +34,10 @@ export class ProjectConfigFile { return this.config.clusterId; } - set clusterId(clusterId: string | undefined) { - this.config.clusterId = clusterId; - } - get workspacePath(): Uri | undefined { return this.config.workspacePath; } - set workspacePath(workspacePath: Uri | undefined) { - this.config.workspacePath = workspacePath; - } - toJSON(): Record { return { ...this.config.authProvider.toJSON(), @@ -56,85 +46,49 @@ export class ProjectConfigFile { }; } - async write() { - try { - const originalConfig = await ProjectConfigFile.load( - this.rootPath, - this.cliPath - ); - if ( - JSON.stringify(originalConfig.toJSON(), null, 2) === - JSON.stringify(this.toJSON(), null, 2) - ) { - return; - } - } catch (e) {} - - const fileName = ProjectConfigFile.getProjectConfigFilePath( - this.rootPath - ); - await fs.mkdir(path.dirname(fileName), {recursive: true}); - - await fs.writeFile(fileName, JSON.stringify(this, null, 2), { - encoding: "utf-8", - }); + static async importOldConfig( + config: any, + cli: CliWrapper + ): Promise { + return await ProfileAuthProvider.from(config.profile, cli); } - static async importOldConfig(config: any): Promise { - const sdkConfig = new Config({ - profile: config.profile, - configFile: - workspaceConfigs.databrickscfgLocation ?? - process.env.DATABRICKS_CONFIG_FILE, - env: {}, - }); - - await sdkConfig.ensureResolved(); - - return new ProfileAuthProvider( - new URL(sdkConfig.host!), - sdkConfig.profile! + static async loadConfig( + rootPath: string + ): Promise | undefined> { + const projectConfigFilePath = path.join( + path.normalize(rootPath), + ".databricks", + "project.json" ); - } - - static async load( - rootPath: string, - cliPath: string - ): Promise { - const projectConfigFilePath = this.getProjectConfigFilePath(rootPath); - let rawConfig; try { rawConfig = await fs.readFile(projectConfigFilePath, { encoding: "utf-8", }); - } catch (e: any) { - if (e.code && e.code === "ENOENT") { - throw new ConfigFileError( - `Project config file does not exist: ${projectConfigFilePath}` - ); + } catch (error: any) { + if (error?.code === "ENOENT") { + return undefined; } else { - throw e; + throw error; } } + return JSON.parse(rawConfig); + } + static async load( + rootPath: string, + cli: CliWrapper + ): Promise { + const config = await ProjectConfigFile.loadConfig(rootPath); + if (!config) { + return undefined; + } let authProvider: AuthProvider; - let config: any; - try { - config = JSON.parse(rawConfig); - if (!config.authType && config.profile) { - authProvider = await this.importOldConfig(config); - } else { - authProvider = AuthProvider.fromJSON(config, cliPath); - } - } catch (e: any) { - logging.NamedLogger.getOrCreate(Loggers.Extension).error( - "Error parsing project config file", - e - ); - throw new ConfigFileError( - `Error parsing project config file: ${e.message}` - ); + if (!config.authType && config.profile) { + authProvider = await this.importOldConfig(config, cli); + } else { + authProvider = AuthProvider.fromJSON(config, cli); } return new ProjectConfigFile( { @@ -149,7 +103,7 @@ export class ProjectConfigFile { : undefined, }, rootPath, - cliPath + cli.cliPath ); } diff --git a/packages/databricks-vscode/src/file-managers/ProjectConfigFileWatcher.ts b/packages/databricks-vscode/src/file-managers/ProjectConfigFileWatcher.ts deleted file mode 100644 index 7f4e8287a..000000000 --- a/packages/databricks-vscode/src/file-managers/ProjectConfigFileWatcher.ts +++ /dev/null @@ -1,78 +0,0 @@ -import {Disposable, workspace} from "vscode"; -import {ConnectionManager} from "../configuration/ConnectionManager"; -import {ProjectConfigFile} from "./ProjectConfigFile"; -import {RemoteUri} from "../sync/SyncDestination"; - -export class ProjectConfigFileWatcher implements Disposable { - private disposables: Array = []; - constructor( - readonly connectionManager: ConnectionManager, - rootPath: string, - cliPath: string - ) { - const fileSystemWatcher = workspace.createFileSystemWatcher( - ProjectConfigFile.getProjectConfigFilePath(rootPath) - ); - - this.disposables.push( - fileSystemWatcher, - fileSystemWatcher.onDidCreate(async () => { - switch (this.connectionManager.state) { - case "DISCONNECTED": - await this.connectionManager.login(); - break; - case "CONNECTING": - await this.connectionManager.waitForConnect(); - break; - case "CONNECTED": - return; - } - }, this), - fileSystemWatcher.onDidChange(async () => { - const configFile = await ProjectConfigFile.load( - rootPath, - cliPath - ); - if (this.connectionManager.state === "CONNECTING") { - await this.connectionManager.waitForConnect(); - } - if ( - configFile.host.toString() !== - connectionManager.databricksWorkspace?.host.toString() || - configFile.authProvider.authType !== - connectionManager.databricksWorkspace?.authProvider - .authType - ) { - await connectionManager.login(false, true); - } - if (connectionManager.cluster?.id !== configFile.clusterId) { - if (configFile.clusterId) { - await connectionManager.attachCluster( - configFile.clusterId - ); - } else { - await connectionManager.detachCluster(); - } - } - if ( - connectionManager.syncDestinationMapper?.remoteUri.path !== - configFile.workspacePath?.path - ) { - if (configFile.workspacePath) { - await connectionManager.attachSyncDestination( - new RemoteUri(configFile.workspacePath?.path) - ); - } else { - await connectionManager.detachSyncDestination(); - } - } - }, this), - fileSystemWatcher.onDidDelete(async () => { - await connectionManager.logout(); - }, this) - ); - } - dispose() { - this.disposables.forEach((item) => item.dispose()); - } -} diff --git a/packages/databricks-vscode/src/language/ConfigureAutocomplete.ts b/packages/databricks-vscode/src/language/ConfigureAutocomplete.ts index 102359e95..f7fa504de 100644 --- a/packages/databricks-vscode/src/language/ConfigureAutocomplete.ts +++ b/packages/databricks-vscode/src/language/ConfigureAutocomplete.ts @@ -11,7 +11,8 @@ import { import {Loggers} from "../logger"; import {StateStorage} from "../vscode-objs/StateStorage"; import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; -import {DbConnectInstallPrompt} from "./DbConnectInstallPrompt"; +import {EnvironmentDependenciesInstaller} from "./EnvironmentDependenciesInstaller"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; async function getImportString(context: ExtensionContext) { try { @@ -43,9 +44,9 @@ export class ConfigureAutocomplete implements Disposable { constructor( private readonly context: ExtensionContext, private readonly stateStorage: StateStorage, - private readonly workspaceFolder: string, + private readonly workspaceFolderManager: WorkspaceFolderManager, private readonly pythonExtension: MsPythonExtensionWrapper, - private readonly dbConnectInstallPrompt: DbConnectInstallPrompt + private readonly environmentDependenciesInstaller: EnvironmentDependenciesInstaller ) { //Remove any type stubs that users already have. We will now start using the python SDK (installed with databricks-connect) let extraPaths = @@ -170,7 +171,11 @@ export class ConfigureAutocomplete implements Disposable { if (dryRun) { return; } - this.dbConnectInstallPrompt.show(false); + this.environmentDependenciesInstaller.show(false); + } + + private get workspaceFolder() { + return this.workspaceFolderManager.activeWorkspaceFolder.uri.fsPath; } private async addBuiltinsFile(dryRun = false): Promise { diff --git a/packages/databricks-vscode/src/language/DbConnectAccessVerifier.ts b/packages/databricks-vscode/src/language/DbConnectAccessVerifier.ts deleted file mode 100644 index 76d5ec039..000000000 --- a/packages/databricks-vscode/src/language/DbConnectAccessVerifier.ts +++ /dev/null @@ -1,187 +0,0 @@ -import {logging} from "@databricks/databricks-sdk"; -import {Cluster} from "../sdk-extensions"; -import {window, commands} from "vscode"; -import {ConnectionManager} from "../configuration/ConnectionManager"; -import {MultiStepAccessVerifier} from "../feature-manager/MultiStepAccessVerfier"; -import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; -import {Loggers} from "../logger"; -import {Context, context} from "@databricks/databricks-sdk/dist/context"; -import {DbConnectInstallPrompt} from "./DbConnectInstallPrompt"; -import {FeatureState} from "../feature-manager/FeatureManager"; -import {DATABRICKS_CONNECT_VERSION} from "../utils/constants"; - -export class DbConnectAccessVerifier extends MultiStepAccessVerifier { - constructor( - private readonly connectionManager: ConnectionManager, - private readonly pythonExtension: MsPythonExtensionWrapper, - private readonly dbConnectInstallPrompt: DbConnectInstallPrompt - ) { - super(["checkCluster", "checkWorkspaceHasUc", "checkDbConnectInstall"]); - this.disposables.push( - this.connectionManager.onDidChangeCluster((cluster) => { - if (this.connectionManager.state !== "CONNECTED") { - return; - } - this.checkCluster(cluster); - }, this), - this.connectionManager.onDidChangeState((e) => { - if (e !== "CONNECTED") { - return; - } - this.checkWorkspaceHasUc(); - }, this), - this.pythonExtension.onDidChangePythonExecutable(async () => { - const check = await this.checkDbConnectInstall(); - if ( - typeof check !== "boolean" && - check.reason?.includes( - "databricks-connect package is not installed" - ) && - check.action - ) { - check.action(true); - } - }, this) - ); - } - - promptForAttachingCluster(msg: string) { - return async () => { - const choice = await window.showInformationMessage( - msg, - "Attach Cluster", - "Ignore" - ); - switch (choice) { - case "Attach Cluster": - commands.executeCommand( - "databricks.connection.attachClusterQuickPick" - ); - } - }; - } - - async checkCluster(cluster?: Cluster) { - if (cluster === undefined) { - return this.rejectStep( - "checkCluster", - "No cluster attached", - this.promptForAttachingCluster( - "Please attach a cluster to use Databricks Connect." - ) - ); - } - await this.connectionManager.waitForConnect(); - - const dbrVersionParts = cluster?.dbrVersion; - if ( - !dbrVersionParts || - (dbrVersionParts[0] !== "x" && dbrVersionParts[0] < 13) - ) { - return this.rejectStep( - "checkCluster", - `Databricks Connect requires cluster DBR >= 13.0.0.`, - this.promptForAttachingCluster( - `Databricks Connect requires cluster DBR >= 13.0.0. Currently it is ${dbrVersionParts.join( - "." - )}. Please attach a new cluster.` - ) - ); - } - if (!cluster.isUc()) { - return this.rejectStep( - "checkCluster", - `Cluster doesn't have UC enabled.`, - this.promptForAttachingCluster( - `Databricks Connect requires a Unity Catalog enabled cluster with Access Mode "Single User" or "Shared". Currently it is ${ - cluster.accessMode ?? "custom" - }. Please attach a new cluster.` - ) - ); - } - return this.acceptStep("checkCluster"); - } - - @logging.withLogContext(Loggers.Extension) - async checkWorkspaceHasUc(@context ctx?: Context) { - this.connectionManager.waitForConnect(); - try { - const catalogList = - this.connectionManager.workspaceClient?.catalogs.list(); - const catalogListIter = catalogList - ? catalogList[Symbol.asyncIterator]() - : undefined; - - if (!(await catalogListIter?.next())) { - return this.rejectStep( - "checkWorkspaceHasUc", - "No catalogues with read permission were found. Please enable UC for the workspace." - ); - } - } catch (e: unknown) { - if (e instanceof Error) { - ctx?.logger?.error("Error while searching for catalogues", e); - return this.rejectStep("checkWorkspaceHasUc", e.message); - } - } - return this.acceptStep("checkWorkspaceHasUc"); - } - - async checkDbConnectInstall(): Promise { - const executable = await this.pythonExtension.getPythonExecutable(); - if (!executable) { - return this.rejectStep( - "checkDbConnectInstall", - "No python executable found." - ); - } - const env = await this.pythonExtension.pythonEnvironment; - if ( - env && - env.version && - !( - env.version.major > 3 || - (env.version.major === 3 && env.version.minor >= 10) - ) - ) { - return this.rejectStep( - "checkDbConnectInstall", - `Databricks Connect requires python >= 3.10.0. Current version is ${[ - env.version.major, - env.version.minor, - env.version.micro, - ].join(".")}.` - ); - } - try { - const exists = await this.pythonExtension.findPackageInEnvironment( - "databricks-connect", - DATABRICKS_CONNECT_VERSION - ); - if (exists) { - return this.acceptStep("checkDbConnectInstall"); - } - return this.rejectStep( - "checkDbConnectInstall", - "databricks-connect package is not installed in the current environment", - (advertisement = false) => - this.dbConnectInstallPrompt.show(advertisement, () => - this.checkDbConnectInstall() - ) - ); - } catch (e: unknown) { - if (e instanceof Error) { - window.showErrorMessage(e.message); - return this.rejectStep("checkDbConnectInstall", e.message); - } - return this.rejectStep("checkDbConnectInstall", e as string); - } - } - - override async check() { - await this.connectionManager.waitForConnect(); - this.checkCluster(this.connectionManager.cluster); - this.checkWorkspaceHasUc(); - this.checkDbConnectInstall(); - } -} diff --git a/packages/databricks-vscode/src/language/DbConnectInstallPrompt.ts b/packages/databricks-vscode/src/language/DbConnectInstallPrompt.ts deleted file mode 100644 index 38b5690d2..000000000 --- a/packages/databricks-vscode/src/language/DbConnectInstallPrompt.ts +++ /dev/null @@ -1,99 +0,0 @@ -import {window} from "vscode"; - -import {Disposable} from "vscode"; -import {StateStorage} from "../vscode-objs/StateStorage"; -import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; -import {DATABRICKS_CONNECT_VERSION} from "../utils/constants"; - -export class DbConnectInstallPrompt implements Disposable { - private disposables: Disposable[] = []; - - constructor( - private readonly stateStorage: StateStorage, - private readonly pythonExtension: MsPythonExtensionWrapper - ) {} - - dispose() { - this.disposables.forEach((i) => i.dispose()); - } - async show(advertisement = false, cb: () => void = () => {}) { - const executable = await this.pythonExtension.getPythonExecutable(); - if ( - advertisement && - executable && - this.stateStorage - .get("databricks.debugging.skipDbConnectInstallForEnvs") - .includes(executable) - ) { - return; - } - - const hasPyspark = await this.pythonExtension.findPackageInEnvironment( - "pyspark" - ); - - const dbConnectDetails = - await this.pythonExtension.getPackageDetailsFromEnvironment( - "databricks-connect" - ); - - const hasDbConnect = !hasPyspark && dbConnectDetails !== undefined; - const env = (await this.pythonExtension.pythonEnvironment)?.environment; - - const mainMessagePart = advertisement - ? "Interactive debugging in PySpark is now available. Start using it by installing Databricks Connect in the" - : "For interactive debugging and autocompletion you need Databricks Connect. Would you like to install it in the"; - const envMessagePart = env - ? "environment " + env.name - : "current environment"; - const pkgUpdateMessagePart = hasPyspark - ? "(pyspark will be uninstalled)" - : hasDbConnect - ? `(databricks-connect will be updated to the latest version: ${dbConnectDetails.version} -> ${DATABRICKS_CONNECT_VERSION} )` - : ""; - const message = `${mainMessagePart} ${envMessagePart}. ${pkgUpdateMessagePart}`; - - const choices = [ - "Install", - "Change environment", - advertisement ? "Never for this environment" : undefined, - ].filter((value) => value !== undefined) as string[]; - - const choice = await window.showInformationMessage(message, ...choices); - - switch (choice) { - case "Install": - try { - await this.pythonExtension.uninstallPackageFromEnvironment( - "pyspark" - ); - await this.pythonExtension.uninstallPackageFromEnvironment( - "databricks-connect" - ); - await this.pythonExtension.installPackageInEnvironment( - "databricks-connect", - DATABRICKS_CONNECT_VERSION - ); - cb(); - } catch (e: unknown) { - if (e instanceof Error) { - window.showErrorMessage(e.message); - } - } - break; - - case "Never for this environment": - if (executable) { - this.stateStorage.set( - "databricks.debugging.skipDbConnectInstallForEnvs", - [executable] - ); - } - break; - - case "Change environment": - await this.pythonExtension.selectPythonInterpreter(); - break; - } - } -} diff --git a/packages/databricks-vscode/src/language/DbConnectStatusBarButton.ts b/packages/databricks-vscode/src/language/DbConnectStatusBarButton.ts index 7c73522ec..08e03a133 100644 --- a/packages/databricks-vscode/src/language/DbConnectStatusBarButton.ts +++ b/packages/databricks-vscode/src/language/DbConnectStatusBarButton.ts @@ -16,15 +16,22 @@ export class DbConnectStatusBarButton implements Disposable { StatusBarAlignment.Left, 1000 ); - this.disposables.push(this.statusBarButton); + this.disposables.push( + this.statusBarButton, + this.featureManager.onDidChangeState( + "environment.dependencies", + this.update, + this + ) + ); this.disableStatusBarButton(); } private async disableStatusBarButton() { const featureState = await this.featureManager.isEnabled( - "debugging.dbconnect" + "environment.dependencies" ); - if (featureState.isDisabledByFf || featureState.avaliable) { + if (featureState.available) { return; } this.statusBarButton.name = "Databricks Connect disabled"; @@ -32,34 +39,19 @@ export class DbConnectStatusBarButton implements Disposable { this.statusBarButton.backgroundColor = new ThemeColor( "statusBarItem.errorBackground" ); - this.statusBarButton.tooltip = featureState?.reason; + // this.statusBarButton.tooltip = featureState?.message; this.statusBarButton.command = { - title: "Call", - command: "databricks.call", - arguments: [ - async () => { - const featureState = await this.featureManager.isEnabled( - "debugging.dbconnect", - true - ); - if (!featureState.avaliable) { - if (featureState.action) { - featureState.action(); - } else if (featureState.reason) { - window.showErrorMessage(featureState.reason); - } - } - }, - ], + title: "Setup Databricks Connect", + command: "databricks.environment.setup", }; this.statusBarButton.show(); } private async enableStatusBarButton() { const featureState = await this.featureManager.isEnabled( - "debugging.dbconnect" + "environment.dependencies" ); - if (!featureState.avaliable) { + if (!featureState.available) { return; } this.statusBarButton.name = "Databricks Connect enabled"; @@ -67,22 +59,17 @@ export class DbConnectStatusBarButton implements Disposable { this.statusBarButton.tooltip = "Databricks Connect enabled"; this.statusBarButton.backgroundColor = undefined; this.statusBarButton.command = { - title: "Call", - command: "databricks.call", - arguments: [ - () => { - this.featureManager.isEnabled("debugging.dbconnect", true); - }, - ], + title: "Setup Databricks Connect", + command: "databricks.environment.setup", }; this.statusBarButton.show(); } public async update() { const featureState = await this.featureManager.isEnabled( - "debugging.dbconnect" + "environment.dependencies" ); - if (!featureState.avaliable) { + if (!featureState.available) { this.disableStatusBarButton(); } else { this.enableStatusBarButton(); diff --git a/packages/databricks-vscode/src/language/EnvironmentCommands.ts b/packages/databricks-vscode/src/language/EnvironmentCommands.ts new file mode 100644 index 000000000..0fcda445c --- /dev/null +++ b/packages/databricks-vscode/src/language/EnvironmentCommands.ts @@ -0,0 +1,117 @@ +import {window, commands, QuickPickItem} from "vscode"; +import {FeatureManager} from "../feature-manager/FeatureManager"; +import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; +import {Cluster} from "../sdk-extensions"; +import {EnvironmentDependenciesInstaller} from "./EnvironmentDependenciesInstaller"; +import {Environment} from "./MsPythonExtensionApi"; +import {environmentName} from "../utils/environmentUtils"; + +export class EnvironmentCommands { + constructor( + private featureManager: FeatureManager, + private pythonExtension: MsPythonExtensionWrapper, + private installer: EnvironmentDependenciesInstaller + ) {} + + async setup(stepId?: string) { + commands.executeCommand("configurationView.focus"); + await window.withProgress( + {location: {viewId: "configurationView"}}, + () => this._setup(stepId) + ); + } + + private async _setup(stepId?: string) { + const state = await this.featureManager.isEnabled( + "environment.dependencies", + true + ); + if (state.available) { + window.showInformationMessage( + "Python environment and Databricks Connect are already set up." + ); + return true; + } + for (const [, step] of state.steps) { + if (step.available || (stepId && step.id !== stepId)) { + continue; + } + if (step.action) { + return await step.action(); + } else if (step.message) { + window.showErrorMessage(step.message); + return false; + } + } + } + + async refresh() { + await window.withProgress( + {location: {viewId: "configurationView"}}, + () => + this.featureManager.isEnabled("environment.dependencies", true) + ); + } + + async selectPythonInterpreter() { + const environments = + await this.pythonExtension.getAvailableEnvironments(); + if (environments.length > 0) { + await this.showEnvironmentsQuickPick(environments); + } else { + await this.pythonExtension.createPythonEnvironment(); + } + } + + async showEnvironmentsQuickPick(environments: Environment[]) { + const envPicks: (QuickPickItem & {path?: string})[] = environments.map( + (env) => ({ + label: environmentName(env), + description: env.path, + path: env.path, + }) + ); + const createNewLabel = "$(add) Create new environment"; + const usePythonExtensionLabel = + "$(gear) Use Python Extension to setup environments"; + const staticPicks: QuickPickItem[] = [ + {label: createNewLabel, alwaysShow: true}, + {label: usePythonExtensionLabel, alwaysShow: true}, + ]; + const selectedPick = await window.showQuickPick( + envPicks.concat(staticPicks), + {title: "Select Python Environment"} + ); + if (selectedPick) { + if (selectedPick.label === createNewLabel) { + await this.pythonExtension.createPythonEnvironment(); + } else if (selectedPick.label === usePythonExtensionLabel) { + await this.pythonExtension.selectPythonInterpreter(); + } else if (selectedPick.path) { + await this.pythonExtension.api.environments.updateActiveEnvironmentPath( + selectedPick.path + ); + } + } + } + + async reinstallDBConnect(cluster?: Cluster) { + const state = await this.featureManager.isEnabled( + "environment.dependencies" + ); + const envAvailable = state.steps.get("checkPythonEnvironment") + ?.available; + if (!envAvailable) { + window.showErrorMessage("Activate a python environment first."); + return; + } + + let placeholderVersion = undefined; + const dbrVersionParts = cluster?.dbrVersion; + if (dbrVersionParts && dbrVersionParts[0] !== "x") { + const minor = dbrVersionParts[1] === "x" ? "*" : dbrVersionParts[1]; + placeholderVersion = `${dbrVersionParts[0]}.${minor}.*`; + } + return this.installer.installWithVersionPrompt(placeholderVersion); + } +} diff --git a/packages/databricks-vscode/src/language/EnvironmentDependenciesInstaller.ts b/packages/databricks-vscode/src/language/EnvironmentDependenciesInstaller.ts new file mode 100644 index 000000000..a116675b4 --- /dev/null +++ b/packages/databricks-vscode/src/language/EnvironmentDependenciesInstaller.ts @@ -0,0 +1,105 @@ +import {commands, EventEmitter, OutputChannel, window} from "vscode"; + +import {Disposable} from "vscode"; +import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; +import {DATABRICKS_CONNECT_VERSION} from "../utils/constants"; + +export class EnvironmentDependenciesInstaller implements Disposable { + private disposables: Disposable[] = []; + private onDidInstallAttemptEmitter = new EventEmitter(); + public onDidTryInstallation = this.onDidInstallAttemptEmitter.event; + + private _outputChannel?: OutputChannel; + + constructor(private readonly pythonExtension: MsPythonExtensionWrapper) {} + + get outputChannel() { + if (!this._outputChannel) { + this._outputChannel = + window.createOutputChannel("Databricks Connect"); + this.disposables.push(this._outputChannel); + } + return this._outputChannel; + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } + + async install(version?: string) { + version = version ?? DATABRICKS_CONNECT_VERSION; + try { + this.outputChannel.clear(); + this.outputChannel.show(); + await this.pythonExtension.uninstallPackageFromEnvironment( + "pyspark", + this.outputChannel + ); + await this.pythonExtension.uninstallPackageFromEnvironment( + "databricks-connect", + this.outputChannel + ); + await this.pythonExtension.installPackageInEnvironment( + "databricks-connect", + version, + this.outputChannel + ); + } catch (e: unknown) { + if (e instanceof Error) { + window.showErrorMessage(e.message); + } + this.outputChannel.show(); + } + this.onDidInstallAttemptEmitter.fire(); + } + + async installWithVersionPrompt(suggestedVersion?: string) { + const version = await window.showInputBox({ + prompt: "Enter a version of the Databricks Connect", + value: suggestedVersion || DATABRICKS_CONNECT_VERSION, + }); + if (version) { + await this.install(version); + } + } + + async show(advertisement = false) { + const hasPyspark = + await this.pythonExtension.findPackageInEnvironment("pyspark"); + + const dbConnectDetails = + await this.pythonExtension.getPackageDetailsFromEnvironment( + "databricks-connect" + ); + + const hasDbConnect = !hasPyspark && dbConnectDetails !== undefined; + const env = (await this.pythonExtension.pythonEnvironment)?.environment; + + const mainMessagePart = advertisement + ? "Interactive debugging in PySpark is now available. Start using it by installing Databricks Connect in the" + : "For interactive debugging and autocompletion you need Databricks Connect. Would you like to install it in the"; + const envMessagePart = env + ? "environment " + env.name + : "current environment"; + const pkgUpdateMessagePart = hasPyspark + ? "(pyspark will be uninstalled)" + : hasDbConnect + ? `(databricks-connect will be changed from ${dbConnectDetails.version} to ${DATABRICKS_CONNECT_VERSION})` + : ""; + const message = `${mainMessagePart} ${envMessagePart}. ${pkgUpdateMessagePart}`; + const choices = ["Install", "Change environment", "Change version"]; + + const choice = await window.showInformationMessage(message, ...choices); + switch (choice) { + case "Install": + return this.install(); + case "Change version": + return this.installWithVersionPrompt(); + case "Change environment": + await commands.executeCommand( + "databricks.environment.selectPythonInterpreter" + ); + return; + } + } +} diff --git a/packages/databricks-vscode/src/language/EnvironmentDependenciesVerifier.ts b/packages/databricks-vscode/src/language/EnvironmentDependenciesVerifier.ts new file mode 100644 index 000000000..85cb4b1c9 --- /dev/null +++ b/packages/databricks-vscode/src/language/EnvironmentDependenciesVerifier.ts @@ -0,0 +1,294 @@ +import {logging} from "@databricks/databricks-sdk"; +import {Cluster} from "../sdk-extensions"; +import {commands} from "vscode"; +import {ConnectionManager} from "../configuration/ConnectionManager"; +import {MultiStepAccessVerifier} from "../feature-manager/MultiStepAccessVerfier"; +import {MsPythonExtensionWrapper} from "./MsPythonExtensionWrapper"; +import {Loggers} from "../logger"; +import {Context, context} from "@databricks/databricks-sdk/dist/context"; +import {EnvironmentDependenciesInstaller} from "./EnvironmentDependenciesInstaller"; +import {FeatureStepState} from "../feature-manager/FeatureManager"; +import {ResolvedEnvironment} from "./MsPythonExtensionApi"; + +export class EnvironmentDependenciesVerifier extends MultiStepAccessVerifier { + constructor( + private readonly connectionManager: ConnectionManager, + private readonly pythonExtension: MsPythonExtensionWrapper, + private readonly installer: EnvironmentDependenciesInstaller + ) { + super([ + "checkCluster", + "checkWorkspaceHasUc", + "checkPythonEnvironment", + "checkEnvironmentDependencies", + ]); + this.disposables.push( + this.connectionManager.onDidChangeCluster(async (cluster) => { + this.checkCluster(cluster); + if (cluster) { + await this.checkPythonEnvironment(); + this.checkEnvironmentDependencies(); + } + }, this), + this.connectionManager.onDidChangeState((e) => { + if (e !== "CONNECTED") { + return; + } + this.checkWorkspaceHasUc(); + }, this), + this.pythonExtension.onDidChangePythonExecutable(async () => { + await this.checkPythonEnvironment(); + const depsCheck = await this.checkEnvironmentDependencies(); + if (!depsCheck.available && depsCheck.action) { + await depsCheck.action(true); + } + }, this), + this.installer.onDidTryInstallation(() => + this.checkEnvironmentDependencies() + ) + ); + } + + promptForAttachingCluster(msg: string) { + return async () => { + await commands.executeCommand( + "databricks.connection.attachClusterQuickPick", + msg + ); + }; + } + + async selectPythonInterpreter() { + await commands.executeCommand( + "databricks.environment.selectPythonInterpreter" + ); + } + + async reinstallDbConnect() { + await commands.executeCommand( + "databricks.environment.reinstallDBConnect" + ); + } + + async checkCluster(cluster?: Cluster) { + if (cluster === undefined) { + return this.rejectStep( + "checkCluster", + "Attach a cluster", + `Databricks Connect requires cluster DBR >= 13.0.0`, + this.promptForAttachingCluster( + "Please attach a cluster to use Databricks Connect." + ) + ); + } + + const dbrVersionParts = cluster?.dbrVersion; + if ( + !dbrVersionParts || + (dbrVersionParts[0] !== "x" && dbrVersionParts[0] < 13) + ) { + return this.rejectStep( + "checkCluster", + "Attach a cluster with DBR >= 13.0.0", + `Databricks Connect requires a cluster with DBR >= 13.0.0`, + this.promptForAttachingCluster( + `Databricks Connect requires cluster DBR >= 13.0.0. Currently it is ${dbrVersionParts.join( + "." + )}. Please attach a new cluster.` + ) + ); + } + if (!cluster.isUc()) { + return this.rejectStep( + "checkCluster", + `Attach a cluster with Unity Catalog`, + "Databricks Connect requires a cluster with UC enabled", + this.promptForAttachingCluster( + `Databricks Connect requires a Unity Catalog enabled cluster with Access Mode "Single User" or "Shared". Currently it is ${ + cluster.accessMode ?? "custom" + }. Please attach a new cluster.` + ) + ); + } + return this.acceptStep("checkCluster"); + } + + @logging.withLogContext(Loggers.Extension) + async checkWorkspaceHasUc(@context ctx?: Context) { + try { + const catalogList = + this.connectionManager.workspaceClient?.catalogs.list(); + const catalogListIter = catalogList + ? catalogList[Symbol.asyncIterator]() + : undefined; + + if (!(await catalogListIter?.next())) { + return this.rejectStep( + "checkWorkspaceHasUc", + "The workspace should have Unity Catalog enabled", + "No catalogues with read permission were found" + ); + } + } catch (e: unknown) { + if (e instanceof Error) { + ctx?.logger?.error("Error while searching for catalogues", e); + return this.rejectStep( + "checkWorkspaceHasUc", + "Failed to check workspace permissions", + e.message + ); + } + } + return this.acceptStep("checkWorkspaceHasUc"); + } + + private matchEnvironmentVersion( + env: ResolvedEnvironment | undefined, + major: number, + minor: number + ): boolean { + if (!env || !env.version || !env.environment) { + return false; + } + return env.version.major === major && env.version.minor === minor; + } + + private printEnvironment(env?: ResolvedEnvironment): string { + return env?.version && env.environment + ? `Current version is ${env.version.major}.${env.version.minor}.${env.version.micro}.` + : "No active environments found."; + } + + async checkPythonEnvironment(): Promise { + const env = await this.pythonExtension.pythonEnvironment; + const envVersionTooLow = + env?.version && (env.version.major !== 3 || env.version.minor < 10); + const noEnvironment = !env?.environment; + if (noEnvironment || envVersionTooLow) { + return this.rejectStep( + "checkPythonEnvironment", + "Activate an environment with Python >= 3.10", + `Databricks Connect requires python >= 3.10. ${this.printEnvironment( + env + )}`, + this.selectPythonInterpreter.bind(this) + ); + } + const executable = await this.pythonExtension.getPythonExecutable(); + if (!executable) { + return this.rejectStep( + "checkPythonEnvironment", + "Activate an environment with Python >= 3.10", + "No python executable found", + this.selectPythonInterpreter.bind(this) + ); + } + const dbrVersionParts = + this.connectionManager.cluster?.dbrVersion || []; + let warning; + if ( + (dbrVersionParts[0] === 13 || dbrVersionParts[0] === 14) && + !this.matchEnvironmentVersion(env, 3, 10) + ) { + warning = `Use python 3.10 to match DBR ${ + dbrVersionParts[0] + } requirements. ${this.printEnvironment(env)}`; + } + if ( + dbrVersionParts[0] === 15 && + !this.matchEnvironmentVersion(env, 3, 11) + ) { + warning = `Use python 3.11 to match DBR ${ + dbrVersionParts[0] + } requirements. ${this.printEnvironment(env)}`; + } + return this.acceptStep( + "checkPythonEnvironment", + `Active Environment: ${env.environment.name}`, + env.executable.uri?.fsPath, + warning + ); + } + + checkDatabricksConnectVersion(version: string) { + const dbconnectcVersionParts = version.split("."); + const dbconnectMajor = parseInt(dbconnectcVersionParts[0], 10); + const dbconnectMinor = parseInt(dbconnectcVersionParts[1], 10); + if (dbconnectMajor < 13) { + return this.rejectStep( + "checkEnvironmentDependencies", + "Update databricks-connect", + `Databricks Connect ${version} is outdated, please update to 13.0.0 or higher.`, + this.reinstallDbConnect.bind(this) + ); + } + const dbrVersionParts = this.connectionManager.cluster?.dbrVersion; + if (dbrVersionParts && dbrVersionParts[0] !== "x") { + const dbrMajor = dbrVersionParts[0]; + const dbrMinor = dbrVersionParts[1]; + const dbconnectIsHigher = + dbconnectMajor > dbrMajor || + (dbconnectMajor === dbrMajor && + dbrMinor !== "x" && + dbconnectMinor > dbrMinor); + if (dbconnectIsHigher) { + return this.rejectStep( + "checkEnvironmentDependencies", + "Reinstall databricks-connect", + `Databricks Connect version (${version}) should be equal or lower than the cluster DBR version (${dbrMajor}.${dbrMinor}).`, + this.reinstallDbConnect.bind(this) + ); + } + } + return this.acceptStep( + "checkEnvironmentDependencies", + `Databricks Connect: ${version}` + ); + } + + async checkEnvironmentDependencies(): Promise { + const envAvailable = this.state.steps.get("checkPythonEnvironment") + ?.available; + if (!envAvailable) { + return this.rejectStep( + "checkEnvironmentDependencies", + "Can't install databricks-connect without an active python environment" + ); + } + try { + const dbconnect = + await this.pythonExtension.getPackageDetailsFromEnvironment( + "databricks-connect" + ); + if (dbconnect) { + return this.checkDatabricksConnectVersion(dbconnect.version); + } else { + return this.rejectStep( + "checkEnvironmentDependencies", + "Install databricks-connect", + "databricks-connect package is not installed in the current environment", + async (advertisement = false) => + this.installer.show(advertisement) + ); + } + } catch (e: unknown) { + const message = e instanceof Error ? e.message : (e as string); + return this.rejectStep( + "checkEnvironmentDependencies", + "Failed to check dependencies", + message, + async () => void (await this.checkEnvironmentDependencies()) + ); + } + } + + override async check() { + await this.connectionManager.waitForConnect(); + await Promise.all([ + this.checkCluster(this.connectionManager.cluster), + this.checkWorkspaceHasUc(), + this.checkPythonEnvironment(), + ]); + await this.checkEnvironmentDependencies(); + } +} diff --git a/packages/databricks-vscode/src/language/MsPythonExtensionWrapper.ts b/packages/databricks-vscode/src/language/MsPythonExtensionWrapper.ts index d85f1b172..7346d6165 100644 --- a/packages/databricks-vscode/src/language/MsPythonExtensionWrapper.ts +++ b/packages/databricks-vscode/src/language/MsPythonExtensionWrapper.ts @@ -4,20 +4,16 @@ import { Event, window, Disposable, - workspace, - RelativePattern, Terminal, commands, + OutputChannel, } from "vscode"; import {StateStorage} from "../vscode-objs/StateStorage"; import {IExtensionApi as MsPythonExtensionApi} from "./MsPythonExtensionApi"; -import * as os from "node:os"; -import * as path from "node:path"; -import {mkdtemp, readFile} from "fs/promises"; import {Mutex} from "../locking"; -import * as cp from "node:child_process"; -import {promisify} from "node:util"; -export const execFile = promisify(cp.execFile); +import * as childProcess from "node:child_process"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; +import {execFile} from "../cli/CliWrapper"; export class MsPythonExtensionWrapper implements Disposable { public readonly api: MsPythonExtensionApi; @@ -26,7 +22,7 @@ export class MsPythonExtensionWrapper implements Disposable { private _terminal?: Terminal; constructor( pythonExtension: Extension, - private readonly workspaceFolder: Uri, + private readonly workspaceFolderManager: WorkspaceFolderManager, private readonly stateStorage: StateStorage ) { this.api = pythonExtension.exports as MsPythonExtensionApi; @@ -58,19 +54,21 @@ export class MsPythonExtensionWrapper implements Disposable { } async getPythonExecutable() { - if (this.api.settings) { - return ( - this.api.settings.getExecutionDetails(this.workspaceFolder) - .execCommand ?? [] - ).join(" "); + const env = await this.pythonEnvironment; + return env?.executable.uri?.fsPath; + } + + async getAvailableEnvironments() { + await this.api.environments.refreshEnvironments(); + const filteredEnvs = []; + for (const env of this.api.environments.known) { + const resolvedEnv = + await this.api.environments.resolveEnvironment(env); + if (resolvedEnv && resolvedEnv.environment) { + filteredEnvs.push(env); + } } - return ( - await this.api.environments.resolveEnvironment( - this.api.environments.getActiveEnvironmentPath( - this.workspaceFolder - ) - ) - )?.executable.uri?.fsPath; + return filteredEnvs; } get onDidChangePythonExecutable(): Event { @@ -88,44 +86,30 @@ export class MsPythonExtensionWrapper implements Disposable { get pythonEnvironment() { return this.api.environments?.resolveEnvironment( - this.api.environments?.getActiveEnvironmentPath() + this.api.environments?.getActiveEnvironmentPath( + this.workspaceFolderManager.activeWorkspaceFolder + ) ); } - private async executeInTerminalE(command: string) { - const dir = await mkdtemp(path.join(os.tmpdir(), "databricks-vscode-")); - const filePath = path.join(dir, "python-terminal-output.txt"); - - const disposables: Disposable[] = []; - const exitCodePromise = new Promise((resolve) => { - const fsWatcher = workspace.createFileSystemWatcher( - new RelativePattern(dir, path.basename(filePath)) - ); - const handleFileChange = async () => { - try { - const fileData = await readFile(filePath, "utf-8"); - resolve(parseInt(fileData)); - } catch (e: unknown) { - resolve(undefined); + async runWithOutput( + command: string, + args: string[], + outputChannel?: OutputChannel + ) { + const cp = childProcess.execFile(command, args); + cp.stdout?.on("data", (data) => outputChannel?.append(data)); + cp.stderr?.on("data", (data) => outputChannel?.append(data)); + return new Promise((resolve, reject) => { + cp.on("exit", (code) => { + if (code === 0) { + resolve(); + } else { + reject(new Error(`Command exited with code ${code}`)); } - }; - disposables.push( - fsWatcher, - fsWatcher.onDidCreate(handleFileChange), - fsWatcher.onDidChange(handleFileChange) - ); + }); + cp.on("error", reject); }); - - try { - await this.terminalMutex.wait(); - this.terminal.show(); - this.terminal.sendText(`${command}; echo $? > ${filePath}`); - const exitCode = await exitCodePromise; - return exitCode; - } finally { - disposables.forEach((i) => i.dispose()); - this.terminalMutex.signal(); - } } async getLatestPackageVersion(name: string) { @@ -194,7 +178,11 @@ export class MsPythonExtensionWrapper implements Disposable { ); } - async installPackageInEnvironment(name: string, version?: string | RegExp) { + async installPackageInEnvironment( + name: string, + version?: string | RegExp, + outputChannel?: OutputChannel + ) { const executable = await this.getPythonExecutable(); if (!executable) { throw Error("No python executable found"); @@ -202,38 +190,47 @@ export class MsPythonExtensionWrapper implements Disposable { if (version === "latest") { version = await this.getLatestPackageVersion(name); } - const execCommand = `'${executable}' -m pip install '${name}${ - version ? `==${version}` : "" - }' --disable-pip-version-check --no-python-version-warning`; - - const exitCode = await this.executeInTerminalE(execCommand); - if (exitCode) { - throw new Error( - `Error while installing ${name} package in the current python environment.` - ); - } + const args = [ + "-m", + "pip", + "install", + `${name}${version ? `==${version}` : ""}`, + "--disable-pip-version-check", + "--no-python-version-warning", + ]; + outputChannel?.appendLine(`Running: ${executable} ${args.join(" ")}`); + await this.runWithOutput(executable, args, outputChannel); } - async uninstallPackageFromEnvironment(name: string) { + async uninstallPackageFromEnvironment( + name: string, + outputChannel?: OutputChannel + ) { const exists = await this.findPackageInEnvironment(name); const executable = await this.getPythonExecutable(); - if (!exists || !executable) { return; } - - const execCommand = `'${executable}' -m pip uninstall '${name}' --disable-pip-version-check --no-python-version-warning -y`; - const exitCode = await this.executeInTerminalE(execCommand); - if (exitCode) { - throw new Error( - `Error while un-installing ${name} package from the current python environment.` - ); - } + const args = [ + "-m", + "pip", + "uninstall", + name, + "--disable-pip-version-check", + "--no-python-version-warning", + "-y", + ]; + outputChannel?.appendLine(`Running: ${executable} ${args.join(" ")}`); + await this.runWithOutput(executable, args, outputChannel); } async selectPythonInterpreter() { await commands.executeCommand("python.setInterpreter"); } + async createPythonEnvironment() { + await commands.executeCommand("python.createEnvironment"); + } + dispose() {} } diff --git a/packages/databricks-vscode/src/language/notebooks/DatabricksNbCellLimits.ts b/packages/databricks-vscode/src/language/notebooks/DatabricksNbCellLimits.ts index d56624674..ca200a534 100644 --- a/packages/databricks-vscode/src/language/notebooks/DatabricksNbCellLimits.ts +++ b/packages/databricks-vscode/src/language/notebooks/DatabricksNbCellLimits.ts @@ -1,13 +1,16 @@ import {workspaceConfigs} from "../../vscode-objs/WorkspaceConfigs"; import {FileUtils} from "../../utils"; -import {Uri} from "vscode"; import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; export async function setDbnbCellLimits( - workspacePath: Uri, + workspaceFolderManager: WorkspaceFolderManager, connectionManager: ConnectionManager ) { - await FileUtils.waitForDatabricksProject(workspacePath, connectionManager); + await FileUtils.waitForDatabricksProject( + workspaceFolderManager.activeWorkspaceFolder.uri, + connectionManager + ); if (workspaceConfigs.jupyterCellMarkerRegex === undefined) { workspaceConfigs.jupyterCellMarkerRegex = "^(# Databricks notebook source|# COMMAND ----------)"; diff --git a/packages/databricks-vscode/src/language/notebooks/NotebookAccessVerifier.ts b/packages/databricks-vscode/src/language/notebooks/NotebookAccessVerifier.ts deleted file mode 100644 index 2cb4e60c9..000000000 --- a/packages/databricks-vscode/src/language/notebooks/NotebookAccessVerifier.ts +++ /dev/null @@ -1,126 +0,0 @@ -import {window} from "vscode"; -import {FeatureManager} from "../../feature-manager/FeatureManager"; -import {MultiStepAccessVerifier} from "../../feature-manager/MultiStepAccessVerfier"; -import {MsPythonExtensionWrapper} from "../MsPythonExtensionWrapper"; -import {StateStorage} from "../../vscode-objs/StateStorage"; - -export class NotebookAccessVerifier extends MultiStepAccessVerifier { - constructor( - private readonly featureManager: FeatureManager, - private readonly pythonExtension: MsPythonExtensionWrapper, - private readonly stateStorage: StateStorage - ) { - super(["isPythonSdkInstalled", "isDbConnectEnabled"]); - - this.disposables.push( - this.featureManager.onDidChangeState( - "debugging.dbconnect", - this.isDbConnectEnabled, - this - ), - this.pythonExtension.onDidChangePythonExecutable( - this.isPythonSdkInstalled, - this - ) - ); - } - - async showSdkInstallPrompt() { - const mainMessagePart = - "Databricks SDK for python enables you to run databricks notebooks locally. Would you like to install it in the"; - - const env = await this.pythonExtension.pythonEnvironment; - const envMessagePart = env?.environment?.name - ? `environment ${env.environment.name}` - : `current environment`; - - const sdkDetails = - await this.pythonExtension.getPackageDetailsFromEnvironment( - "databricks-sdk" - ); - const sdkUpdateMessagePart = sdkDetails - ? `(databricks-sdk will be updated to the latest version: ${ - sdkDetails.version - } -> ${await this.pythonExtension.getLatestPackageVersion( - "databricks-sdk" - )})` - : ""; - - const message = `${mainMessagePart} ${envMessagePart}? ${sdkUpdateMessagePart}`; - const result = await window.showInformationMessage( - message, - "Install", - "Change environment", - "Never for this environment" - ); - switch (result) { - case "Install": - await this.pythonExtension.installPackageInEnvironment( - "databricks-sdk", - "latest" - ); - return true; - - case "Change environment": - await this.pythonExtension.selectPythonInterpreter(); - break; - - case "Never for this environment": - if (env?.path) { - this.stateStorage.skipDatabricksSdkInstallForEnv(env?.path); - } - } - return false; - } - - async isPythonSdkInstalled() { - try { - await this.waitForStep("isDbConnectEnabled"); - const databricksSdkExists = - await this.pythonExtension.findPackageInEnvironment( - "databricks-sdk", - "latest" - ); - if (databricksSdkExists) { - return this.acceptStep("isPythonSdkInstalled"); - } - return this.rejectStep( - "isPythonSdkInstalled", - "Python SDK is not installed", - async () => { - try { - if (await this.showSdkInstallPrompt()) { - this.acceptStep("isPythonSdkInstalled"); - } - } catch (e) { - if (e instanceof Error) { - window.showErrorMessage(e.message); - } - } - } - ); - } catch (e) { - if (e instanceof Error) { - return this.rejectStep("isPythonSdkInstalled", e.message); - } - } - } - - async isDbConnectEnabled() { - const dbconnectFeature = await this.featureManager.isEnabled( - "debugging.dbconnect" - ); - if (dbconnectFeature.avaliable) { - return this.acceptStep("isDbConnectEnabled"); - } - return this.rejectStep( - "isDbConnectEnabled", - "DbConnect is not enabled" - ); - } - - async check() { - this.isPythonSdkInstalled(); - this.isDbConnectEnabled(); - } -} diff --git a/packages/databricks-vscode/src/language/notebooks/NotebookInitScriptManager.ts b/packages/databricks-vscode/src/language/notebooks/NotebookInitScriptManager.ts index e9d10da67..62c494c55 100644 --- a/packages/databricks-vscode/src/language/notebooks/NotebookInitScriptManager.ts +++ b/packages/databricks-vscode/src/language/notebooks/NotebookInitScriptManager.ts @@ -1,6 +1,5 @@ import { Disposable, - Uri, ExtensionContext, window, OutputChannel, @@ -18,14 +17,12 @@ import {Loggers} from "../../logger"; import {Context, context} from "@databricks/databricks-sdk/dist/context"; import {Mutex} from "../../locking"; import {MsPythonExtensionWrapper} from "../MsPythonExtensionWrapper"; -import {execFile as ef} from "child_process"; -import {promisify} from "util"; -import {EnvVarGenerators, FileUtils} from "../../utils"; +import {FileUtils} from "../../utils"; import {workspaceConfigs} from "../../vscode-objs/WorkspaceConfigs"; -import {SystemVariables} from "../../vscode-objs/SystemVariables"; import {LocalUri} from "../../sync/SyncDestination"; - -const execFile = promisify(ef); +import {DatabricksEnvFileManager} from "../../file-managers/DatabricksEnvFileManager"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; +import {execFile} from "../../cli/CliWrapper"; async function isDbnbTextEditor(editor?: TextEditor) { try { @@ -51,19 +48,18 @@ export class NotebookInitScriptManager implements Disposable { private currentEnvPath?: string | null = null; constructor( - private readonly workspacePath: Uri, + private readonly workspaceFolderManager: WorkspaceFolderManager, private readonly extensionContext: ExtensionContext, private readonly connectionManager: ConnectionManager, private readonly featureManager: FeatureManager, - private readonly pythonExtension: MsPythonExtensionWrapper + private readonly pythonExtension: MsPythonExtensionWrapper, + private readonly databricksEnvFileManager: DatabricksEnvFileManager ) { - this.featureManager.isEnabled("notebooks.dbconnect").then((state) => { - if (!state.isDisabledByFf) { - this.outputWindow = window.createOutputChannel( - "Databricks Notebooks" - ); - this.disposables.push(this.outputWindow); - } + this.featureManager.isEnabled("environment.dependencies").then(() => { + this.outputWindow = window.createOutputChannel( + "Databricks Notebooks" + ); + this.disposables.push(this.outputWindow); }); this.disposables.push( this.connectionManager.onDidChangeState(async (e) => { @@ -79,11 +75,14 @@ export class NotebookInitScriptManager implements Disposable { this.currentEnvPath = null; this.verifyInitScript(); }), - this.featureManager.onDidChangeState("notebooks.dbconnect", () => { - this.initScriptSuccessfullyVerified = false; - this.currentEnvPath = null; - this.verifyInitScript(); - }), + this.featureManager.onDidChangeState( + "environment.dependencies", + () => { + this.initScriptSuccessfullyVerified = false; + this.currentEnvPath = null; + this.verifyInitScript(); + } + ), workspace.onDidOpenNotebookDocument(async () => { if (await this.isKnownEnvironment()) { return; @@ -183,8 +182,8 @@ export class NotebookInitScriptManager implements Disposable { async updateInitScript() { if ( - !(await this.featureManager.isEnabled("notebooks.dbconnect")) - .avaliable + !(await this.featureManager.isEnabled("environment.dependencies")) + .available ) { return; } @@ -193,16 +192,6 @@ export class NotebookInitScriptManager implements Disposable { await this.copyInitScript(); } - private async getUserEnvVars() { - if (workspaceConfigs.userEnvFile === undefined) { - return; - } - const userEnvFile = new SystemVariables(this.workspacePath).resolve( - workspaceConfigs.userEnvFile - ); - return EnvVarGenerators.getUserEnvVars(Uri.file(userEnvFile)); - } - private async showVerificationFailMessage() { if (this.verificationErrorMessageMutex.locked) { return; @@ -237,23 +226,15 @@ export class NotebookInitScriptManager implements Disposable { let someScriptFailed = false; for (const fileBaseName of await this.sourceFiles) { const file = path.join(this.startupDir, fileBaseName); - const env = { - ...(EnvVarGenerators.getCommonDatabricksEnvVars( - this.connectionManager - ) ?? {}), - ...((await EnvVarGenerators.getDbConnectEnvVars( - this.connectionManager, - this.workspacePath - )) ?? {}), - ...(EnvVarGenerators.getIdeEnvVars() ?? {}), - ...((await this.getUserEnvVars()) ?? {}), - }; + const env = await this.databricksEnvFileManager.getEnv(); + const {stderr} = await execFile( executable, ["-m", "IPython", file], { env, - cwd: this.workspacePath.fsPath, + cwd: this.workspaceFolderManager.activeWorkspaceFolder.uri + .fsPath, } ); const correctlyFormatttedErrors = stderr @@ -295,6 +276,10 @@ export class NotebookInitScriptManager implements Disposable { fromCommand = false, @context ctx?: Context ) { + if (this.connectionManager.state !== "CONNECTED") { + return; + } + // If we are not in a jupyter notebook or a databricks notebook, // then we don't need to verify the init script if ( @@ -307,13 +292,13 @@ export class NotebookInitScriptManager implements Disposable { } await FileUtils.waitForDatabricksProject( - this.workspacePath, + this.workspaceFolderManager.activeWorkspaceFolder.uri, this.connectionManager ); if ( - !(await this.featureManager.isEnabled("notebooks.dbconnect")) - .avaliable + !(await this.featureManager.isEnabled("environment.dependencies")) + .available ) { return; } diff --git a/packages/databricks-vscode/src/locking/Barrier.ts b/packages/databricks-vscode/src/locking/Barrier.ts new file mode 100644 index 000000000..4c741a4b2 --- /dev/null +++ b/packages/databricks-vscode/src/locking/Barrier.ts @@ -0,0 +1,9 @@ +export class Barrier { + public promise: Promise; + public resolve: () => void = () => {}; + constructor() { + this.promise = new Promise((resolve) => { + this.resolve = resolve; + }); + } +} diff --git a/packages/databricks-vscode/src/locking/CachedValue.test.ts b/packages/databricks-vscode/src/locking/CachedValue.test.ts new file mode 100644 index 000000000..a96c4c4c5 --- /dev/null +++ b/packages/databricks-vscode/src/locking/CachedValue.test.ts @@ -0,0 +1,42 @@ +import {expect} from "chai"; +import {CachedValue} from "./CachedValue"; + +describe(__filename, () => { + class GetterSpy { + value: string = "test"; + callCount: number = 0; + get(): Promise { + this.callCount += 1; + return Promise.resolve(this.value); + } + } + + let getterSpy: GetterSpy; + let st: CachedValue; + + beforeEach(() => { + getterSpy = new GetterSpy(); + st = new CachedValue(getterSpy.get.bind(getterSpy)); + }); + + it("should use getter to lazily fetch value initially", async () => { + expect(await st.value).to.equal("test"); + expect(getterSpy.callCount).to.equal(1); + }); + + it("should use cached value if not dirty", async () => { + expect(await st.value).to.equal("test"); + expect(await st.value).to.equal("test"); + expect(getterSpy.callCount).to.equal(1); + }); + + it("should use getter if dirty", async () => { + expect(await st.value).to.equal("test"); + getterSpy.value = "test2"; + expect(getterSpy.callCount).to.equal(1); + + st.invalidate(); + expect(await st.value).to.equal("test2"); + expect(getterSpy.callCount).to.equal(2); + }); +}); diff --git a/packages/databricks-vscode/src/locking/CachedValue.ts b/packages/databricks-vscode/src/locking/CachedValue.ts new file mode 100644 index 000000000..ebbe30f33 --- /dev/null +++ b/packages/databricks-vscode/src/locking/CachedValue.ts @@ -0,0 +1,121 @@ +import {Disposable} from "vscode"; +import {Mutex} from "."; +import lodash from "lodash"; +import {EventEmitterWithErrorHandler} from "../utils/EventWithErrorHandler"; + +const customizer: lodash.IsEqualCustomizer = (value, other) => { + if (value instanceof URL && other instanceof URL) { + return value.toString() === other.toString(); + } + return undefined; +}; +export class CachedValue implements Disposable { + private disposables: Disposable[] = []; + + private _value: T | null = null; + private _dirty = true; + private readonly mutex = new Mutex(); + private readonly onDidChangeEmitter = new EventEmitterWithErrorHandler<{ + oldValue: T | null; + newValue: T; + }>({log: true, throw: false}); + public readonly onDidChange = this.onDidChangeEmitter.event; + + constructor(private readonly getter: () => Promise) { + this.disposables.push( + this.onDidChange(async ({oldValue, newValue}) => { + function isObject( + value: unknown + ): value is object | undefined | null { + return ( + typeof value === "object" || + typeof value === "undefined" || + value === null + ); + } + if (!isObject(oldValue) || !isObject(newValue)) { + return; + } + + if (oldValue === null || oldValue === undefined) { + oldValue = {} as T; + } + if (newValue === null || newValue === undefined) { + newValue = {} as T; + } + + for (const key of Object.keys({ + ...oldValue, + ...newValue, + } as any) as (keyof T)[]) { + if ( + oldValue === null || + !lodash.isEqualWith( + oldValue?.[key], + newValue?.[key], + customizer + ) + ) { + this.onDidChangeKeyEmitters.get(key)?.fire(); + } + } + }) + ); + } + + get value(): Promise { + return this.mutex.synchronise(async () => { + try { + if (this._dirty || this._value === null) { + const newValue = await this.getter(); + this.set(newValue); + return this._value as T; + } + } finally { + this._dirty = false; + } + return this._value; + }); + } + + set(value: T) { + if (!lodash.isEqualWith(value, this._value, customizer)) { + this.onDidChangeEmitter.fire({ + oldValue: this._value, + newValue: value, + }); + this._value = value; + } + } + private readonly onDidChangeKeyEmitters = new Map< + keyof T, + EventEmitterWithErrorHandler + >(); + + onDidChangeKey(key: T extends object ? keyof T : never) { + if (!this.onDidChangeKeyEmitters.has(key)) { + this.onDidChangeKeyEmitters.set( + key, + new EventEmitterWithErrorHandler({log: true, throw: false}) + ); + } + return this.onDidChangeKeyEmitters.get(key)!.event; + } + + invalidate() { + this._dirty = true; + } + + async refresh() { + this.invalidate(); + try { + await this.value; + } finally { + this._dirty = false; + } + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/locking/Mutex.ts b/packages/databricks-vscode/src/locking/Mutex.ts index 7a30e0b18..866a756d2 100644 --- a/packages/databricks-vscode/src/locking/Mutex.ts +++ b/packages/databricks-vscode/src/locking/Mutex.ts @@ -24,4 +24,29 @@ export class Mutex { get locked() { return this._locked; } + + async synchronise(fn: () => Promise) { + await this.wait(); + try { + return await fn(); + } finally { + this.signal(); + } + } + + static synchronise(mutexKey: string) { + return function ( + target: any, + key: string, + descriptor: PropertyDescriptor + ) { + const original = descriptor.value; + descriptor.value = async function (...args: any[]) { + const mutex = (this as any)[mutexKey] as Mutex; + return await mutex.synchronise(async () => { + return await original.apply(this, args); + }); + }; + }; + } } diff --git a/packages/databricks-vscode/src/locking/index.ts b/packages/databricks-vscode/src/locking/index.ts index ac662fb58..834516389 100644 --- a/packages/databricks-vscode/src/locking/index.ts +++ b/packages/databricks-vscode/src/locking/index.ts @@ -1,2 +1,9 @@ +import {Mutex} from "./Mutex"; + export * from "./Mutex"; export * from "./RWLock"; + +export class WithMutex { + public readonly mutex = new Mutex(); + constructor(public value: T) {} +} diff --git a/packages/databricks-vscode/src/logger/LoggerManager.ts b/packages/databricks-vscode/src/logger/LoggerManager.ts index 59efa27a2..7d29f5933 100644 --- a/packages/databricks-vscode/src/logger/LoggerManager.ts +++ b/packages/databricks-vscode/src/logger/LoggerManager.ts @@ -1,14 +1,21 @@ import {logging} from "@databricks/databricks-sdk"; -import {env, ExtensionContext, window} from "vscode"; +import {env, ExtensionContext, window, LogOutputChannel} from "vscode"; import {loggers, format, transports} from "winston"; -import {getOutputConsoleTransport} from "./outputConsoleTransport"; + +import {getJsonFormat} from "./truncatedJsonFormat"; import {unlink, access, mkdir} from "fs/promises"; import path from "path"; +import { + LOG_OUTPUT_CHANNEL_LEVELS, + LogOutputChannelStream, +} from "./OutputConsoleStream"; // eslint-disable-next-line @typescript-eslint/naming-convention const {NamedLogger, ExposedLoggers} = logging; export class LoggerManager { + private outputChannels: Map = new Map(); + constructor(readonly context: ExtensionContext) {} async getLogFile(prefix: string) { @@ -25,41 +32,58 @@ export class LoggerManager { return logFile; } - private getFileTransport( - filename: string, - extraOptions?: Omit< - transports.FileTransportOptions, - "filename" | "format" - > + private getLogOutputChannel( + name: "Databricks Logs" | "Databricks Bundle Logs" ) { - return new transports.File({ - format: format.combine(format.timestamp(), format.json()), - filename: filename, - ...extraOptions, - }); + if (!this.outputChannels.has(name)) { + const outputChannel = window.createOutputChannel(name, {log: true}); + outputChannel.clear(); + this.outputChannels.set(name, outputChannel); + } + return this.outputChannels.get(name)!; } async initLoggers() { - const outputChannel = window.createOutputChannel("Databricks Logs"); - outputChannel.clear(); - - const sdkAndExtensionLogfile = await this.getLogFile( - "sdk-and-extension" - ); + /** + * We need to create a new transport for each log levle. + * This because the log output channel requires different functions to print different levels of log. + * Since the log output channel is part of the stream, which does not get the log level as input ever, + * we need to specify the log level of the stream at object initialisation time. + */ + const commonLogTransports = [ + ...LOG_OUTPUT_CHANNEL_LEVELS.map( + (level) => + new transports.Stream({ + stream: new LogOutputChannelStream( + this.getLogOutputChannel("Databricks Logs"), + level, + { + defaultEncoding: "utf-8", + } + ), + format: format.combine( + // Since we want each stream to be targeted to a specific log level, + // we need to filter the logs by level. Returning false from the first format + // will prevent the log from being printed. + format((info) => info.level === level && info)(), + getJsonFormat() + ), + level, + }) + ), + new transports.File({ + format: format.combine(format.timestamp(), format.json()), + filename: await this.getLogFile("sdk-and-extension"), + level: "debug", + }), + ]; NamedLogger.getOrCreate( ExposedLoggers.SDK, { factory: (name) => { return loggers.add(name, { - transports: [ - getOutputConsoleTransport(outputChannel, { - level: "debug", - }), - this.getFileTransport(sdkAndExtensionLogfile, { - level: "debug", - }), - ], + transports: commonLogTransports, }); }, }, @@ -69,16 +93,56 @@ export class LoggerManager { // This logger collects all the logs in the extension. NamedLogger.getOrCreate( Loggers.Extension, + { + factory: (name) => { + return loggers.add(name, { + transports: commonLogTransports, + }); + }, + }, + true + ); + + /** + * We need to create a new transport for each log levle. + * This because the log output channel requires different functions to print different levels of log. + * Since the log output channel is part of the stream, which does not get the log level as input ever, + * we need to specify the log level of the stream at object initialisation time. + */ + const bundleTransports = LOG_OUTPUT_CHANNEL_LEVELS.filter( + (i) => i !== "debug" && i !== "trace" //Only log info, error, warn + ).map( + (level) => + new transports.Stream({ + stream: new LogOutputChannelStream( + this.getLogOutputChannel("Databricks Bundle Logs"), + level, + { + defaultEncoding: "utf-8", + } + ), + format: format.combine( + // Since we want each stream to be targeted to a specific log level, + // we need to filter the logs by level. Returning false from the first format + // will prevent the log from being printed. + format((info) => info.level === level && info)(), + format.timestamp(), + format.printf((info) => { + return `${info.bundleOpName}: ${info.message}`; + }) + ), + level, + }) + ); + + NamedLogger.getOrCreate( + Loggers.Bundle, { factory: (name) => { return loggers.add(name, { transports: [ - getOutputConsoleTransport(outputChannel, { - level: "error", - }), - this.getFileTransport(sdkAndExtensionLogfile, { - level: "debug", - }), + ...commonLogTransports, + ...bundleTransports, ], }); }, @@ -90,10 +154,15 @@ export class LoggerManager { openLogFolder() { env.openExternal(this.context.logUri); } + + showOutputChannel(name: "Databricks Logs" | "Databricks Bundle Logs") { + this.getLogOutputChannel(name).show(); + } } /* eslint-disable @typescript-eslint/naming-convention */ export enum Loggers { Extension = "Extension", + Bundle = "Bundle", } /* eslint-enable @typescript-eslint/naming-convention */ diff --git a/packages/databricks-vscode/src/logger/OutputConsoleStream.ts b/packages/databricks-vscode/src/logger/OutputConsoleStream.ts index ccb304b62..aefa5f674 100644 --- a/packages/databricks-vscode/src/logger/OutputConsoleStream.ts +++ b/packages/databricks-vscode/src/logger/OutputConsoleStream.ts @@ -1,11 +1,20 @@ import internal, {Writable} from "stream"; import {StringDecoder} from "string_decoder"; -import {OutputChannel} from "vscode"; +import {LogOutputChannel} from "vscode"; -export class OutputConsoleStream extends Writable { +export const LOG_OUTPUT_CHANNEL_LEVELS = [ + "info", + "error", + "warn", + "debug", + "trace", +] as const; + +export class LogOutputChannelStream extends Writable { private readonly _decoder = new StringDecoder(); constructor( - private readonly _outputChannel: OutputChannel, + private readonly _outputChannel: LogOutputChannel, + private readonly level: (typeof LOG_OUTPUT_CHANNEL_LEVELS)[number], opts?: internal.WritableOptions ) { super(opts); @@ -16,10 +25,14 @@ export class OutputConsoleStream extends Writable { encoding: BufferEncoding, callback: (error?: Error | null | undefined) => void ): void { - const decoded = Buffer.isBuffer(chunk) + let decoded = Buffer.isBuffer(chunk) ? this._decoder.write(chunk) : chunk; - this._outputChannel.append(decoded); + + if (typeof decoded === "string") { + decoded = decoded.trimEnd(); + } + this._outputChannel[this.level](decoded); callback(); } diff --git a/packages/databricks-vscode/src/logger/outputConsoleTransport.ts b/packages/databricks-vscode/src/logger/outputConsoleTransport.ts deleted file mode 100644 index cdac9f5f5..000000000 --- a/packages/databricks-vscode/src/logger/outputConsoleTransport.ts +++ /dev/null @@ -1,101 +0,0 @@ -import {OutputChannel} from "vscode"; -import {transports, format} from "winston"; -import {OutputConsoleStream} from "./OutputConsoleStream"; -import {LEVEL, MESSAGE, SPLAT} from "triple-beam"; -import {inspect} from "util"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; - -function processPrimitiveOrString(obj: any) { - let valueStr: string; - if (Object(obj) !== obj) { - valueStr = typeof obj === "string" ? obj : String(obj).toString(); - } else { - valueStr = JSON.stringify(obj); - } - - return valueStr.length > workspaceConfigs.maxFieldLength - ? `${valueStr.slice(0, workspaceConfigs.maxFieldLength)} ...(${ - valueStr.length - workspaceConfigs.maxFieldLength - } bytes more)` - : valueStr; -} - -function processArray(obj: Array, depth: number): Array { - const finalArr = []; - for (const child of obj) { - finalArr.push(recursiveTruncate(child, depth - 1)); - if (finalArr.length === workspaceConfigs.maxArrayLength) { - break; - } - } - if (obj.length > workspaceConfigs.maxArrayLength) { - finalArr.push( - `...${obj.length - workspaceConfigs.maxArrayLength} more items` - ); - } - return finalArr; -} - -function recursiveTruncate(obj: any, depth: number) { - //If object is of primitive type - if (Object(obj) !== obj || depth === 0) { - return processPrimitiveOrString(obj); - } - - if (Array.isArray(obj)) { - return processArray(obj, depth); - } - - obj = Object.assign({}, obj); - - for (const key in obj) { - obj[key] = recursiveTruncate(obj[key], depth - 1); - } - return obj; -} - -export function getOutputConsoleTransport( - outputChannel: OutputChannel, - extraOptions?: Omit -) { - return new transports.Stream({ - format: format((info: any) => { - const stripped = Object.assign({}, info) as any; - delete stripped[LEVEL]; - delete stripped[MESSAGE]; - delete stripped[SPLAT]; - delete stripped["level"]; - delete stripped["message"]; - - info[MESSAGE] = - info.level === "error" - ? inspect( - { - ...stripped, - level: info.level, - message: info.message, - }, - false, - 1000 - ) - : inspect( - { - ...recursiveTruncate( - stripped, - workspaceConfigs.truncationDepth - ), - timestamp: new Date().toLocaleString(), - level: info.level, - message: info.message, - }, - false, - workspaceConfigs.truncationDepth - ); - return info; - })(), - stream: new OutputConsoleStream(outputChannel, { - defaultEncoding: "utf-8", - }), - ...extraOptions, - }); -} diff --git a/packages/databricks-vscode/src/logger/truncatedJsonFormat.ts b/packages/databricks-vscode/src/logger/truncatedJsonFormat.ts new file mode 100644 index 000000000..c27672192 --- /dev/null +++ b/packages/databricks-vscode/src/logger/truncatedJsonFormat.ts @@ -0,0 +1,89 @@ +import {format} from "winston"; +import {LEVEL, MESSAGE, SPLAT} from "triple-beam"; +import {inspect} from "util"; +import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; + +function processPrimitiveOrString(obj: any) { + let valueStr: string; + if (Object(obj) !== obj) { + valueStr = typeof obj === "string" ? obj : String(obj).toString(); + } else { + valueStr = JSON.stringify(obj); + } + + return valueStr.length > workspaceConfigs.maxFieldLength + ? `${valueStr.slice(0, workspaceConfigs.maxFieldLength)} ...(${ + valueStr.length - workspaceConfigs.maxFieldLength + } bytes more)` + : valueStr; +} + +function processArray(obj: Array, depth: number): Array { + const finalArr = []; + for (const child of obj) { + finalArr.push(recursiveTruncate(child, depth - 1)); + if (finalArr.length === workspaceConfigs.maxArrayLength) { + break; + } + } + if (obj.length > workspaceConfigs.maxArrayLength) { + finalArr.push( + `...${obj.length - workspaceConfigs.maxArrayLength} more items` + ); + } + return finalArr; +} + +function recursiveTruncate(obj: any, depth: number) { + //If object is of primitive type + if (Object(obj) !== obj || depth === 0) { + return processPrimitiveOrString(obj); + } + + if (Array.isArray(obj)) { + return processArray(obj, depth); + } + + obj = Object.assign({}, obj); + + for (const key in obj) { + obj[key] = recursiveTruncate(obj[key], depth - 1); + } + return obj; +} +export function getJsonFormat() { + return format((info: any) => { + const stripped = Object.assign({}, info) as any; + delete stripped[LEVEL]; + delete stripped[MESSAGE]; + delete stripped[SPLAT]; + delete stripped["level"]; + delete stripped["message"]; + + info[MESSAGE] = + info.level === "error" + ? inspect( + { + ...stripped, + level: info.level, + message: info.message, + }, + false, + 1000 + ) + : inspect( + { + ...recursiveTruncate( + stripped, + workspaceConfigs.truncationDepth + ), + timestamp: new Date().toLocaleString(), + level: info.level, + message: info.message, + }, + false, + workspaceConfigs.truncationDepth + ); + return info; + })(); +} diff --git a/packages/databricks-vscode/src/run/DatabricksDebugAdapter.ts b/packages/databricks-vscode/src/run/DatabricksDebugAdapter.ts index ccc5f040c..ddb52c8eb 100644 --- a/packages/databricks-vscode/src/run/DatabricksDebugAdapter.ts +++ b/packages/databricks-vscode/src/run/DatabricksDebugAdapter.ts @@ -20,10 +20,10 @@ import { ExtensionContext, } from "vscode"; import {ConnectionManager} from "../configuration/ConnectionManager"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; -import {WorkspaceFsAccessVerifier} from "../workspace-fs"; import {DatabricksRuntime} from "./DatabricksRuntime"; import {Subject} from "./Subject"; +import {BundleCommands} from "../ui/bundle-resource-explorer/BundleCommands"; +import {ConfigModel} from "../configuration/models/ConfigModel"; /** * This interface describes the mock-debug specific launch attributes @@ -47,9 +47,9 @@ export class DatabricksDebugAdapterFactory { constructor( private connection: ConnectionManager, - private codeSynchroniser: CodeSynchronizer, - private context: ExtensionContext, - private wsfsAccessVerifier: WorkspaceFsAccessVerifier + private configModel: ConfigModel, + private bundleCommands: BundleCommands, + private context: ExtensionContext ) {} dispose() {} @@ -58,9 +58,9 @@ export class DatabricksDebugAdapterFactory return new DebugAdapterInlineImplementation( new DatabricksDebugSession( this.connection, - this.codeSynchroniser, - this.context, - this.wsfsAccessVerifier + this.configModel, + this.bundleCommands, + this.context ) ); } @@ -73,17 +73,17 @@ export class DatabricksDebugSession extends LoggingDebugSession { constructor( connection: ConnectionManager, - codeSynchronizer: CodeSynchronizer, - context: ExtensionContext, - wsfsAccessVerifier: WorkspaceFsAccessVerifier + configModel: ConfigModel, + bundleCommands: BundleCommands, + context: ExtensionContext ) { super(); this.runtime = new DatabricksRuntime( connection, - codeSynchronizer, - context, - wsfsAccessVerifier + configModel, + bundleCommands, + context ); this.disposables.push( diff --git a/packages/databricks-vscode/src/run/DatabricksDebugConfigurationProvider.ts b/packages/databricks-vscode/src/run/DatabricksDebugConfigurationProvider.ts new file mode 100644 index 000000000..76b2adc5f --- /dev/null +++ b/packages/databricks-vscode/src/run/DatabricksDebugConfigurationProvider.ts @@ -0,0 +1,65 @@ +import { + DebugConfigurationProvider, + DebugConfiguration, + WorkspaceFolder, + ExtensionContext, +} from "vscode"; +import path from "node:path"; +import {DatabricksEnvFileManager} from "../file-managers/DatabricksEnvFileManager"; + +export interface DatabricksPythonDebugConfiguration extends DebugConfiguration { + databricks?: boolean; + program: string; + env?: Record; + isInternalDatabricksRun?: boolean; + console?: "integratedTerminal" | "externalTerminal" | "internalConsole"; +} + +function isTest(debugConfiguration: DebugConfiguration) { + return ( + debugConfiguration.env?.RUN_TEST_IDS_PORT !== undefined || + debugConfiguration.request === "test" || + debugConfiguration.name === "Debug Unit Test" + ); +} +export class DatabricksDebugConfigurationProvider + implements DebugConfigurationProvider +{ + constructor( + private readonly context: ExtensionContext, + private readonly databricksEnvFileManager: DatabricksEnvFileManager + ) {} + + async resolveDebugConfigurationWithSubstitutedVariables( + folder: WorkspaceFolder | undefined, + debugConfiguration: DebugConfiguration + ) { + if ( + debugConfiguration.databricks !== true && + !isTest(debugConfiguration) + ) { + return debugConfiguration; + } + + // Only add the bootstrap script if we are running explicit databricks debug + // configs. Other sources of configs such as tests, should not have the bootstrap + if (debugConfiguration.databricks) { + const userProgram = debugConfiguration.program; + debugConfiguration.program = this.context.asAbsolutePath( + path.join("resources", "python", "dbconnect-bootstrap.py") + ); + debugConfiguration.args = [ + userProgram, + ...(debugConfiguration.args ?? []), + ]; + } + + // Explicitly set our env vars even though bootstrap loads them. + debugConfiguration.env = { + ...(await this.databricksEnvFileManager.getEnv()), + ...(debugConfiguration.env ?? {}), + }; + + return debugConfiguration; + } +} diff --git a/packages/databricks-vscode/src/run/DatabricksRuntime.test.ts b/packages/databricks-vscode/src/run/DatabricksRuntime.test.ts index 164d63857..9bc96df0f 100644 --- a/packages/databricks-vscode/src/run/DatabricksRuntime.test.ts +++ b/packages/databricks-vscode/src/run/DatabricksRuntime.test.ts @@ -1,173 +1,174 @@ -/* eslint-disable @typescript-eslint/naming-convention */ - -import assert from "assert"; -import {mock, when, instance, anything, verify, capture} from "ts-mockito"; -import {Disposable, ExtensionContext, Uri} from "vscode"; -import {Cluster, Command, ExecutionContext} from "../sdk-extensions"; -import {DatabricksRuntime, OutputEvent} from "./DatabricksRuntime"; -import {ConnectionManager} from "../configuration/ConnectionManager"; -import { - LocalUri, - RemoteUri, - SyncDestinationMapper, -} from "../sync/SyncDestination"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; -import path from "node:path"; -import {WorkspaceFsAccessVerifier} from "../workspace-fs"; - -describe(__filename, () => { - let disposables: Array; - let runtime: DatabricksRuntime; - let executionContextMock: ExecutionContext; - let connectionManagerMock: ConnectionManager; - - beforeEach(async () => { - disposables = []; - - connectionManagerMock = mock(ConnectionManager); - when(connectionManagerMock.state).thenReturn("CONNECTING"); - - executionContextMock = mock(ExecutionContext); - when( - executionContextMock.execute( - anything(), - anything(), - anything(), - anything() - ) - ).thenResolve({ - cmd: mock(Command), - result: { - id: "123", - status: "Finished", - results: { - resultType: "text", - data: "43", - }, - }, - }); - const executionContext = instance(executionContextMock); - - const cluster = mock(Cluster); - when(cluster.createExecutionContext(anything())).thenResolve( - executionContext - ); - when(cluster.id).thenReturn("cluster-1"); - when(cluster.state).thenReturn("RUNNING"); - when(connectionManagerMock.cluster).thenReturn( - instance(cluster) - ); - - const syncDestination = new SyncDestinationMapper( - new LocalUri("/Desktop/workspaces"), - new RemoteUri("/Repos/fabian@databricks.com/test") - ); - when(connectionManagerMock.syncDestinationMapper).thenReturn( - syncDestination - ); - - const connectionManager = instance( - connectionManagerMock - ); - - const extensionContextMock = mock(); - when(extensionContextMock.extensionUri).thenReturn( - Uri.file(path.join(__dirname, "..", "..")) - ); - - const mockWsfsAccessVerfier = mock(); - when(mockWsfsAccessVerfier.verifyCluster(anything())).thenResolve(); - - const mockCodeSynchronizer = mock(); - when(mockCodeSynchronizer.state).thenReturn("WATCHING_FOR_CHANGES"); - - runtime = new DatabricksRuntime( - connectionManager, - instance(mockCodeSynchronizer), - instance(extensionContextMock), - instance(mockWsfsAccessVerfier) - ); - }); - - afterEach(() => { - disposables.forEach((d) => d.dispose()); - }); - - it("run a file", async () => { - const outputs: Array = []; - disposables.push( - runtime.onError((e) => { - console.error(e); - assert(false); - }), - runtime.onDidSendOutput((o) => { - outputs.push(o); - }) - ); - - await runtime.start("/Desktop/workspaces/hello.py", [], {}); - - verify(connectionManagerMock.waitForConnect()).called(); - assert.equal(outputs.length, 6); - assert(outputs[0].text.includes("Connecting to cluster")); - assert( - outputs[1].text.includes("Creating execution context on cluster") - ); - assert(outputs[2].text.includes("Synchronizing code to")); - assert(outputs[3].text.includes("Running hello.py")); - assert.equal(outputs[4].text, "43"); - assert(outputs[5].text.includes("Done")); - }); - - it("should inject environment variables", async () => { - await runtime.start("/Desktop/workspaces/hello.py", [], {TEST: "TEST"}); - - const code = capture(executionContextMock.execute).first()[0]; - assert(code.includes(`env = {"TEST":"TEST"}`)); - }); - - it("should have the right code without env vars", async () => { - await runtime.start("/Desktop/workspaces/hello.py", [], {}); - - const code = capture(executionContextMock.execute).first()[0]; - assert(code.includes(`env = {}`)); - }); - - it("should handle failed executions", async () => { - when( - executionContextMock.execute( - anything(), - anything(), - anything(), - anything() - ) - ).thenResolve({ - cmd: mock(Command), - result: { - id: "123", - status: "Finished", - results: { - resultType: "error", - summary: "summary", - cause: "something went wrong", - }, - }, - }); - - const outputs: Array = []; - disposables.push( - runtime.onError((e) => { - console.error(e); - assert(false); - }), - runtime.onDidSendOutput((o) => { - outputs.push(o); - }) - ); - - await runtime.start("/Desktop/workspaces/hello.py", [], {}); - - assert.equal(outputs.length, 6); - assert.equal(outputs[4].text, "something went wrong"); - }); -}); +//TODO: Fix these tests for new deploy and run paradigm +// /* eslint-disable @typescript-eslint/naming-convention */ + +// import assert from "assert"; +// import {mock, when, instance, anything, verify, capture} from "ts-mockito"; +// import {Disposable, ExtensionContext, Uri} from "vscode"; +// import {Cluster, Command, ExecutionContext} from "../sdk-extensions"; +// import {DatabricksRuntime, OutputEvent} from "./DatabricksRuntime"; +// import {ConnectionManager} from "../configuration/ConnectionManager"; +// import { +// LocalUri, +// RemoteUri, +// SyncDestinationMapper, +// } from "../sync/SyncDestination"; +// import {CodeSynchronizer} from "../sync/CodeSynchronizer"; +// import path from "node:path"; +// import {WorkspaceFsAccessVerifier} from "../workspace-fs"; + +// describe(__filename, () => { +// let disposables: Array; +// let runtime: DatabricksRuntime; +// let executionContextMock: ExecutionContext; +// let connectionManagerMock: ConnectionManager; + +// beforeEach(async () => { +// disposables = []; + +// connectionManagerMock = mock(ConnectionManager); +// when(connectionManagerMock.state).thenReturn("CONNECTING"); + +// executionContextMock = mock(ExecutionContext); +// when( +// executionContextMock.execute( +// anything(), +// anything(), +// anything(), +// anything() +// ) +// ).thenResolve({ +// cmd: mock(Command), +// result: { +// id: "123", +// status: "Finished", +// results: { +// resultType: "text", +// data: "43", +// }, +// }, +// }); +// const executionContext = instance(executionContextMock); + +// const cluster = mock(Cluster); +// when(cluster.createExecutionContext(anything())).thenResolve( +// executionContext +// ); +// when(cluster.id).thenReturn("cluster-1"); +// when(cluster.state).thenReturn("RUNNING"); +// when(connectionManagerMock.cluster).thenReturn( +// instance(cluster) +// ); + +// const syncDestination = new SyncDestinationMapper( +// new LocalUri("/Desktop/workspaces"), +// new RemoteUri("/Repos/fabian@databricks.com/test") +// ); +// when(connectionManagerMock.syncDestinationMapper).thenReturn( +// syncDestination +// ); + +// const connectionManager = instance( +// connectionManagerMock +// ); + +// const extensionContextMock = mock(); +// when(extensionContextMock.extensionUri).thenReturn( +// Uri.file(path.join(__dirname, "..", "..")) +// ); + +// const mockWsfsAccessVerfier = mock(); +// when(mockWsfsAccessVerfier.verifyCluster(anything())).thenResolve(); + +// const mockCodeSynchronizer = mock(); +// when(mockCodeSynchronizer.state).thenReturn("WATCHING_FOR_CHANGES"); + +// runtime = new DatabricksRuntime( +// connectionManager, +// instance(mockCodeSynchronizer), +// instance(extensionContextMock), +// instance(mockWsfsAccessVerfier) +// ); +// }); + +// afterEach(() => { +// disposables.forEach((d) => d.dispose()); +// }); + +// it("run a file", async () => { +// const outputs: Array = []; +// disposables.push( +// runtime.onError((e) => { +// console.error(e); +// assert(false); +// }), +// runtime.onDidSendOutput((o) => { +// outputs.push(o); +// }) +// ); + +// await runtime.start("/Desktop/workspaces/hello.py", [], {}); + +// verify(connectionManagerMock.waitForConnect()).called(); +// assert.equal(outputs.length, 6); +// assert(outputs[0].text.includes("Connecting to cluster")); +// assert( +// outputs[1].text.includes("Creating execution context on cluster") +// ); +// assert(outputs[2].text.includes("Synchronizing code to")); +// assert(outputs[3].text.includes("Running hello.py")); +// assert.equal(outputs[4].text, "43"); +// assert(outputs[5].text.includes("Done")); +// }); + +// it("should inject environment variables", async () => { +// await runtime.start("/Desktop/workspaces/hello.py", [], {TEST: "TEST"}); + +// const code = capture(executionContextMock.execute).first()[0]; +// assert(code.includes(`env = {"TEST":"TEST"}`)); +// }); + +// it("should have the right code without env vars", async () => { +// await runtime.start("/Desktop/workspaces/hello.py", [], {}); + +// const code = capture(executionContextMock.execute).first()[0]; +// assert(code.includes(`env = {}`)); +// }); + +// it("should handle failed executions", async () => { +// when( +// executionContextMock.execute( +// anything(), +// anything(), +// anything(), +// anything() +// ) +// ).thenResolve({ +// cmd: mock(Command), +// result: { +// id: "123", +// status: "Finished", +// results: { +// resultType: "error", +// summary: "summary", +// cause: "something went wrong", +// }, +// }, +// }); + +// const outputs: Array = []; +// disposables.push( +// runtime.onError((e) => { +// console.error(e); +// assert(false); +// }), +// runtime.onDidSendOutput((o) => { +// outputs.push(o); +// }) +// ); + +// await runtime.start("/Desktop/workspaces/hello.py", [], {}); + +// assert.equal(outputs.length, 6); +// assert.equal(outputs[4].text, "something went wrong"); +// }); +// }); diff --git a/packages/databricks-vscode/src/run/DatabricksRuntime.ts b/packages/databricks-vscode/src/run/DatabricksRuntime.ts index 55ad658b2..31f353bb7 100644 --- a/packages/databricks-vscode/src/run/DatabricksRuntime.ts +++ b/packages/databricks-vscode/src/run/DatabricksRuntime.ts @@ -21,16 +21,16 @@ import { } from "../sync/SyncDestination"; import {ConnectionManager} from "../configuration/ConnectionManager"; import { - promptForAttachingSyncDest, + promptForChangingTargetMode, promptForClusterAttach, promptForClusterStart, } from "./prompts"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; import * as fs from "node:fs/promises"; import {parseErrorResult} from "./ErrorParser"; import path from "node:path"; -import {WorkspaceFsAccessVerifier} from "../workspace-fs"; import {Time, TimeUnits} from "@databricks/databricks-sdk"; +import {BundleCommands} from "../ui/bundle-resource-explorer/BundleCommands"; +import {ConfigModel} from "../configuration/models/ConfigModel"; export interface OutputEvent { type: "prio" | "out" | "err"; @@ -97,9 +97,9 @@ export class DatabricksRuntime implements Disposable { constructor( private connection: ConnectionManager, - private codeSynchronizer: CodeSynchronizer, - private context: ExtensionContext, - private wsfsAccessVerifier: WorkspaceFsAccessVerifier + private readonly configModel: ConfigModel, + private bundleCommands: BundleCommands, + private context: ExtensionContext ) {} /** @@ -124,9 +124,24 @@ export class DatabricksRuntime implements Disposable { try { if (this.connection.state === "CONNECTING") { - log("Connecting to cluster ..."); + log("Connecting to databricks..."); await this.cancellable(this.connection.waitForConnect()); } + const mode = await this.configModel.get("mode"); + if (mode !== "development") { + promptForChangingTargetMode(mode); + return this._onErrorEmitter.fire(undefined); + } + const syncDestinationMapper = this.connection.syncDestinationMapper; + if (syncDestinationMapper === undefined) { + throw new Error("No sync destination found"); + } + + log("Uploading assets to databricks workspace..."); + this.state = "SYNCING"; + await this.bundleCommands.sync(); + + await commands.executeCommand("workbench.panel.repl.view.focus"); const cluster = this.connection.cluster; if (!cluster) { @@ -134,20 +149,12 @@ export class DatabricksRuntime implements Disposable { return this._onErrorEmitter.fire(undefined); } - await this.wsfsAccessVerifier.verifyCluster(cluster); - await this.wsfsAccessVerifier.verifyWorkspaceConfigs(); if (!["RUNNING", "RESIZING"].includes(cluster.state)) { this._onErrorEmitter.fire(undefined); promptForClusterStart(); return; } - const syncDestination = this.connection.syncDestinationMapper; - if (!syncDestination) { - promptForAttachingSyncDest(); - return this._onErrorEmitter.fire(undefined); - } - log(`Creating execution context on cluster ${cluster.id} ...`); this.state = "CREATE_CONTEXT"; @@ -163,52 +170,12 @@ export class DatabricksRuntime implements Disposable { await executionContext.destroy(); }); - // We wait for sync to complete so that the local files are consistant - // with the remote repo files - log(`Synchronizing code to ${syncDestination.remoteUri.path} ...`); - this.state = "SYNCING"; - - this.disposables.push( - this.codeSynchronizer.onDidChangeState((state) => { - if ( - !["IN_PROGRESS", "WATCHING_FOR_CHANGES"].includes(state) - ) { - return this._onErrorEmitter.fire( - "Execution cancelled because sync was stopped" - ); - } - }) - ); - - if ( - !["IN_PROGRESS", "WATCHING_FOR_CHANGES"].includes( - this.codeSynchronizer.state - ) - ) { - await commands.executeCommand("databricks.sync.start"); - } - - // We wait for sync to complete so that the local files are consistant - // with the remote repo files - await this.cancellable(this.codeSynchronizer.waitForSyncComplete()); if (this._runtimeState === "CANCELED") { return; } - if (this.codeSynchronizer.state !== "WATCHING_FOR_CHANGES") { - this._onDidSendOutputEmitter.fire({ - type: "err", - text: `Can't sync ${program}. Reason: ${this.codeSynchronizer.state}`, - filePath: program, - line: 0, - column: 0, - }); - this._onErrorEmitter.fire(`Error in running ${program}.`); - return; - } - await commands.executeCommand("workbench.panel.repl.view.focus"); log( - `Running ${syncDestination.localUri.relativePath( + `Running ${syncDestinationMapper.localUri.relativePath( new LocalUri(program) )} ...\n` ); @@ -218,7 +185,7 @@ export class DatabricksRuntime implements Disposable { await this.compileCommandString( program, args, - syncDestination, + syncDestinationMapper, envVars ), undefined, @@ -241,7 +208,7 @@ export class DatabricksRuntime implements Disposable { let localFile = ""; try { if (frame.file) { - localFile = syncDestination.remoteToLocal( + localFile = syncDestinationMapper.remoteToLocal( new RemoteUri(path.posix.normalize(frame.file)) ).path; diff --git a/packages/databricks-vscode/src/run/DatabricksWorkflowDebugAdapter.ts b/packages/databricks-vscode/src/run/DatabricksWorkflowDebugAdapter.ts index 02bf2e602..3f92afd92 100644 --- a/packages/databricks-vscode/src/run/DatabricksWorkflowDebugAdapter.ts +++ b/packages/databricks-vscode/src/run/DatabricksWorkflowDebugAdapter.ts @@ -22,11 +22,15 @@ import {DebugProtocol} from "@vscode/debugprotocol"; import {ConnectionManager} from "../configuration/ConnectionManager"; import {Subject} from "./Subject"; import {WorkflowRunner} from "./WorkflowRunner"; -import {promptForClusterAttach, promptForClusterStart} from "./prompts"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; +import { + promptForChangingTargetMode, + promptForClusterAttach, + promptForClusterStart, +} from "./prompts"; import {LocalUri} from "../sync/SyncDestination"; -import {WorkspaceFsAccessVerifier} from "../workspace-fs"; import {FileUtils} from "../utils"; +import {BundleCommands} from "../ui/bundle-resource-explorer/BundleCommands"; +import {ConfigModel} from "../configuration/models/ConfigModel"; /** * This interface describes the mock-debug specific launch attributes @@ -52,13 +56,13 @@ export class DatabricksWorkflowDebugAdapterFactory constructor( private connection: ConnectionManager, - private wsfsAccessVerifier: WorkspaceFsAccessVerifier, + private configModel: ConfigModel, context: ExtensionContext, - codeSynchronizer: CodeSynchronizer + bundleCommands: BundleCommands ) { this.workflowRunner = new WorkflowRunner( context, - codeSynchronizer, + bundleCommands, connection ); } @@ -71,8 +75,8 @@ export class DatabricksWorkflowDebugAdapterFactory return new DebugAdapterInlineImplementation( new DatabricksWorkflowDebugSession( this.connection, - this.workflowRunner, - this.wsfsAccessVerifier + this.configModel, + this.workflowRunner ) ); } @@ -85,8 +89,8 @@ export class DatabricksWorkflowDebugSession extends LoggingDebugSession { constructor( private connection: ConnectionManager, - private workflowRunner: WorkflowRunner, - private wsfsAccessVerifier: WorkspaceFsAccessVerifier + private configModel: ConfigModel, + private workflowRunner: WorkflowRunner ) { super(); } @@ -174,6 +178,12 @@ export class DatabricksWorkflowDebugSession extends LoggingDebugSession { await this.connection.waitForConnect(); } + const mode = await this.configModel.get("mode"); + if (mode !== "development") { + promptForChangingTargetMode(mode); + return this.onError(); + } + const cluster = this.connection.cluster; const workspaceClient = this.connection.workspaceClient; @@ -181,16 +191,14 @@ export class DatabricksWorkflowDebugSession extends LoggingDebugSession { promptForClusterAttach(); return this.onError(); } - const syncDestination = this.connection.syncDestinationMapper; - if (!syncDestination) { + const syncDestinationMapper = this.connection.syncDestinationMapper; + if (!syncDestinationMapper) { return this.onError( - "You must configure code synchronization to run on Databricks" + "No sync destination found. Maybe the databricks.yml is misconfgured." ); } await cluster.refresh(); - await this.wsfsAccessVerifier.verifyCluster(cluster); - await this.wsfsAccessVerifier.verifyWorkspaceConfigs(); if (!["RUNNING", "RESIZING"].includes(cluster.state)) { promptForClusterStart(); return this.onError(); @@ -201,7 +209,7 @@ export class DatabricksWorkflowDebugSession extends LoggingDebugSession { parameters, args, cluster, - syncDestination: syncDestination, + syncDestinationMapper, token: this.token, }); } diff --git a/packages/databricks-vscode/src/run/RunCommands.ts b/packages/databricks-vscode/src/run/RunCommands.ts index 17342f97a..0e1e2da93 100644 --- a/packages/databricks-vscode/src/run/RunCommands.ts +++ b/packages/databricks-vscode/src/run/RunCommands.ts @@ -1,20 +1,57 @@ -import {debug, Uri, window} from "vscode"; +import {commands, debug, ExtensionContext, Uri, window} from "vscode"; import {ConnectionManager} from "../configuration/ConnectionManager"; -import {promptForAttachingSyncDest} from "./prompts"; import {FileUtils} from "../utils"; import {LocalUri} from "../sync/SyncDestination"; +import {DatabricksPythonDebugConfiguration} from "./DatabricksDebugConfigurationProvider"; +import {MsPythonExtensionWrapper} from "../language/MsPythonExtensionWrapper"; +import path from "path"; +import {FeatureManager} from "../feature-manager/FeatureManager"; +import { + escapeExecutableForTerminal, + escapePathArgument, +} from "../utils/shellUtils"; +import {CustomWhenContext} from "../vscode-objs/CustomWhenContext"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; /** * Run related commands */ export class RunCommands { - constructor(private connection: ConnectionManager) {} + constructor( + private connection: ConnectionManager, + private readonly workspaceFolderManager: WorkspaceFolderManager, + private readonly pythonExtension: MsPythonExtensionWrapper, + private readonly featureManager: FeatureManager, + private readonly context: ExtensionContext, + private readonly customWhenContext: CustomWhenContext + ) { + this.context.subscriptions.push( + window.onDidChangeActiveTextEditor(async () => + this.updateRunAsWorkflowContext() + ) + ); + this.updateRunAsWorkflowContext(); + } + + async updateRunAsWorkflowContext() { + const uri = window.activeTextEditor?.document.uri; + if ( + uri && + uri.scheme === "file" && + ((await FileUtils.isNotebook(new LocalUri(uri))) || + uri.fsPath.endsWith(".py")) + ) { + this.customWhenContext.setShowRunAsWorkflow(true); + } else { + this.customWhenContext.setShowRunAsWorkflow(false); + } + } /** * Run a Python file using the command execution API */ runEditorContentsCommand() { - return async (resource: Uri) => { + return async (resource?: Uri) => { const targetResource = this.getTargetResource(resource); if (targetResource) { if (await FileUtils.isNotebook(new LocalUri(targetResource))) { @@ -28,11 +65,6 @@ export class RunCommands { await this.connection.waitForConnect(); } - if (this.connection.syncDestinationMapper === undefined) { - promptForAttachingSyncDest(); - return; - } - await debug.startDebugging( undefined, { @@ -51,7 +83,7 @@ export class RunCommands { * Run a Python file or notebook as a workflow on the connected cluster */ runEditorContentsAsWorkflowCommand() { - return async (resource: Uri) => { + return async (resource?: Uri) => { const targetResource = this.getTargetResource(resource); if (targetResource) { if (this.connection.state === "CONNECTING") { @@ -59,8 +91,9 @@ export class RunCommands { } if (this.connection.syncDestinationMapper === undefined) { - promptForAttachingSyncDest(); - return; + throw new Error( + "No sync destination found. Maybe the databricks.yml is misconfgured." + ); } await debug.startDebugging( @@ -77,10 +110,75 @@ export class RunCommands { }; } - private getTargetResource(resource: Uri): Uri | undefined { + private async checkDbconnectEnabled() { + const featureState = await this.featureManager.isEnabled( + "environment.dependencies" + ); + if (featureState.available) { + return true; + } + return await commands.executeCommand("databricks.environment.setup"); + } + + private getTargetResource(resource?: Uri): Uri | undefined { if (!resource && window.activeTextEditor) { return window.activeTextEditor.document.uri; } return resource; } + + async debugFileUsingDbconnect(resource?: Uri) { + if (!(await this.checkDbconnectEnabled())) { + return; + } + + const targetResource = this.getTargetResource(resource); + if (!targetResource) { + window.showErrorMessage("Open a file to run"); + return; + } + const config: DatabricksPythonDebugConfiguration = { + program: targetResource.fsPath, + type: "python", + name: "Databricks Connect", + request: "launch", + databricks: true, + console: "integratedTerminal", + env: {...process.env}, + }; + + debug.startDebugging( + this.workspaceFolderManager.activeWorkspaceFolder, + config + ); + } + + async runFileUsingDbconnect(resource?: Uri) { + if (!(await this.checkDbconnectEnabled())) { + return; + } + + const targetResource = this.getTargetResource(resource); + if (!targetResource) { + window.showErrorMessage("Open a file to run"); + return; + } + + const executable = await this.pythonExtension.getPythonExecutable(); + if (!executable) { + window.showErrorMessage("No python executable found"); + return; + } + + const terminal = window.activeTerminal ?? window.createTerminal(); + const bootstrapPath = this.context.asAbsolutePath( + path.join("resources", "python", "dbconnect-bootstrap.py") + ); + terminal.show(); + terminal.sendText( + `${escapeExecutableForTerminal(executable)} ${escapePathArgument( + bootstrapPath + )} ${escapePathArgument(targetResource.fsPath)}` + ); + } } diff --git a/packages/databricks-vscode/src/run/WorkflowRunner.ts b/packages/databricks-vscode/src/run/WorkflowRunner.ts index 9214c0280..f2511ba39 100644 --- a/packages/databricks-vscode/src/run/WorkflowRunner.ts +++ b/packages/databricks-vscode/src/run/WorkflowRunner.ts @@ -4,7 +4,6 @@ import {basename} from "node:path"; import { CancellationToken, CancellationTokenSource, - commands, Disposable, ExtensionContext, Uri, @@ -12,13 +11,12 @@ import { window, } from "vscode"; import {LocalUri, SyncDestinationMapper} from "../sync/SyncDestination"; -import {CodeSynchronizer} from "../sync/CodeSynchronizer"; import {FileUtils} from "../utils"; import {WorkflowOutputPanel} from "./WorkflowOutputPanel"; import Convert from "ansi-to-html"; import {ConnectionManager} from "../configuration/ConnectionManager"; import {WorkspaceFsWorkflowWrapper} from "../workspace-fs/WorkspaceFsWorkflowWrapper"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; +import {BundleCommands} from "../ui/bundle-resource-explorer/BundleCommands"; export class WorkflowRunner implements Disposable { private panels = new Map(); @@ -26,7 +24,7 @@ export class WorkflowRunner implements Disposable { constructor( private context: ExtensionContext, - private codeSynchronizer: CodeSynchronizer, + private bundleCommands: BundleCommands, private readonly connectionManager: ConnectionManager ) {} @@ -71,57 +69,44 @@ export class WorkflowRunner implements Disposable { parameters = {}, args = [], cluster, - syncDestination, + syncDestinationMapper, token, }: { program: LocalUri; parameters?: Record; args?: Array; cluster: Cluster; - syncDestination: SyncDestinationMapper; + syncDestinationMapper: SyncDestinationMapper; token?: CancellationToken; }) { const panel = await this.getPanelForUri(program.uri); - const cancellation = new CancellationTokenSource(); - panel.onDidDispose(() => cancellation.cancel()); + const panelCancellation = new CancellationTokenSource(); + panel.onDidDispose(() => panelCancellation.cancel()); if (token) { - token.onCancellationRequested(() => { - cancellation.cancel(); - }); + token.onCancellationRequested(() => panelCancellation.cancel()); + } + + try { + await this.bundleCommands.sync(); + } catch (e: unknown) { + if (e instanceof Error) { + panel.showError({ + message: `Can't upload assets to databricks workspace. \nReason: ${e.message}`, + }); + } + return; } - if ( - !["IN_PROGRESS", "WATCHING_FOR_CHANGES"].includes( - this.codeSynchronizer.state - ) - ) { - await commands.executeCommand("databricks.sync.start"); + if (panelCancellation.token.isCancellationRequested) { + return; } - // We wait for sync to complete so that the local files are consistant - // with the remote repo files - await Promise.race([ - this.codeSynchronizer.waitForSyncComplete(), - new Promise( - (resolve) => - token?.onCancellationRequested(() => resolve(undefined)) - ), - ]); if (token?.isCancellationRequested) { panel.showError({ message: "Execution terminated by user.", }); - this.codeSynchronizer.stop(); - return; - } - if (this.codeSynchronizer.state !== "WATCHING_FOR_CHANGES") { - panel.showError({ - message: `Can't sync ${program}. \nReason: ${ - this.codeSynchronizer.reason ?? this.codeSynchronizer.state - }`, - }); return; } @@ -152,18 +137,15 @@ export class WorkflowRunner implements Disposable { const notebookType = await FileUtils.isNotebook(program); if (notebookType) { let remoteFilePath: string = - syncDestination.localToRemoteNotebook(program).path; - if ( - workspaceConfigs.enableFilesInWorkspace && - syncDestination.remoteUri.type === "workspace" - ) { + syncDestinationMapper.localToRemoteNotebook(program).path; + if (syncDestinationMapper.remoteUri.type === "workspace") { const wrappedFile = await new WorkspaceFsWorkflowWrapper( this.connectionManager, this.context ).createNotebookWrapper( program, - syncDestination.localToRemote(program), - syncDestination.remoteUri, + syncDestinationMapper.localToRemote(program), + syncDestinationMapper.remoteUri, notebookType ); remoteFilePath = wrappedFile @@ -180,20 +162,20 @@ export class WorkflowRunner implements Disposable { ) => { panel.updateState(cluster, state, run); }, - token: cancellation.token, + token: panelCancellation.token, }) ); } else { - const originalFileUri = syncDestination.localToRemote(program); + const originalFileUri = + syncDestinationMapper.localToRemote(program); const wrappedFile = - workspaceConfigs.enableFilesInWorkspace && - syncDestination.remoteUri.type === "workspace" + syncDestinationMapper.remoteUri.type === "workspace" ? await new WorkspaceFsWorkflowWrapper( this.connectionManager, this.context ).createPythonFileWrapper( originalFileUri, - syncDestination.remoteUri + syncDestinationMapper.remoteUri ) : undefined; const response = await cluster.runPythonAndWait({ @@ -205,7 +187,7 @@ export class WorkflowRunner implements Disposable { ) => { panel.updateState(cluster, state, run); }, - token: cancellation.token, + token: panelCancellation.token, }); //TODO: Respone logs will contain bootstrap code path in the error stack trace. Remove it. panel.showStdoutResult(response.logs || ""); diff --git a/packages/databricks-vscode/src/run/prompts.ts b/packages/databricks-vscode/src/run/prompts.ts index ea6b44cda..4d563ede8 100644 --- a/packages/databricks-vscode/src/run/prompts.ts +++ b/packages/databricks-vscode/src/run/prompts.ts @@ -26,16 +26,16 @@ export async function promptForClusterStart() { } } -export async function promptForAttachingSyncDest() { +export async function promptForChangingTargetMode(curMode: string | undefined) { const response = await window.showErrorMessage( - "Please configure a Sync Destination", - "Configure Sync Destination", + `Running is disabled for non development targets. Current target mode is ${curMode}.`, + "Change Target Mode", "Cancel" ); switch (response) { - case "Configure Sync Destination": + case "Change Target Mode": await commands.executeCommand( - "databricks.connection.attachSyncDestination" + "databricks.connection.bundle.selectTarget" ); } } diff --git a/packages/databricks-vscode/src/sdk-extensions/Cluster.ts b/packages/databricks-vscode/src/sdk-extensions/Cluster.ts index a4bb41ebf..de9fc1dc8 100644 --- a/packages/databricks-vscode/src/sdk-extensions/Cluster.ts +++ b/packages/databricks-vscode/src/sdk-extensions/Cluster.ts @@ -173,16 +173,16 @@ export class Cluster { )); } - const permissionApi = new iam.PermissionsService(this.client); - const perms = await permissionApi.get({ - request_object_id: this.id, - request_object_type: "clusters", + const perms = await this.clusterApi.getPermissions({ + cluster_id: this.id, }); - return (this._hasExecutePerms = (perms.access_control_list ?? []).find((ac) => { return ( ac.user_name === userDetails.userName || + // `users` is a system group for "All Workspace Users" + // https://docs.databricks.com/en/admin/users-groups/groups.html + ac.group_name === "users" || userDetails.groups ?.map((v) => v.display) .includes(ac.group_name ?? "") diff --git a/packages/databricks-vscode/src/sdk-extensions/wsfs/WorkspaceFsDir.ts b/packages/databricks-vscode/src/sdk-extensions/wsfs/WorkspaceFsDir.ts index e8258acbf..de02ef562 100644 --- a/packages/databricks-vscode/src/sdk-extensions/wsfs/WorkspaceFsDir.ts +++ b/packages/databricks-vscode/src/sdk-extensions/wsfs/WorkspaceFsDir.ts @@ -6,7 +6,7 @@ import {isDirectory, isFile} from "./utils"; export class WorkspaceFsDir extends WorkspaceFsEntity { override async generateUrl(host: URL): Promise { - return `${host.host}#folder/${this.details.object_id}`; + return `${host.host}/browse/folders/${this.details.object_id}`; } public getAbsoluteChildPath(path: string) { diff --git a/packages/databricks-vscode/src/sync/CodeSynchronizer.ts b/packages/databricks-vscode/src/sync/CodeSynchronizer.ts index 14fa0bbd5..0388c10da 100644 --- a/packages/databricks-vscode/src/sync/CodeSynchronizer.ts +++ b/packages/databricks-vscode/src/sync/CodeSynchronizer.ts @@ -3,6 +3,7 @@ import {SyncTask, TASK_SYNC_TYPE} from "../cli/SyncTasks"; import {CliWrapper} from "../cli/CliWrapper"; import {ConnectionManager} from "../configuration/ConnectionManager"; import {PackageMetaData} from "../utils/packageJsonUtils"; +import {ConfigModel} from "../configuration/models/ConfigModel"; export type SyncState = | "IN_PROGRESS" @@ -31,6 +32,7 @@ export class CodeSynchronizer implements Disposable { constructor( private connection: ConnectionManager, + private readonly configModel: ConfigModel, private cli: CliWrapper, private packageMetadata: PackageMetaData ) { @@ -77,6 +79,7 @@ export class CodeSynchronizer implements Disposable { this._onDidChangeStateEmitter.fire(this._state); const task = new SyncTask( this.connection, + this.configModel, this.cli, syncType, this.packageMetadata, @@ -109,28 +112,10 @@ export class CodeSynchronizer implements Disposable { this.disposables.forEach((d) => d.dispose()); } - // This function waits for sync to reach WATCHING_FOR_CHANGES which is a - // necessary condition to execute local code on databricks. This state denotes - // all local changes have been synced to remote workspace - async waitForSyncComplete(): Promise { - if (this._state !== "WATCHING_FOR_CHANGES") { - return await new Promise((resolve) => { - const changeListener = this.onDidChangeState(() => { - if ( - [ - "WATCHING_FOR_CHANGES", - "FILES_IN_REPOS_DISABLED", - "FILES_IN_WORKSPACE_DISABLED", - "ERROR", - ].includes(this.state) - ) { - changeListener.dispose(); - resolve(); - } - }, this); - - this.disposables.push(changeListener); - }); - } + get isRunning() { + return ( + this.state === "IN_PROGRESS" || + this.state === "WATCHING_FOR_CHANGES" + ); } } diff --git a/packages/databricks-vscode/src/telemetry/constants.ts b/packages/databricks-vscode/src/telemetry/constants.ts index c833824dc..3a44b450c 100644 --- a/packages/databricks-vscode/src/telemetry/constants.ts +++ b/packages/databricks-vscode/src/telemetry/constants.ts @@ -1,22 +1,36 @@ import {AuthType} from "@databricks/databricks-sdk"; -/** The production application insights configuration string for Databricks. */ -export const PROD_APP_INSIGHTS_CONFIGURATION_STRING = - "InstrumentationKey=ebe191c5-f06b-4189-b68c-34fb5fbdb3f0;IngestionEndpoint=https://eastus2-3.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus2.livediagnostics.monitor.azure.com/"; -/** The application insights configuration string used while developing on the VS Code extension */ -export const DEV_APP_INSIGHTS_CONFIGURATION_STRING = - "InstrumentationKey=257d1561-5005-4a76-a3a8-7955df129e86;IngestionEndpoint=https://eastus2-3.in.applicationinsights.azure.com/;LiveEndpoint=https://eastus2.livediagnostics.monitor.azure.com/"; +/** The production application insights instrumentation key for Databricks. */ +export const PROD_APP_INSIGHTS_CONFIGURATION_KEY = + "ebe191c5-f06b-4189-b68c-34fb5fbdb3f0"; +/** The application insights instrumentation key used while developing on the VS Code extension */ +export const DEV_APP_INSIGHTS_CONFIGURATION_KEY = + "257d1561-5005-4a76-a3a8-7955df129e86"; /** The list of all events which can be monitored. */ /* eslint-disable @typescript-eslint/naming-convention */ export enum Events { COMMAND_EXECUTION = "commandExecution", - EXTENSION_ACTIVATED = "extensionActivation", + EXTENSION_ACTIVATION = "extensionActivation", + EXTENSION_INITIALIZATION = "extensionInitialization", + AUTO_LOGIN = "autoLogin", + MANUAL_LOGIN = "manualLogin", + AUTO_MIGRATION = "autoMigration", + MANUAL_MIGRATION = "manualMigration", + BUNDLE_RUN = "bundleRun", + BUNDLE_INIT = "bundleInit", + BUNDLE_SUB_PROJECTS = "bundleSubProjects", CONNECTION_STATE_CHANGED = "connectionStateChanged", - SYNC_DESTINATION = "syncDestination", - SWITCH_TO_WORKSPACE_PROMPT = "switchToWorkspacePrompt", } /* eslint-enable @typescript-eslint/naming-convention */ +export type AutoLoginSource = "init" | "hostChange" | "targetChange"; +export type ManualLoginSource = + | "authTypeSwitch" + | "authTypeLogin" + | "command" + | "api"; +export type BundleRunResourceType = "pipelines" | "jobs"; + /** Documentation about all of the properties and metrics of the event. */ type EventDescription = {[K in keyof T]?: {comment?: string}}; @@ -69,8 +83,70 @@ export class EventTypes { }, ...getDurationProperty(), }; - [Events.EXTENSION_ACTIVATED]: EventType = { - comment: "Extention was activated", + [Events.EXTENSION_ACTIVATION]: EventType = { + comment: "Extension was activated", + }; + [Events.EXTENSION_INITIALIZATION]: EventType< + { + success: boolean; + type?: "dabs" | "legacy" | "unknown"; + } & DurationMeasurement + > = { + comment: "Extension services were initialized", + }; + [Events.AUTO_LOGIN]: EventType< + { + success: boolean; + source: AutoLoginSource; + } & DurationMeasurement + > = { + comment: "Extension logged in automatically", + }; + [Events.MANUAL_LOGIN]: EventType< + { + success: boolean; + source: ManualLoginSource; + } & DurationMeasurement + > = { + comment: "User logged in manually", + }; + [Events.AUTO_MIGRATION]: EventType< + { + success: boolean; + } & DurationMeasurement + > = { + comment: "Extension migrated automatically", + }; + [Events.MANUAL_MIGRATION]: EventType< + { + success: boolean; + } & DurationMeasurement + > = { + comment: "User migrated manually", + }; + [Events.BUNDLE_RUN]: EventType< + { + success: boolean; + cancelled?: boolean; + resourceType?: BundleRunResourceType; + } & DurationMeasurement + > = { + comment: "Execute a bundle resource", + }; + [Events.BUNDLE_INIT]: EventType< + { + success: boolean; + } & DurationMeasurement + > = { + comment: "Initialize a new bundle project", + }; + [Events.BUNDLE_SUB_PROJECTS]: EventType<{ + count: number; + }> = { + comment: "Sub-projects in the active workspace folder", + count: { + comment: "Amount of sub-projects in the active workspace folder", + }, }; [Events.CONNECTION_STATE_CHANGED]: EventType<{ newState: string; @@ -80,22 +156,6 @@ export class EventTypes { comment: "The new state of the connection", }, }; - [Events.SYNC_DESTINATION]: EventType<{ - destination: string; - }> = { - comment: "Sync destination was selected", - destination: { - comment: "The destination that was selected", - }, - }; - [Events.SWITCH_TO_WORKSPACE_PROMPT]: EventType<{ - selection: string; - }> = { - comment: "Prompt to switch to workspace was shown", - selection: { - comment: "The selection that was made", - }, - }; } /** @@ -110,6 +170,10 @@ export type EventProperties = { : never; }; +export type EventReporter = ( + props: Omit +) => void; + export type EnvironmentType = "tests" | "prod"; /** diff --git a/packages/databricks-vscode/src/telemetry/index.test.ts b/packages/databricks-vscode/src/telemetry/index.test.ts index 5bf0cb221..a6d0dfb14 100644 --- a/packages/databricks-vscode/src/telemetry/index.test.ts +++ b/packages/databricks-vscode/src/telemetry/index.test.ts @@ -5,7 +5,6 @@ import {mock, instance, capture, when} from "ts-mockito"; import {Telemetry, getContextMetadata, toUserMetadata} from "."; import {Events, Metadata} from "./constants"; import {DatabricksWorkspace} from "../configuration/DatabricksWorkspace"; -import {Uri} from "vscode"; import {ConnectionManager} from "../configuration/ConnectionManager"; import {ApiClient, Config} from "@databricks/databricks-sdk"; @@ -41,7 +40,7 @@ describe(__filename, () => { }); it("sets context metadata with prod env type", async () => { - delete process.env["TEST_DEFAULT_CLUSTER_ID"]; + delete process.env["DATABRICKS_VSCODE_INTEGRATION_TEST"]; telemetry.setMetadata(Metadata.CONTEXT, getContextMetadata()); telemetry.recordEvent(Events.COMMAND_EXECUTION, { command: "testCommand", @@ -59,7 +58,7 @@ describe(__filename, () => { }); it("sets context metadata with tests env type", async () => { - process.env["TEST_DEFAULT_CLUSTER_ID"] = "123"; + process.env["DATABRICKS_VSCODE_INTEGRATION_TEST"] = "true"; telemetry.setMetadata(Metadata.CONTEXT, getContextMetadata()); telemetry.recordEvent(Events.COMMAND_EXECUTION, { command: "testCommand", @@ -79,7 +78,7 @@ describe(__filename, () => { it("sets user metadata correctly after logged in", async () => { const ws = mock(DatabricksWorkspace); when(ws.userName).thenReturn("miles@databricks.com"); - when(ws.host).thenReturn(Uri.parse("https://my.databricks.com")); + when(ws.host).thenReturn(new URL("https://my.databricks.com")); const cm = mock(ConnectionManager); when(cm.databricksWorkspace).thenReturn(instance(ws)); const mockConfig = mock(Config); diff --git a/packages/databricks-vscode/src/telemetry/index.ts b/packages/databricks-vscode/src/telemetry/index.ts index b56f9dd30..2f8062ca5 100644 --- a/packages/databricks-vscode/src/telemetry/index.ts +++ b/packages/databricks-vscode/src/telemetry/index.ts @@ -1,20 +1,21 @@ import TelemetryReporter from "@vscode/extension-telemetry"; import {DatabricksWorkspace} from "../configuration/DatabricksWorkspace"; -import {isDevExtension} from "../utils/developmentUtils"; +import {isDevExtension, isIntegrationTest} from "../utils/developmentUtils"; import { - DEV_APP_INSIGHTS_CONFIGURATION_STRING, + DEV_APP_INSIGHTS_CONFIGURATION_KEY, EventProperties, EventTypes, ExtraMetadata, Metadata, MetadataTypes, - PROD_APP_INSIGHTS_CONFIGURATION_STRING, + PROD_APP_INSIGHTS_CONFIGURATION_KEY, } from "./constants"; import crypto from "crypto"; import bcrypt from "bcryptjs"; import {ConnectionManager} from "../configuration/ConnectionManager"; export {Events, EventTypes} from "./constants"; +export type {EventReporter} from "./constants"; /** * A version number used for the telemetry metric schema. The version of the schema is always provided @@ -55,7 +56,7 @@ async function getDatabricksWorkspaceMetadata( const hashedUserName = await bcrypt.hash(userName, bcryptSalt); return { hashedUserName: hashedUserName, - host: databricksWorkspace.host.authority, + host: databricksWorkspace.host.host, }; } @@ -81,17 +82,15 @@ export async function toUserMetadata( export function getContextMetadata(): ExtraMetadata[Metadata.CONTEXT] { return { - environmentType: process.env["TEST_DEFAULT_CLUSTER_ID"] - ? "tests" - : "prod", + environmentType: isIntegrationTest() ? "tests" : "prod", }; } function getTelemetryKey(): string { if (isDevExtension()) { - return DEV_APP_INSIGHTS_CONFIGURATION_STRING; + return DEV_APP_INSIGHTS_CONFIGURATION_KEY; } - return PROD_APP_INSIGHTS_CONFIGURATION_STRING; + return PROD_APP_INSIGHTS_CONFIGURATION_KEY; } function getTelemetryReporter(): TelemetryReporter | undefined { @@ -183,4 +182,12 @@ export class Telemetry { finalMetrics ); } + + start(eventName: E) { + const start = performance.now(); + return (props: Omit) => { + const duration = performance.now() - start; + this.recordEvent(eventName, {duration, ...(props as any)}); + }; + } } diff --git a/packages/databricks-vscode/src/test/e2e/auth.e2e.ts b/packages/databricks-vscode/src/test/e2e/auth.e2e.ts new file mode 100644 index 000000000..ae2fbe47e --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/auth.e2e.ts @@ -0,0 +1,101 @@ +import assert from "node:assert"; +import { + dismissNotifications, + waitForInput, + getViewSection, + waitForLogin, +} from "./utils/commonUtils.ts"; +import {CustomTreeSection} from "wdio-vscode-service"; +import { + getBasicBundleConfig, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; + +describe("Configure Databricks Extension", async function () { + this.timeout(3 * 60 * 1000); + + it("should open VSCode and dismiss notifications", async function () { + assert( + process.env.DATABRICKS_CONFIG_FILE, + "DATABRICKS_CONFIG_FILE doesn't exist" + ); + const workbench = await browser.getWorkbench(); + const title = await workbench.getTitleBar().getTitle(); + assert( + title.indexOf("[Extension Development Host]") >= 0, + "Unexpected VSCode title" + ); + await dismissNotifications(); + }); + + it("should wait for a welcome screen", async () => { + const section = await getViewSection("CONFIGURATION"); + const welcomeButtons = await browser.waitUntil(async () => { + const welcome = await section!.findWelcomeContent(); + const buttons = await welcome!.getButtons(); + if (buttons?.length >= 2) { + return buttons; + } + }); + assert(welcomeButtons, "Welcome buttons don't exist"); + }); + + it("should automatically login after detecting bundle configuration", async () => { + assert(process.env.WORKSPACE_PATH, "WORKSPACE_PATH doesn't exist"); + await writeRootBundleConfig( + getBasicBundleConfig(), + process.env.WORKSPACE_PATH + ); + await waitForLogin("DEFAULT"); + }); + + it("should create new profile", async () => { + // We create a new profile programmatically to avoid leaking tokens through screenshots or video reporters. + // We still trigger similar code path to the UI flow. + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand( + "databricks.connection.saveNewProfile", + "NEW_PROFILE" + ); + }); + }); + + it("should change profiles", async () => { + const section = (await getViewSection( + "CONFIGURATION" + )) as CustomTreeSection; + assert(section, "CONFIGURATION section doesn't exist"); + const signInButton = await browser.waitUntil( + async () => { + const items = await section.getVisibleItems(); + for (const item of items) { + const label = await item.getLabel(); + if (label.toLowerCase().includes("auth type")) { + return item.getActionButton("Sign in"); + } + } + }, + {timeout: 10_000} + ); + assert(signInButton, "Sign In button doesn't exist"); + (await signInButton.elem).click(); + + const authMethodInput = await waitForInput(); + const newProfilePick = + await authMethodInput.findQuickPick("NEW_PROFILE"); + assert( + newProfilePick, + "NEW_PROFILE is absent in the quick pick selection" + ); + await newProfilePick.select(); + await waitForLogin("NEW_PROFILE"); + }); + + it("should pick up new profile after reloading", async () => { + const workbench = await driver.getWorkbench(); + const editorView = workbench.getEditorView(); + await editorView.closeAllEditors(); + await workbench.executeCommand("Developer: Reload Window"); + await waitForLogin("NEW_PROFILE"); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/bundle_init.e2e.ts b/packages/databricks-vscode/src/test/e2e/bundle_init.e2e.ts new file mode 100644 index 000000000..3d9fd9d09 --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/bundle_init.e2e.ts @@ -0,0 +1,133 @@ +import assert from "node:assert"; +import { + dismissNotifications, + getTabByTitle, + getUniqueResourceName, + getViewSection, + waitForInput, + waitForLogin, + waitForTreeItems, +} from "./utils/commonUtils.ts"; +import {Workbench, sleep} from "wdio-vscode-service"; +import {tmpdir} from "os"; +import {Key} from "webdriverio"; + +describe("Bundle Init", async function () { + let workbench: Workbench; + let vscodeWorkspaceRoot: string; + let projectName: string; + + this.timeout(3 * 60 * 1000); + + before(async function () { + assert( + process.env.TEST_DEFAULT_CLUSTER_ID, + "TEST_DEFAULT_CLUSTER_ID env var doesn't exist" + ); + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + workbench = await browser.getWorkbench(); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should initialize new project", async function () { + await browser.executeWorkbench((vscode) => { + vscode.commands.executeCommand("databricks.bundle.initNewProject"); + }); + + projectName = getUniqueResourceName("init_test"); + + const hostSelectionInput = await waitForInput(); + await hostSelectionInput.confirm(); + + await sleep(1000); + + const profileSelectionInput = await waitForInput(); + await profileSelectionInput.selectQuickPick("DEFAULT"); + + const parentDir = tmpdir(); + const parentFolderInput = await waitForInput(); + // Type in the parentDir value to the input + await browser.keys(parentDir.split("")); + await sleep(1000); + const picks = await parentFolderInput.getQuickPicks(); + const pick = picks.filter((p) => p.getIndex() === 0)[0]; + assert(pick, "Parent folder quick pick doesn't have any items"); + expect(await pick.getLabel()).toBe(parentDir); + await pick.select(); + + await dismissNotifications(); + + // Wait for the databricks cli terminal window to pop up and select all + // default options for the default template + const editorView = workbench.getEditorView(); + const title = "Databricks Project Init"; + const initTab = await getTabByTitle(title); + assert(initTab, "Can't find a tab for project-init terminal wizard"); + await initTab.select(); + await sleep(1000); + + //select temaplate type + await browser.keys("default-python".split("")); + await sleep(1000); + await browser.keys([Key.Enter]); + //enter project name temaplate type + await browser.keys(projectName.split("")); + await sleep(1000); + await browser.keys([Key.Enter]); + await browser.waitUntil( + async () => { + const activeTab = await editorView.getActiveTab(); + if ((await activeTab?.getTitle()) !== title) { + return true; + } + await browser.keys([Key.Enter]); + }, + { + timeout: 20_000, + interval: 2_000, + timeoutMsg: "Can't complete cli bundle init wizard", + } + ); + + const openProjectFolderInput = await waitForInput(); + await openProjectFolderInput.selectQuickPick(projectName); + + // Wait until vscode is re-opened with the new workspace root + await browser.waitUntil( + async () => { + vscodeWorkspaceRoot = (await browser.executeWorkbench( + (vscode) => { + return vscode.workspace.workspaceFolders[0].uri.fsPath; + } + )) as string; + return vscodeWorkspaceRoot.includes(projectName); + }, + { + timeout: 60_000, + timeoutMsg: "Can't connect to the new project window", + } + ); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + }); + + it("should find resource explorer view", async function () { + const section = await getViewSection("BUNDLE RESOURCE EXPLORER"); + assert(section); + await waitForTreeItems(section, 20_000); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/bundle_variables.e2e.ts b/packages/databricks-vscode/src/test/e2e/bundle_variables.e2e.ts new file mode 100644 index 000000000..5d07ea6ed --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/bundle_variables.e2e.ts @@ -0,0 +1,213 @@ +import assert from "node:assert"; +import { + dismissNotifications, + getUniqueResourceName, + getViewSection, + waitForLogin, + waitForTreeItems, +} from "./utils/commonUtils.ts"; +import {CustomTreeSection, TextEditor, Workbench} from "wdio-vscode-service"; +import { + getBasicBundleConfig, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; +import {BundleSchema} from "../../bundle/types.ts"; + +describe("Bundle Variables", async function () { + let workbench: Workbench; + let vscodeWorkspaceRoot: string; + let schemaDef: BundleSchema; + + this.timeout(3 * 60 * 1000); + + async function createProjectWithJob() { + const projectName = getUniqueResourceName("bundle_variables"); + /* eslint-disable @typescript-eslint/naming-convention */ + schemaDef = getBasicBundleConfig({ + bundle: { + name: projectName, + deployment: {}, + }, + variables: { + varWithDefault: { + default: "default", + }, + }, + targets: { + dev_test: { + variables: { + varWithDefault: "dev", + }, + }, + }, + }); + + /* eslint-enable @typescript-eslint/naming-convention */ + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + } + + before(async function () { + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + + workbench = await browser.getWorkbench(); + vscodeWorkspaceRoot = process.env.WORKSPACE_PATH; + await createProjectWithJob(); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + async function assertVariableValue( + section: CustomTreeSection, + variableName: string, + expected: {value?: string; defaultValue?: string} + ) { + await section.expand(); + const variableTreeItem = await section.findItem(variableName); + assert(variableTreeItem); + assert.strictEqual( + await variableTreeItem.getDescription(), + expected.value + ); + + if (expected.defaultValue) { + const defaultValueTreeItem = ( + await section.openItem(variableName) + )[0]; + assert(defaultValueTreeItem); + assert.strictEqual( + await defaultValueTreeItem.getLabel(), + "Default" + ); + assert.strictEqual( + await defaultValueTreeItem.getDescription(), + expected.defaultValue + ); + } + } + + it("should find bundle variable explorer and load default variables", async function () { + const section = (await getViewSection("BUNDLE VARIABLES")) as + | CustomTreeSection + | undefined; + assert(section); + await waitForTreeItems(section, 20_000); + + await assertVariableValue(section, "varWithDefault", { + value: "dev", + defaultValue: "default", + }); + }); + + it("should override default variable", async function () { + await browser.executeWorkbench((vscode) => { + vscode.commands.executeCommand( + "databricks.bundle.variable.openFile" + ); + }); + const editor = (await workbench + .getEditorView() + .openEditor("vscode.bundlevars.json")) as TextEditor; + assert(editor); + + await editor.clearText(); + await editor.setText( + JSON.stringify({varWithDefault: "new value"}, null, 4) + ); + await editor.save(); + + const section = (await getViewSection("BUNDLE VARIABLES")) as + | CustomTreeSection + | undefined; + assert(section); + await waitForTreeItems(section, 5_000); + + await browser.waitUntil( + async () => { + await assertVariableValue(section, "varWithDefault", { + value: "new value", + defaultValue: "default", + }); + return true; + }, + { + timeout: 10_000, + interval: 2_000, + timeoutMsg: "Variable value not updated", + } + ); + }); + + it("should revert overrides", async function () { + const section = (await getViewSection("BUNDLE VARIABLES")) as + | CustomTreeSection + | undefined; + assert(section); + await waitForTreeItems(section, 5_000); + + const action = await section.getAction( + "Reset bundle variables to default values" + ); + + assert(action); + await (await action.elem).click(); + + await browser.waitUntil( + async () => { + await assertVariableValue(section, "varWithDefault", { + value: "dev", + defaultValue: "default", + }); + return true; + }, + { + timeout: 10_000, + interval: 2_000, + timeoutMsg: "Variable value not updated", + } + ); + }); + + it("should update view if bundle changes", async function () { + schemaDef.targets!["dev_test"].variables!["varWithDefault"] = + "changed value in bundle"; + + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + + const section = (await getViewSection("BUNDLE VARIABLES")) as + | CustomTreeSection + | undefined; + assert(section); + await waitForTreeItems(section, 5_000); + + await browser.waitUntil( + async () => { + await assertVariableValue(section, "varWithDefault", { + value: "changed value in bundle", + defaultValue: "default", + }); + return true; + }, + { + timeout: 10_000, + interval: 2_000, + timeoutMsg: "Variable value not updated", + } + ); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/configure.e2e.ts b/packages/databricks-vscode/src/test/e2e/configure.e2e.ts deleted file mode 100644 index c33a1d997..000000000 --- a/packages/databricks-vscode/src/test/e2e/configure.e2e.ts +++ /dev/null @@ -1,198 +0,0 @@ -import assert from "node:assert"; -import path from "node:path"; -import * as fs from "fs/promises"; -import { - dismissNotifications, - getViewSection, - waitForTreeItems, -} from "./utils.ts"; -import { - CustomTreeSection, - InputBox, - sleep, - TreeItem, - Workbench, -} from "wdio-vscode-service"; -import {expect} from "chai"; - -describe("Configure Databricks Extension", async function () { - // this will be populated by the tests - let clusterId: string; - let projectDir: string; - let host: string; - let workbench: Workbench; - - this.timeout(3 * 60 * 1000); - - before(async function () { - assert( - process.env.TEST_DEFAULT_CLUSTER_ID, - "TEST_DEFAULT_CLUSTER_ID env var doesn't exist" - ); - assert( - process.env.WORKSPACE_PATH, - "WORKSPACE_PATH env var doesn't exist" - ); - assert( - process.env.DATABRICKS_HOST, - "DATABRICKS_HOST env var doesn't exist" - ); - clusterId = process.env.TEST_DEFAULT_CLUSTER_ID; - projectDir = process.env.WORKSPACE_PATH; - host = process.env.DATABRICKS_HOST; - workbench = await browser.getWorkbench(); - await dismissNotifications(); - }); - - it("should open VSCode", async function () { - const title = await workbench.getTitleBar().getTitle(); - assert(title.indexOf("[Extension Development Host]") >= 0); - }); - - it("should dismiss notifications", async function () { - //Collect all notifications - sleep(2000); - const notifications = await workbench.getNotifications(); - for (const n of notifications) { - await n.dismiss(); - } - }); - - it("should wait for quickstart", async () => { - const section = await getViewSection("CONFIGURATION"); - assert(section); - const welcome = await section.findWelcomeContent(); - assert(welcome); - await browser.waitUntil( - async () => { - return ( - ( - await ( - await workbench.getEditorView().getEditorGroup(0) - ).getOpenTabs() - ).findIndex(async (value) => { - return (await value.getTitle()).includes( - "DATABRICKS.quickstart.md" - ); - }) !== -1 - ); - }, - {timeout: 10_000} - ); - - //Wait for quickstart text to be visible. - sleep(2000); - }); - - it("should open databricks panel and login", async function () { - const section = await getViewSection("CONFIGURATION"); - assert(section); - const welcome = await section.findWelcomeContent(); - assert(welcome); - const buttons = await welcome.getButtons(); - assert(buttons); - assert(buttons.length > 0); - - let input: InputBox | undefined; - await browser.waitUntil( - async () => { - await (await buttons[0].elem).click(); - - input = await new InputBox(workbench.locatorMap).wait(); - return input !== undefined; - }, - {timeout: 3000, interval: 500} - ); - - assert(input !== undefined); - while (await input.hasProgress()) { - await sleep(500); - } - - await input.confirm(); - await sleep(1000); - - input = await new InputBox(workbench.locatorMap).wait(); - while (await input.hasProgress()) { - await sleep(500); - } - - await input.selectQuickPick("DEFAULT"); - - assert(await waitForTreeItems(section, 10_000)); - }); - - it("should attach cluster", async function () { - const config = await getViewSection("CONFIGURATION"); - assert(config); - const configTree = config as CustomTreeSection; - - assert(await waitForTreeItems(configTree)); - - const configItems = await configTree.getVisibleItems(); - - let clusterConfigItem: TreeItem | undefined; - for (const i of configItems) { - const label = await i.getLabel(); - if (label.startsWith("Cluster")) { - clusterConfigItem = i; - break; - } - } - assert(clusterConfigItem); - - const buttons = await ( - clusterConfigItem as TreeItem - ).getActionButtons(); - - const configureButton = buttons.filter((b) => { - return b.getLabel() === "Configure cluster"; - })[0]; - assert(configureButton); - - await configureButton.elem.click(); - - const input = await new InputBox(workbench.locatorMap).wait(); - await sleep(200); - - await input.setText(clusterId); - await sleep(500); - await input.confirm(); - - // wait for tree to update - let clusterPropsItems; - do { - await sleep(200); - clusterPropsItems = await clusterConfigItem.getChildren(); - } while (clusterPropsItems.length <= 1); - - // get cluster ID - const clusterProps: Record = {}; - for (const i of clusterPropsItems) { - clusterProps[await i.getLabel()] = (await i.getDescription()) || ""; - } - - const testClusterId = clusterProps["Cluster ID"]; - assert.equal(testClusterId, clusterId); - }); - - it("should write the project config file", async function () { - const projectConfig = JSON.parse( - await fs.readFile( - path.join(projectDir, ".databricks", "project.json"), - "utf-8" - ) - ); - - const expectedHost = new URL( - host.startsWith("https") ? host : `https://${host}` - ).toString(); - - expect(projectConfig).to.include({ - host: expectedHost, - authType: "profile", - profile: "DEFAULT", - clusterId, - }); - }); -}); diff --git a/packages/databricks-vscode/src/test/e2e/deploy_and_run_job.e2e.ts b/packages/databricks-vscode/src/test/e2e/deploy_and_run_job.e2e.ts new file mode 100644 index 000000000..f099c366b --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/deploy_and_run_job.e2e.ts @@ -0,0 +1,207 @@ +import assert from "node:assert"; +import { + dismissNotifications, + getUniqueResourceName, + getViewSection, + waitForLogin, + waitForTreeItems, +} from "./utils/commonUtils.ts"; +import {CustomTreeSection, Workbench} from "wdio-vscode-service"; +import { + getBasicBundleConfig, + getSimpleJobsResource, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; +import path from "node:path"; +import fs from "fs/promises"; +import {BundleSchema} from "../../bundle/types.ts"; +import {getJobViewItem} from "./utils/dabsExplorerUtils.ts"; +import {fileURLToPath} from "url"; + +/* eslint-disable @typescript-eslint/naming-convention */ +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); +/* eslint-enable @typescript-eslint/naming-convention */ + +describe("Deploy and run job", async function () { + let workbench: Workbench; + let resourceExplorerView: CustomTreeSection; + let vscodeWorkspaceRoot: string; + let jobName: string; + let clusterId: string; + + this.timeout(3 * 60 * 1000); + + async function createProjectWithJob() { + /** + * process.env.WORKSPACE_PATH (cwd) + * ├── databricks.yml + * └── src + * └── notebook.ipynb + */ + + const projectName = getUniqueResourceName("deploy_and_run_job"); + const notebookTaskName = getUniqueResourceName("notebook_task"); + /* eslint-disable @typescript-eslint/naming-convention */ + const jobDef = getSimpleJobsResource({ + tasks: [ + { + task_key: notebookTaskName, + notebook_task: { + notebook_path: "src/notebook.ipynb", + }, + existing_cluster_id: clusterId, + }, + ], + }); + jobName = jobDef.name!; + + const schemaDef: BundleSchema = getBasicBundleConfig({ + bundle: { + name: projectName, + deployment: {}, + }, + targets: { + dev_test: { + resources: { + jobs: { + vscode_integration_test: jobDef, + }, + }, + }, + }, + }); + /* eslint-enable @typescript-eslint/naming-convention */ + + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + + await fs.mkdir(path.join(vscodeWorkspaceRoot, "src"), { + recursive: true, + }); + await fs.copyFile( + path.join(__dirname, "resources", "spark_select_1.ipynb"), + path.join(vscodeWorkspaceRoot, "src", "notebook.ipynb") + ); + } + + before(async function () { + assert( + process.env.TEST_DEFAULT_CLUSTER_ID, + "TEST_DEFAULT_CLUSTER_ID env var doesn't exist" + ); + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + + clusterId = process.env.TEST_DEFAULT_CLUSTER_ID; + workbench = await browser.getWorkbench(); + vscodeWorkspaceRoot = process.env.WORKSPACE_PATH; + await createProjectWithJob(); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + it("should find resource explorer view", async function () { + const section = await getViewSection("BUNDLE RESOURCE EXPLORER"); + assert(section); + await waitForTreeItems(section, 20_000); + resourceExplorerView = section as CustomTreeSection; + }); + + it("should deploy and run the current job", async () => { + const outputView = await workbench.getBottomBar().openOutputView(); + await outputView.selectChannel("Databricks Bundle Logs"); + await outputView.clearText(); + + const jobItem = await getJobViewItem(resourceExplorerView, jobName); + assert(jobItem, `Job ${jobName} not found in resource explorer`); + + const deployAndRunButton = await jobItem.getActionButton( + "Deploy the bundle and run the resource" + ); + assert(deployAndRunButton, "Deploy and run button not found"); + await deployAndRunButton.elem.click(); + + console.log("Waiting for deployment to finish"); + // Wait for the deployment to finish + await browser.waitUntil( + async () => { + try { + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand( + "workbench.panel.output.focus" + ); + }); + const outputView = await workbench + .getBottomBar() + .openOutputView(); + + if ( + (await outputView.getCurrentChannel()) !== + "Databricks Bundle Logs" + ) { + await outputView.selectChannel( + "Databricks Bundle Logs" + ); + } + + const logs = (await outputView.getText()).join(""); + console.log(logs); + return ( + logs.includes("Bundle deployed successfully") && + logs.includes("Bundle configuration refreshed") + ); + } catch (e) { + return false; + } + }, + { + timeout: 60_000, + interval: 1_000, + timeoutMsg: + "Can't find 'Bundle deployed successfully' message in output channel", + } + ); + + console.log("Waiting for run to finish"); + // Wait for status to reach success + await browser.waitUntil( + async () => { + const jobItem = await getJobViewItem( + resourceExplorerView, + jobName + ); + if (jobItem === undefined) { + return false; + } + + const runStatusItem = await jobItem.findChildItem("Run Status"); + if (runStatusItem === undefined) { + return false; + } + + return (await runStatusItem.getDescription()) === "Success"; + }, + { + timeout: 120_000, + interval: 2_000, + timeoutMsg: + "The run status didn't reach success within 120 seconds", + } + ); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/destroy.e2e.ts b/packages/databricks-vscode/src/test/e2e/destroy.e2e.ts new file mode 100644 index 000000000..67c51fa38 --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/destroy.e2e.ts @@ -0,0 +1,243 @@ +import assert from "node:assert"; +import { + dismissNotifications, + getUniqueResourceName, + getViewSection, + waitForLogin, + waitForTreeItems, +} from "./utils/commonUtils.ts"; +import {Workbench} from "wdio-vscode-service"; +import { + getBasicBundleConfig, + getSimpleJobsResource, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; +import path from "node:path"; +import fs from "fs/promises"; +import {BundleSchema} from "../../bundle/types.ts"; +import {fileURLToPath} from "url"; +import {WorkspaceClient} from "@databricks/databricks-sdk"; + +/* eslint-disable @typescript-eslint/naming-convention */ +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); +/* eslint-enable @typescript-eslint/naming-convention */ + +describe("Deploy and destroy", async function () { + let workbench: Workbench; + let vscodeWorkspaceRoot: string; + let jobName: string; + let clusterId: string; + + this.timeout(3 * 60 * 1000); + + async function createProjectWithJob() { + /** + * process.env.WORKSPACE_PATH (cwd) + * ├── databricks.yml + * └── src + * └── notebook.ipynb + */ + + const projectName = getUniqueResourceName("deploy_and_destroy_bundle"); + const notebookTaskName = getUniqueResourceName("notebook_task"); + /* eslint-disable @typescript-eslint/naming-convention */ + const jobDef = getSimpleJobsResource({ + tasks: [ + { + task_key: notebookTaskName, + notebook_task: { + notebook_path: "src/notebook.ipynb", + }, + existing_cluster_id: clusterId, + }, + ], + }); + jobName = jobDef.name!; + + const schemaDef: BundleSchema = getBasicBundleConfig({ + bundle: { + name: projectName, + deployment: {}, + }, + targets: { + dev_test: { + resources: { + jobs: { + vscode_integration_test: jobDef, + }, + }, + }, + }, + }); + /* eslint-enable @typescript-eslint/naming-convention */ + + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + + await fs.mkdir(path.join(vscodeWorkspaceRoot, "src"), { + recursive: true, + }); + await fs.copyFile( + path.join(__dirname, "resources", "spark_select_1.ipynb"), + path.join(vscodeWorkspaceRoot, "src", "notebook.ipynb") + ); + } + + before(async function () { + assert( + process.env.TEST_DEFAULT_CLUSTER_ID, + "TEST_DEFAULT_CLUSTER_ID env var doesn't exist" + ); + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + + clusterId = process.env.TEST_DEFAULT_CLUSTER_ID; + workbench = await browser.getWorkbench(); + vscodeWorkspaceRoot = process.env.WORKSPACE_PATH; + await createProjectWithJob(); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + it("should find resource explorer view", async function () { + const section = await getViewSection("BUNDLE RESOURCE EXPLORER"); + assert(section); + await waitForTreeItems(section, 20_000); + }); + + it("should deploy and run the current job", async () => { + const wsClient = new WorkspaceClient({ + configFile: process.env.DATABRICKS_CONFIG_FILE, + profile: "DEFAULT", + }); + + const prefix = `[dev ${(await wsClient.currentUser.me()).userName + ?.split("@")[0] + .replaceAll(/[^a-zA-Z0-9]/g, "_")}]`; + + const outputView = await workbench.getBottomBar().openOutputView(); + await outputView.selectChannel("Databricks Bundle Logs"); + await outputView.clearText(); + + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand("databricks.bundle.deploy"); + }); + console.log("Waiting for deployment to finish"); + // Wait for the deployment to finish + await browser.waitUntil( + async () => { + try { + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand( + "workbench.panel.output.focus" + ); + }); + const outputView = await workbench + .getBottomBar() + .openOutputView(); + + if ( + (await outputView.getCurrentChannel()) !== + "Databricks Bundle Logs" + ) { + await outputView.selectChannel( + "Databricks Bundle Logs" + ); + } + + const logs = (await outputView.getText()).join(""); + console.log(logs); + return ( + logs.includes("Bundle deployed successfully") && + logs.includes("Bundle configuration refreshed") + ); + } catch (e) { + return false; + } + }, + { + timeout: 60_000, + interval: 1_000, + timeoutMsg: + "Can't find 'Bundle deployed successfully' message in output channel", + } + ); + + let found = false; + // eslint-disable-next-line @typescript-eslint/no-unused-vars + for await (const j of wsClient.jobs.list({ + name: `${prefix} ${jobName}`, + })) { + found = true; + } + assert(found, `Job ${jobName} not found in workspace`); + + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand("databricks.bundle.destroy"); + }); + console.log("Waiting for bundle to destroy"); + // Wait for status to reach success + await browser.waitUntil( + async () => { + try { + await browser.executeWorkbench(async (vscode) => { + await vscode.commands.executeCommand( + "workbench.panel.output.focus" + ); + }); + const outputView = await workbench + .getBottomBar() + .openOutputView(); + + if ( + (await outputView.getCurrentChannel()) !== + "Databricks Bundle Logs" + ) { + await outputView.selectChannel( + "Databricks Bundle Logs" + ); + } + + const logs = (await outputView.getText()).join(""); + console.log(logs); + return ( + logs.includes("Bundle destroyed successfully") && + logs.includes("Bundle configuration refreshed") + ); + } catch (e) { + return false; + } + }, + { + timeout: 120_000, + interval: 2_000, + timeoutMsg: + "The run status didn't reach success within 120 seconds", + } + ); + + found = false; + // eslint-disable-next-line @typescript-eslint/no-unused-vars + for await (const j of wsClient.jobs.list({ + name: `${prefix} ${jobName}`, + })) { + found = true; + } + assert(!found, `Job ${jobName} still found in workspace`); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/refresh_resource_explorer_on_yml_change.e2e.ts b/packages/databricks-vscode/src/test/e2e/refresh_resource_explorer_on_yml_change.e2e.ts new file mode 100644 index 000000000..1932696e1 --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/refresh_resource_explorer_on_yml_change.e2e.ts @@ -0,0 +1,169 @@ +import assert from "assert"; +import {CustomTreeSection} from "wdio-vscode-service"; +import { + dismissNotifications, + getUniqueResourceName, + getViewSection, + waitForLogin, +} from "./utils/commonUtils.ts"; +import fs from "fs/promises"; +import path from "path"; +import { + getBasicBundleConfig, + getSimpleJobsResource, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; +import {BundleSchema, BundleTarget, Resource} from "../../bundle/types"; +import {geTaskViewItem, getJobViewItem} from "./utils/dabsExplorerUtils.ts"; +import {fileURLToPath} from "url"; + +/* eslint-disable @typescript-eslint/naming-convention */ +const __filename = fileURLToPath(import.meta.url); +const __dirname = path.dirname(__filename); +/* eslint-enable @typescript-eslint/naming-convention */ + +describe("Automatically refresh resource explorer", async function () { + let vscodeWorkspaceRoot: string; + let projectName: string; + let resourceExplorerView: CustomTreeSection; + let clusterId: string; + let jobDef: Resource; + + this.timeout(3 * 60 * 1000); + + async function createProjectWithJob() { + /** + * process.env.WORKSPACE_PATH (cwd) + * ├── databricks.yml + * └── src + * └── notebook.ipynb + */ + + const notebookTaskName = getUniqueResourceName("notebook_task"); + /* eslint-disable @typescript-eslint/naming-convention */ + jobDef = getSimpleJobsResource({ + tasks: [ + { + task_key: notebookTaskName, + notebook_task: { + notebook_path: "src/notebook.ipynb", + }, + existing_cluster_id: clusterId, + }, + ], + }); + + const schemaDef: BundleSchema = getBasicBundleConfig({ + bundle: { + name: projectName, + deployment: {}, + }, + targets: { + dev_test: { + resources: { + jobs: { + vscode_integration_test: jobDef, + }, + }, + }, + }, + }); + /* eslint-enable @typescript-eslint/naming-convention */ + + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + + await fs.mkdir(path.join(vscodeWorkspaceRoot, "src"), { + recursive: true, + }); + await fs.copyFile( + path.join(__dirname, "resources", "spark_select_1.ipynb"), + path.join(vscodeWorkspaceRoot, "src", "notebook.ipynb") + ); + } + + before(async function () { + assert( + process.env.TEST_DEFAULT_CLUSTER_ID, + "TEST_DEFAULT_CLUSTER_ID env var doesn't exist" + ); + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + + clusterId = process.env.TEST_DEFAULT_CLUSTER_ID; + vscodeWorkspaceRoot = process.env.WORKSPACE_PATH!; + + const basicBundleConfig = getBasicBundleConfig(); + projectName = basicBundleConfig.bundle!.name!; + + await writeRootBundleConfig(basicBundleConfig, vscodeWorkspaceRoot); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + }); + + it("should find resource explorer view", async function () { + const section = await getViewSection("BUNDLE RESOURCE EXPLORER"); + assert(section); + resourceExplorerView = section as CustomTreeSection; + }); + + it("should pickup changes to jobs resource", async function () { + await resourceExplorerView.expand(); + const resourceExplorerItems = + await resourceExplorerView.getVisibleItems(); + assert( + resourceExplorerItems.length === 0, + `Resource explorer should be empty, found (${( + await Promise.all( + resourceExplorerItems.map((i) => i.getLabel()) + ) + ).join(", ")})` + ); + + const outputView = await (await browser.getWorkbench()) + .getBottomBar() + .openOutputView(); + await outputView.selectChannel("Databricks Bundle Logs"); + + await createProjectWithJob(); + + await browser.waitUntil( + async () => { + const job = await getJobViewItem( + resourceExplorerView, + jobDef.name! + ); + return job !== undefined; + }, + { + timeout: 20_000, + interval: 2_000, + timeoutMsg: `Job view item with name ${jobDef.name} not found`, + } + ); + + for (const task of jobDef.tasks!) { + assert( + await geTaskViewItem( + resourceExplorerView, + jobDef.name!, + task.task_key! + ), + `Task view item with name ${task.task_key} not found` + ); + } + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/resources/requirements.txt b/packages/databricks-vscode/src/test/e2e/resources/requirements.txt new file mode 100644 index 000000000..e17a00b5c --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/resources/requirements.txt @@ -0,0 +1,3 @@ +# Taken from https://github.com/databricks/cli/blob/main/libs/template/templates/default-python/template/%7B%7B.project_name%7D%7D/requirements-dev.txt.tmpl +setuptools +wheel diff --git a/packages/databricks-vscode/src/test/e2e/resources/spark_select_1.ipynb b/packages/databricks-vscode/src/test/e2e/resources/spark_select_1.ipynb new file mode 100644 index 000000000..a58605b6e --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/resources/spark_select_1.ipynb @@ -0,0 +1,20 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "spark.sql(\"SELECT 1\")" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/packages/databricks-vscode/src/test/e2e/run_files.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_files.e2e.ts new file mode 100644 index 000000000..b9eb2873b --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/run_files.e2e.ts @@ -0,0 +1,97 @@ +import path from "node:path"; +import * as fs from "fs/promises"; +import assert from "node:assert"; +import { + dismissNotifications, + executeCommandWhenAvailable, + openFile, + waitForLogin, + waitForWorkflowWebview, +} from "./utils/commonUtils.ts"; +import {sleep} from "wdio-vscode-service"; +import { + getBasicBundleConfig, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; + +describe("Run files", async function () { + let projectDir: string; + this.timeout(3 * 60 * 1000); + + before(async () => { + assert(process.env.WORKSPACE_PATH, "WORKSPACE_PATH doesn't exist"); + + projectDir = process.env.WORKSPACE_PATH; + + await fs.writeFile( + path.join(projectDir, "lib.py"), + [ + "def func(spark):", + `\tspark.sql('SELECT "hello world"').show()`, + ].join("\n") + ); + const nestedDir = path.join(projectDir, "nested"); + await fs.mkdir(nestedDir, {recursive: true}); + await fs.writeFile( + path.join(nestedDir, "hello.py"), + [`from lib import func`, "func(spark)"].join("\n") + ); + + await writeRootBundleConfig(getBasicBundleConfig(), projectDir); + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + beforeEach(async () => { + await openFile("hello.py"); + }); + + it("should cancel a run during deployment", async () => { + const workbench = await driver.getWorkbench(); + await executeCommandWhenAvailable("Databricks: Upload and Run File"); + await browser.waitUntil(async () => { + const notifications = await workbench.getNotifications(); + for (const notification of notifications) { + const message = await notification.getMessage(); + if (message.includes("Uploading bundle assets")) { + await notification.takeAction("Cancel"); + return true; + } + } + return false; + }); + const debugOutput = await workbench + .getBottomBar() + .openDebugConsoleView(); + while (true) { + const text = await (await debugOutput.elem).getHTML(); + if (text && text.includes("Cancelled")) { + break; + } else { + await sleep(2000); + } + } + }); + + it("should run a python file on a cluster", async () => { + const workbench = await driver.getWorkbench(); + await executeCommandWhenAvailable("Databricks: Upload and Run File"); + + const debugOutput = await workbench + .getBottomBar() + .openDebugConsoleView(); + + while (true) { + await sleep(2000); + const text = await (await debugOutput.elem).getHTML(); + if (text && text.includes("hello world")) { + break; + } + } + }); + + it("should run a python file as a workflow", async () => { + await executeCommandWhenAvailable("Databricks: Run File as Workflow"); + await waitForWorkflowWebview("hello world"); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_repo.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_repo.e2e.ts deleted file mode 100644 index f5da1099c..000000000 --- a/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_repo.e2e.ts +++ /dev/null @@ -1,221 +0,0 @@ -import path from "node:path"; -import * as fs from "fs/promises"; -import assert from "node:assert"; -import { - dismissNotifications, - getViewSection, - startSyncIfStopped, - waitForSyncComplete, - waitForTreeItems, -} from "./utils.ts"; -import {sleep} from "wdio-vscode-service"; - -describe("Run job on cluster with repo", async function () { - let projectDir: string; - this.timeout(2 * 60 * 1000); - - before(async () => { - assert(process.env.TEST_DEFAULT_CLUSTER_ID); - assert(process.env.TEST_REPO_PATH); - assert(process.env.WORKSPACE_PATH); - projectDir = process.env.WORKSPACE_PATH; - - await fs.mkdir(path.join(projectDir, ".databricks"), { - recursive: true, - }); - - await fs.mkdir(path.join(projectDir, ".vscode"), { - recursive: true, - }); - await fs.writeFile( - path.join(projectDir, ".vscode", "settings.json"), - JSON.stringify({ - // eslint-disable-next-line @typescript-eslint/naming-convention - "databricks.sync.destinationType": "repo", - }) - ); - - await fs.writeFile( - path.join(projectDir, ".databricks", "project.json"), - JSON.stringify({ - clusterId: process.env["TEST_DEFAULT_CLUSTER_ID"], - profile: "DEFAULT", - workspacePath: process.env["TEST_REPO_PATH"], - }) - ); - await fs.writeFile( - path.join(projectDir, "file.py"), - `spark.sql('SELECT "hello world"').show()` - ); - - await fs.mkdir(path.join(projectDir, "a", "b c"), { - recursive: true, - }); - - await fs.writeFile( - path.join(projectDir, "a", "b c", "notebook.py"), - [ - "# Databricks notebook source", - `spark.sql('SELECT "hello world"').show()`, - "# COMMAND ----------", - "# MAGIC %sh pwd", - ].join("\n") - ); - - const section = await getViewSection("CONFIGURATION"); - assert(section); - await waitForTreeItems(section); - await dismissNotifications(); - }); - - it("should run a python notebook as a job on a cluster", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(200); - await input.setText("notebook.py"); - await input.confirm(); - await sleep(500); - - // run file - await workbench.executeQuickPick( - "Databricks: Run File as Workflow on Databricks" - ); - - await dismissNotifications(); - const webView = await workbench.getWebviewByTitle(/Databricks Job Run/); - await webView.open(); - - /* eslint-disable @typescript-eslint/naming-convention */ - const labelToDefaults = { - taskRunId: {label: "task-run-id", default: /N\\A/}, - clusterId: {label: "cluster", default: /N\\A/}, - startTime: {label: "run-start-time", default: /-/}, - endTime: {label: "run-end-time", default: /-/}, - duration: {label: "run-duration", default: /-/}, - status: {label: "run-status", default: /Synchronizing/}, - }; - /* eslint-enable @typescript-eslint/naming-convention */ - - // wait for job to get a task id - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel( - labelToDefaults.taskRunId.label - ) - ).match(labelToDefaults.taskRunId.default) === null, - { - timeoutMsg: "Job did not start", - } - ); - - expect( - await browser.getTextByLabel(labelToDefaults.startTime.label) - ).not.toHaveText(labelToDefaults.startTime.default); - - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel(labelToDefaults.status.label) - ).match(/Succeeded/) !== null, - { - timeout: 30000, - interval: 100, - timeoutMsg: "Job did not reach succeeded status after 30s.", - } - ); - - const iframe = browser.$("#frame"); - browser.switchToFrame(iframe); - - const iframeRoot = await browser.$("html"); - expect(iframeRoot).toHaveTextContaining(/a\/b c$/); - - browser.switchToParentFrame(); - - webView.close(); - }); - - it("should run a python file as a job on a cluster", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(200); - await input.setText("file.py"); - await input.confirm(); - await sleep(500); - - // run file - await workbench.executeQuickPick( - "Databricks: Run File as Workflow on Databricks" - ); - - await dismissNotifications(); - const webView = await workbench.getWebviewByTitle(/Databricks Job Run/); - await webView.open(); - - /* eslint-disable @typescript-eslint/naming-convention */ - const labelToDefaults = { - taskRunId: {label: "task-run-id", default: /N\\A/}, - clusterId: {label: "cluster", default: /N\\A/}, - startTime: {label: "run-start-time", default: /-/}, - endTime: {label: "run-end-time", default: /-/}, - duration: {label: "run-duration", default: /-/}, - status: {label: "run-status", default: /Synchronizing/}, - }; - /* eslint-enable @typescript-eslint/naming-convention */ - - // wait for job to get a task id - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel( - labelToDefaults.taskRunId.label - ) - ).match(labelToDefaults.taskRunId.default) === null, - { - timeoutMsg: "Job did not start", - } - ); - - expect( - await browser.getTextByLabel(labelToDefaults.startTime.label) - ).not.toHaveText(labelToDefaults.startTime.default); - - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel(labelToDefaults.status.label) - ).includes("Succeeded"), - { - timeout: 30000, - interval: 100, - timeoutMsg: "Job did not reach succeeded status after 30s.", - } - ); - - webView.close(); - }); - - after(async () => { - try { - await fs.rm(path.join(projectDir, ".vscode"), { - recursive: true, - force: true, - }); - } catch {} - }); -}); diff --git a/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_workspace.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_workspace.e2e.ts deleted file mode 100644 index 6c81f10df..000000000 --- a/packages/databricks-vscode/src/test/e2e/run_job_on_cluster_with_workspace.e2e.ts +++ /dev/null @@ -1,311 +0,0 @@ -/* eslint-disable @typescript-eslint/naming-convention */ -import path from "node:path"; -import * as fs from "fs/promises"; -import assert from "node:assert"; -import { - dismissNotifications, - getViewSection, - startSyncIfStopped, - waitForSyncComplete, - waitForTreeItems, -} from "./utils.ts"; -import {sleep} from "wdio-vscode-service"; - -describe("Run job on cluster with workspace", async function () { - let projectDir: string; - this.timeout(2 * 60 * 1000); - - before(async () => { - assert(process.env.TEST_DEFAULT_CLUSTER_ID); - assert(process.env.TEST_WORKSPACE_FOLDER_PATH); - assert(process.env.WORKSPACE_PATH); - projectDir = process.env.WORKSPACE_PATH; - - await fs.mkdir(path.join(projectDir, ".databricks"), { - recursive: true, - }); - - await fs.mkdir(path.join(projectDir, ".vscode"), { - recursive: true, - }); - await fs.writeFile( - path.join(projectDir, ".vscode", "settings.json"), - JSON.stringify({ - // eslint-disable-next-line @typescript-eslint/naming-convention - "databricks.sync.destinationType": "workspace", - }) - ); - - await fs.writeFile( - path.join(projectDir, ".databricks", "project.json"), - JSON.stringify({ - clusterId: process.env["TEST_DEFAULT_CLUSTER_ID"], - profile: "DEFAULT", - workspacePath: process.env["TEST_WORKSPACE_FOLDER_PATH"], - }) - ); - await fs.writeFile( - path.join(projectDir, "file.py"), - `spark.sql('SELECT "hello world"').show()` - ); - - await fs.mkdir(path.join(projectDir, "a", "b c"), { - recursive: true, - }); - - await fs.writeFile( - path.join(projectDir, "a", "b c", "notebook.py"), - [ - "# Databricks notebook source", - `spark.sql('SELECT "hello world"').show()`, - "# COMMAND ----------", - "# MAGIC %sh pwd", - ].join("\n") - ); - - await fs.writeFile( - path.join(projectDir, "notebook_ipynb.ipynb"), - JSON.stringify({ - cells: [ - { - cell_type: "code", - execution_count: null, - metadata: {}, - outputs: [], - source: ['print("hello")'], - }, - ], - metadata: { - kernelspec: { - display_name: "Python 3", - language: "python", - name: "python3", - }, - orig_nbformat: 4, - }, - nbformat: 4, - nbformat_minor: 2, - }) - ); - const section = await getViewSection("CONFIGURATION"); - assert(section); - await waitForTreeItems(section); - await dismissNotifications(); - }); - - it("should run a python notebook as a job on a cluster", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(200); - await input.setText("notebook.py"); - await input.confirm(); - await sleep(500); - - // run file - await workbench.executeQuickPick( - "Databricks: Run File as Workflow on Databricks" - ); - - await dismissNotifications(); - const webView = await workbench.getWebviewByTitle(/Databricks Job Run/); - await webView.open(); - - /* eslint-disable @typescript-eslint/naming-convention */ - const labelToDefaults = { - taskRunId: {label: "task-run-id", default: /N\\A/}, - clusterId: {label: "cluster", default: /N\\A/}, - startTime: {label: "run-start-time", default: /-/}, - endTime: {label: "run-end-time", default: /-/}, - duration: {label: "run-duration", default: /-/}, - status: {label: "run-status", default: /Synchronizing/}, - }; - /* eslint-enable @typescript-eslint/naming-convention */ - - // wait for job to get a task id - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel( - labelToDefaults.taskRunId.label - ) - ).match(labelToDefaults.taskRunId.default) === null, - { - timeoutMsg: "Job did not start", - } - ); - - expect( - await browser.getTextByLabel(labelToDefaults.startTime.label) - ).not.toHaveText(labelToDefaults.startTime.default); - - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel(labelToDefaults.status.label) - ).match(/Succeeded/) !== null, - { - timeout: 30000, - interval: 100, - timeoutMsg: "Job did not reach succeeded status after 30s.", - } - ); - - const iframe = browser.$("#frame"); - browser.switchToFrame(iframe); - - const iframeRoot = await browser.$("html"); - expect(iframeRoot).toHaveTextContaining(/a\/b c$/); - - browser.switchToParentFrame(); - webView.close(); - }); - - it("should run a jupyter notebook as a job on a cluster", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(200); - await input.setText("notebook_ipynb.ipynb"); - await input.confirm(); - await sleep(500); - - // run file - await workbench.executeQuickPick( - "Databricks: Run File as Workflow on Databricks" - ); - - await dismissNotifications(); - const webView = await workbench.getWebviewByTitle(/Databricks Job Run/); - await webView.open(); - - /* eslint-disable @typescript-eslint/naming-convention */ - const labelToDefaults = { - taskRunId: {label: "task-run-id", default: /N\\A/}, - clusterId: {label: "cluster", default: /N\\A/}, - startTime: {label: "run-start-time", default: /-/}, - endTime: {label: "run-end-time", default: /-/}, - duration: {label: "run-duration", default: /-/}, - status: {label: "run-status", default: /Synchronizing/}, - }; - /* eslint-enable @typescript-eslint/naming-convention */ - - // wait for job to get a task id - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel( - labelToDefaults.taskRunId.label - ) - ).match(labelToDefaults.taskRunId.default) === null, - { - timeoutMsg: "Job did not start", - } - ); - - expect( - await browser.getTextByLabel(labelToDefaults.startTime.label) - ).not.toHaveText(labelToDefaults.startTime.default); - - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel(labelToDefaults.status.label) - ).match(/Succeeded/) !== null, - { - timeout: 30000, - interval: 100, - timeoutMsg: "Job did not reach succeeded status after 30s.", - } - ); - - webView.close(); - }); - it("should run a python file as a job on a cluster", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(200); - await input.setText("file.py"); - await input.confirm(); - await sleep(500); - - // run file - await workbench.executeQuickPick( - "Databricks: Run File as Workflow on Databricks" - ); - - await dismissNotifications(); - const webView = await workbench.getWebviewByTitle(/Databricks Job Run/); - await webView.open(); - - /* eslint-disable @typescript-eslint/naming-convention */ - const labelToDefaults = { - taskRunId: {label: "task-run-id", default: /N\\A/}, - clusterId: {label: "cluster", default: /N\\A/}, - startTime: {label: "run-start-time", default: /-/}, - endTime: {label: "run-end-time", default: /-/}, - duration: {label: "run-duration", default: /-/}, - status: {label: "run-status", default: /Synchronizing/}, - }; - /* eslint-enable @typescript-eslint/naming-convention */ - - // wait for job to get a task id - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel( - labelToDefaults.taskRunId.label - ) - ).match(labelToDefaults.taskRunId.default) === null, - { - timeoutMsg: "Job did not start", - } - ); - - expect( - await browser.getTextByLabel(labelToDefaults.startTime.label) - ).not.toHaveText(labelToDefaults.startTime.default); - - await browser.waitUntil( - async () => - ( - await browser.getTextByLabel(labelToDefaults.status.label) - ).includes("Succeeded"), - { - timeout: 30000, - interval: 100, - timeoutMsg: "Job did not reach succeeded status after 30s.", - } - ); - - webView.close(); - }); - - after(async () => { - try { - await fs.rm(path.join(projectDir, ".vscode"), { - recursive: true, - force: true, - }); - } catch {} - }); -}); diff --git a/packages/databricks-vscode/src/test/e2e/run_notebooks.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_notebooks.e2e.ts new file mode 100644 index 000000000..d6e1186d7 --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/run_notebooks.e2e.ts @@ -0,0 +1,86 @@ +import path from "node:path"; +import * as fs from "fs/promises"; +import assert from "node:assert"; +import { + dismissNotifications, + executeCommandWhenAvailable, + openFile, + waitForLogin, + waitForWorkflowWebview, +} from "./utils/commonUtils.ts"; +import { + getBasicBundleConfig, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; + +describe("Run notebooks", async function () { + let projectDir: string; + this.timeout(3 * 60 * 1000); + + before(async () => { + assert(process.env.WORKSPACE_PATH); + projectDir = process.env.WORKSPACE_PATH; + + await fs.writeFile( + path.join(projectDir, "lib.py"), + [ + "def func(spark):", + `\tspark.sql('SELECT "hello world"').show()`, + ].join("\n") + ); + await fs.mkdir(path.join(projectDir, "a", "b c"), { + recursive: true, + }); + await fs.writeFile( + path.join(projectDir, "a", "b c", "notebook.py"), + [ + "# Databricks notebook source", + `spark.sql('SELECT "hello world"').show()`, + "# COMMAND ----------", + "# MAGIC %sh pwd", + ].join("\n") + ); + await fs.writeFile( + path.join(projectDir, "notebook.ipynb"), + JSON.stringify({ + /* eslint-disable @typescript-eslint/naming-convention */ + cells: [ + { + cell_type: "code", + execution_count: null, + metadata: {}, + outputs: [], + source: [`from lib import func`, "func(spark)"], + }, + ], + metadata: { + kernelspec: { + display_name: "Python 3", + language: "python", + name: "python3", + }, + orig_nbformat: 4, + }, + nbformat: 4, + nbformat_minor: 2, + /* eslint-enable @typescript-eslint/naming-convention */ + }) + ); + + await writeRootBundleConfig(getBasicBundleConfig(), projectDir); + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + it("should run a notebook.py file as a workflow", async () => { + await openFile("notebook.py"); + await executeCommandWhenAvailable("Databricks: Run File as Workflow"); + await waitForWorkflowWebview("a/b c"); + }); + + it("should run a notebook.ipynb file as a workflow", async () => { + await openFile("notebook.ipynb"); + await executeCommandWhenAvailable("Databricks: Run File as Workflow"); + await waitForWorkflowWebview("hello world"); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_repo.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_repo.e2e.ts deleted file mode 100644 index 45dd291a3..000000000 --- a/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_repo.e2e.ts +++ /dev/null @@ -1,123 +0,0 @@ -import path from "node:path"; -import * as fs from "fs/promises"; -import assert from "node:assert"; -import { - dismissNotifications, - getViewSection, - startSyncIfStopped, - waitForSyncComplete, - waitForTreeItems, -} from "./utils.ts"; -import {sleep} from "wdio-vscode-service"; - -describe("Run python on cluster with repo", async function () { - let projectDir: string; - this.timeout(3 * 60 * 1000); - - before(async () => { - assert(process.env.DATABRICKS_HOST); - assert(process.env.TEST_DEFAULT_CLUSTER_ID); - assert(process.env.TEST_REPO_PATH); - assert(process.env.WORKSPACE_PATH); - projectDir = process.env.WORKSPACE_PATH; - - await fs.mkdir(path.join(projectDir, ".databricks"), { - recursive: true, - }); - - await fs.mkdir(path.join(projectDir, ".vscode"), { - recursive: true, - }); - await fs.writeFile( - path.join(projectDir, ".vscode", "settings.json"), - JSON.stringify({ - // eslint-disable-next-line @typescript-eslint/naming-convention - "databricks.sync.destinationType": "repo", - }) - ); - - await fs.writeFile( - path.join(projectDir, ".databricks", "project.json"), - JSON.stringify({ - host: process.env["DATABRICKS_HOST"], - authType: "profile", - profile: "DEFAULT", - clusterId: process.env["TEST_DEFAULT_CLUSTER_ID"], - workspacePath: process.env["TEST_REPO_PATH"], - }) - ); - await fs.mkdir(path.join(projectDir, "nested"), {recursive: true}); - await fs.writeFile( - path.join(projectDir, "nested", "hello.py"), - [`from lib import func`, "func(spark)"].join("\n") - ); - - await fs.writeFile( - path.join(projectDir, "lib.py"), - [ - "def func(spark):", - `\tspark.sql('SELECT "hello world"').show()`, - ].join("\n") - ); - await dismissNotifications(); - }); - - it("should connect to Databricks", async () => { - const section = await getViewSection("CONFIGURATION"); - assert(section); - await waitForTreeItems(section); - }); - - it("should start syncing", async () => { - const workbench = await driver.getWorkbench(); - - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - await workbench.executeCommand( - "Databricks: Start synchronization (full sync)" - ); - - await startSyncIfStopped(); - await waitForSyncComplete(); - }); - - it("should run a python file on a cluster", async () => { - const workbench = await driver.getWorkbench(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(1000); - await input.setText("hello.py"); - await input.confirm(); - await sleep(1000); - - // run file - await workbench.executeQuickPick( - "Databricks: Upload and Run File on Databricks" - ); - - const debugOutput = await workbench - .getBottomBar() - .openDebugConsoleView(); - - while (true) { - // dismiss by message - await dismissNotifications(); - await sleep(2000); - const text = await (await debugOutput.elem).getHTML(); - if (text && text.includes("hello world")) { - break; - } - } - }); - - after(async () => { - try { - await fs.rm(path.join(projectDir, ".vscode"), { - recursive: true, - force: true, - }); - } catch {} - }); -}); diff --git a/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_workspace.e2e.ts b/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_workspace.e2e.ts deleted file mode 100644 index 94c689dbd..000000000 --- a/packages/databricks-vscode/src/test/e2e/run_on_cluster_with_workspace.e2e.ts +++ /dev/null @@ -1,120 +0,0 @@ -import path from "node:path"; -import * as fs from "fs/promises"; -import assert from "node:assert"; -import { - dismissNotifications, - getViewSection, - startSyncIfStopped, - waitForSyncComplete, - waitForTreeItems, -} from "./utils.ts"; -import {sleep} from "wdio-vscode-service"; - -describe("Run python on cluster with workspace", async function () { - let projectDir: string; - this.timeout(3 * 60 * 1000); - - before(async () => { - assert(process.env.DATABRICKS_HOST); - assert(process.env.TEST_DEFAULT_CLUSTER_ID); - assert(process.env.TEST_WORKSPACE_FOLDER_PATH); - assert(process.env.WORKSPACE_PATH); - projectDir = process.env.WORKSPACE_PATH; - - await fs.mkdir(path.join(projectDir, ".databricks"), { - recursive: true, - }); - - await fs.mkdir(path.join(projectDir, ".vscode"), { - recursive: true, - }); - await fs.writeFile( - path.join(projectDir, ".vscode", "settings.json"), - JSON.stringify({ - // eslint-disable-next-line @typescript-eslint/naming-convention - "databricks.sync.destinationType": "workspace", - }) - ); - - await ( - await driver.getWorkbench() - ).executeCommand("Developer: Reload Window"); - - await fs.writeFile( - path.join(projectDir, ".databricks", "project.json"), - JSON.stringify({ - host: process.env["DATABRICKS_HOST"], - authType: "profile", - profile: "DEFAULT", - clusterId: process.env["TEST_DEFAULT_CLUSTER_ID"], - workspacePath: process.env["TEST_WORKSPACE_FOLDER_PATH"], - }) - ); - await fs.mkdir(path.join(projectDir, "nested"), {recursive: true}); - await fs.writeFile( - path.join(projectDir, "nested", "hello.py"), - [`from lib import func`, "func(spark)"].join("\n") - ); - - await fs.writeFile( - path.join(projectDir, "lib.py"), - [ - "def func(spark):", - `\tspark.sql('SELECT "hello world"').show()`, - ].join("\n") - ); - await dismissNotifications(); - }); - - it("should connect to Databricks", async () => { - const section = await getViewSection("CONFIGURATION"); - assert(section); - await waitForTreeItems(section); - }); - - it("should start syncing", async () => { - await startSyncIfStopped(); - await waitForSyncComplete(); - }); - - it("should run a python file on a cluster", async () => { - const workbench = await driver.getWorkbench(); - const editorView = workbench.getEditorView(); - await editorView.closeAllEditors(); - - // open file - const input = await workbench.openCommandPrompt(); - await sleep(1000); - await input.setText("hello.py"); - await input.confirm(); - await sleep(1000); - - // run file - await workbench.executeQuickPick( - "Databricks: Upload and Run File on Databricks" - ); - - const debugOutput = await workbench - .getBottomBar() - .openDebugConsoleView(); - - while (true) { - // dismiss by message - await dismissNotifications(); - await sleep(2000); - const text = await (await debugOutput.elem).getHTML(); - if (text && text.includes("hello world")) { - break; - } - } - }); - - after(async () => { - try { - await fs.rm(path.join(projectDir, ".vscode"), { - recursive: true, - force: true, - }); - } catch {} - }); -}); diff --git a/packages/databricks-vscode/src/test/e2e/sync.e2e.ts b/packages/databricks-vscode/src/test/e2e/sync.e2e.ts new file mode 100644 index 000000000..47cd41d37 --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/sync.e2e.ts @@ -0,0 +1,139 @@ +import assert from "node:assert"; +import { + dismissNotifications, + getUniqueResourceName, + getViewSection, + waitForLogin, + waitForSyncComplete, +} from "./utils/commonUtils.ts"; +import { + getBasicBundleConfig, + writeRootBundleConfig, +} from "./utils/dabsFixtures.ts"; +import path from "node:path"; +import fs from "fs/promises"; +import {BundleSchema} from "../../bundle/types.ts"; +import {WorkspaceClient} from "@databricks/databricks-sdk"; + +describe("Sync", async function () { + let vscodeWorkspaceRoot: string; + let workspaceClient: WorkspaceClient; + let projectName: string; + + this.timeout(3 * 60 * 1000); + + async function createProject() { + /** + * process.env.WORKSPACE_PATH (cwd) + * ├── databricks.yml + * └── src + * └── notebook.py + */ + + projectName = getUniqueResourceName("sync"); + /* eslint-disable @typescript-eslint/naming-convention */ + + const schemaDef: BundleSchema = getBasicBundleConfig({ + bundle: { + name: projectName, + deployment: {}, + }, + targets: { + dev_test: { + default: true, + mode: "development", + workspace: { + root_path: + "/Users/${workspace.current_user.userName}/vscode-integration-test/${bundle.name}", + }, + }, + }, + }); + /* eslint-enable @typescript-eslint/naming-convention */ + + await writeRootBundleConfig(schemaDef, vscodeWorkspaceRoot); + + await fs.mkdir(path.join(vscodeWorkspaceRoot, "src"), { + recursive: true, + }); + } + + before(async function () { + assert( + process.env.WORKSPACE_PATH, + "WORKSPACE_PATH env var doesn't exist" + ); + assert( + process.env.DATABRICKS_HOST, + "DATABRICKS_HOST env var doesn't exist" + ); + assert( + process.env.DATABRICKS_TOKEN, + "DATABRICKS_TOKEN env var doesn't exist" + ); + + vscodeWorkspaceRoot = process.env.WORKSPACE_PATH; + workspaceClient = new WorkspaceClient({ + host: process.env.DATABRICKS_HOST, + token: process.env.DATABRICKS_TOKEN, + }); + await createProject(); + await dismissNotifications(); + }); + + it("should wait for extension activation", async () => { + const section = await getViewSection("CONFIGURATION"); + assert(section); + }); + + it("should wait for connection", async () => { + await waitForLogin("DEFAULT"); + await dismissNotifications(); + }); + + it("should sync files", async () => { + await browser.executeWorkbench((vscode) => { + vscode.commands.executeCommand("databricks.sync.start"); + }); + + const notebookContent = "print('original content')"; + await fs.writeFile( + path.join(vscodeWorkspaceRoot, "src", "notebook.py"), + notebookContent + ); + + await waitForSyncComplete(); + + const userName = (await workspaceClient.currentUser.me()).userName; + const workspacePath = `/Users/${userName}/vscode-integration-test/${projectName}/files/src/notebook.py`; + const file = await workspaceClient.workspace.export({ + path: workspacePath, + }); + + assert(file.content); + assert.strictEqual(atob(file.content), notebookContent); + }); + + it("should watch for file changes and sync changed files", async () => { + const newNotebookContent = "print('Hello, World!')"; + await fs.writeFile( + path.join(vscodeWorkspaceRoot, "src", "notebook.py"), + newNotebookContent + ); + + await browser.executeWorkbench((vscode) => { + vscode.commands.executeCommand("workbench.action.files.saveAll"); + }); + + await waitForSyncComplete(); + + const userName = (await workspaceClient.currentUser.me()).userName; + const workspacePath = `/Users/${userName}/vscode-integration-test/${projectName}/files/src/notebook.py`; + const file = await workspaceClient.workspace.export({ + path: workspacePath, + }); + + assert(file.content); + assert.strictEqual(atob(file.content), newNotebookContent); + }); +}); diff --git a/packages/databricks-vscode/src/test/e2e/utils.ts b/packages/databricks-vscode/src/test/e2e/utils.ts deleted file mode 100644 index 0b1645005..000000000 --- a/packages/databricks-vscode/src/test/e2e/utils.ts +++ /dev/null @@ -1,206 +0,0 @@ -import assert from "node:assert"; -import { - CustomTreeSection, - sleep, - TreeItem, - ViewControl, - ViewSection, -} from "wdio-vscode-service"; - -// eslint-disable-next-line @typescript-eslint/naming-convention -const ViewSectionTypes = [ - "CLUSTERS", - "CONFIGURATION", - "WORKSPACE EXPLORER", -] as const; -export type ViewSectionType = (typeof ViewSectionTypes)[number]; - -export async function findViewSection(name: ViewSectionType) { - const workbench = await browser.getWorkbench(); - - let control: ViewControl | undefined; - await browser.waitUntil( - async () => { - control = await workbench - .getActivityBar() - .getViewControl("Databricks"); - if (!control) { - return false; - } - return true; - }, - { - timeout: 10 * 1000, - interval: 1 * 1000, - timeoutMsg: `Can't find view control "${name}"`, - } - ); - const views = - (await (await control?.openView())?.getContent()?.getSections()) ?? []; - for (const v of views) { - if ((await v.getTitle()).toUpperCase() === name) { - return v; - } - } -} - -export async function getViewSection( - name: ViewSectionType -): Promise { - const section = await findViewSection(name); - assert(section); - - for (const s of ViewSectionTypes) { - if (s !== name) { - await (await findViewSection(s))?.collapse(); - } - } - - await section.expand(); - await (await section.elem).click(); - return section; -} - -export async function getViewSubSection( - section: ViewSectionType, - subSection: string -): Promise { - for (const s of ViewSectionTypes) { - if (s !== section) { - await (await findViewSection(s))?.collapse(); - } - } - const sectionView = await getViewSection(section); - - if (!sectionView) { - return; - } - - const configTree = sectionView as CustomTreeSection; - - await waitForTreeItems(configTree); - const configItems = await configTree.getVisibleItems(); - - let subConfigItem: TreeItem | undefined; - for (const i of configItems) { - const label = await i.getLabel(); - if (label.startsWith(subSection)) { - subConfigItem = i; - break; - } - } - return subConfigItem; -} - -export async function waitForTreeItems( - section: ViewSection, - timeoutMs = 5000 -): Promise { - const start = Date.now(); - while (true) { - const items = await section.getVisibleItems(); - if (items.length > 0) { - return true; - } - if (Date.now() - start > timeoutMs) { - return false; - } - await new Promise((resolve) => setTimeout(resolve, 200)); - } -} - -export async function dismissNotifications() { - const workbench = await browser.getWorkbench(); - await sleep(1000); - const notifs = await workbench.getNotifications(); - try { - for (const n of notifs) { - await n.dismiss(); - } - } catch {} -} - -export async function waitForSyncComplete() { - await browser.waitUntil( - async () => { - return await getViewSubSection("CONFIGURATION", "Sync Destination"); - }, - { - timeout: 20000, - interval: 2000, - timeoutMsg: "Couldn't find sync destination tree items.", - } - ); - await browser.waitUntil( - async () => { - const repoConfigItem = await getViewSubSection( - "CONFIGURATION", - "Sync Destination" - ); - if (repoConfigItem === undefined) { - return false; - } - await repoConfigItem.expand(); - - let status: TreeItem | undefined = undefined; - for (const i of await repoConfigItem.getChildren()) { - if ((await i.getLabel()).includes("State")) { - status = i; - break; - } - } - if (status === undefined) { - return false; - } - - const description = await status?.getDescription(); - return ( - description !== undefined && - description.includes("WATCHING_FOR_CHANGES") - ); - }, - { - timeout: 60000, - interval: 2000, - timeoutMsg: "Couldn't finish sync in 1m", - } - ); -} - -export async function startSyncIfStopped() { - browser.waitUntil( - async () => { - const repoConfigItem = await getViewSubSection( - "CONFIGURATION", - "Sync Destination" - ); - if (repoConfigItem === undefined) { - return false; - } - await repoConfigItem.expand(); - - let status: TreeItem | undefined = undefined; - for (const i of await repoConfigItem.getChildren()) { - if ((await i.getLabel()).includes("State")) { - status = i; - break; - } - } - if (status === undefined) { - return false; - } - - if ((await status.getDescription())?.includes("STOPPED")) { - const buttons = await repoConfigItem.getActionButtons(); - if (buttons.length === 0) { - return false; - } - await buttons[0].elem.click(); - } - return true; - }, - { - timeout: 20000, - } - ); -} diff --git a/packages/databricks-vscode/src/test/e2e/utils/commonUtils.ts b/packages/databricks-vscode/src/test/e2e/utils/commonUtils.ts new file mode 100644 index 000000000..619c2312a --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/utils/commonUtils.ts @@ -0,0 +1,317 @@ +import assert from "node:assert"; +import {randomUUID} from "crypto"; +import { + CustomTreeSection, + sleep, + TreeItem, + ViewControl, + ViewSection, + InputBox, +} from "wdio-vscode-service"; + +// eslint-disable-next-line @typescript-eslint/naming-convention +const ViewSectionTypes = [ + "CLUSTERS", + "CONFIGURATION", + "WORKSPACE EXPLORER", + "BUNDLE RESOURCE EXPLORER", + "BUNDLE VARIABLES", +] as const; +export type ViewSectionType = (typeof ViewSectionTypes)[number]; + +export async function findViewSection(name: ViewSectionType) { + const workbench = await browser.getWorkbench(); + + let control: ViewControl | undefined; + await browser.waitUntil( + async () => { + control = await workbench + .getActivityBar() + .getViewControl("Databricks"); + if (!control) { + return false; + } + return true; + }, + { + timeout: 10 * 1000, + interval: 1 * 1000, + timeoutMsg: `Can't find view control "${name}"`, + } + ); + const views = + (await (await control?.openView())?.getContent()?.getSections()) ?? []; + for (const v of views) { + const title = await v.getTitle(); + if (title === null) { + continue; + } + if (title.toUpperCase() === name) { + return v; + } + } +} + +export async function getViewSection( + name: ViewSectionType +): Promise { + let section: ViewSection | undefined; + await browser.waitUntil( + async () => { + section = await findViewSection(name); + return section !== undefined; + }, + { + timeout: 10 * 1000, + timeoutMsg: `Can't find view section "${name}"`, + } + ); + + for (const s of ViewSectionTypes) { + if (s !== name) { + await (await findViewSection(s))?.collapse(); + } + } + + await section!.expand(); + await (await section!.elem).click(); + return section; +} + +export async function getViewSubSection( + section: ViewSectionType, + subSection: string +): Promise { + for (const s of ViewSectionTypes) { + if (s !== section) { + await (await findViewSection(s))?.collapse(); + } + } + const sectionView = await getViewSection(section); + + if (!sectionView) { + return; + } + + const configTree = sectionView as CustomTreeSection; + + await waitForTreeItems(configTree); + const configItems = await configTree.getVisibleItems(); + + let subConfigItem: TreeItem | undefined; + for (const i of configItems) { + const label = await i.getLabel(); + if (label.startsWith(subSection)) { + subConfigItem = i; + break; + } + } + return subConfigItem; +} + +export async function waitForTreeItems( + section: ViewSection, + timeoutMs = 5000 +): Promise { + const start = Date.now(); + while (true) { + const items = await section.getVisibleItems(); + if (items.length > 0) { + return true; + } + if (Date.now() - start > timeoutMs) { + return false; + } + await new Promise((resolve) => setTimeout(resolve, 200)); + } +} + +export async function dismissNotifications() { + const workbench = await browser.getWorkbench(); + await sleep(1000); + const notifs = await workbench.getNotifications(); + try { + for (const n of notifs) { + await n.dismiss(); + } + } catch {} +} + +export async function waitForSyncComplete() { + const viewSection = (await getViewSection("CONFIGURATION")) as + | CustomTreeSection + | undefined; + + assert(viewSection, "CONFIGURATION section doesn't exist"); + + await browser.waitUntil( + async () => { + const subTreeItems = await viewSection.openItem("Workspace Folder"); + for (const item of subTreeItems) { + if ((await item.getLabel()).includes("State")) { + const status = await item.getDescription(); + return status === "WATCHING_FOR_CHANGES"; + } + } + return false; + }, + { + timeout: 60_000, + interval: 2000, + timeoutMsg: "Couldn't finish sync in 1m", + } + ); +} + +export async function getTabByTitle(title: string) { + const workbench = await browser.getWorkbench(); + return await browser.waitUntil( + async () => { + console.log("Searching for a tab with title:", title); + const tabs = await workbench.getEditorView().getOpenTabs(); + for (const tab of tabs) { + const tabTitle = await tab.getTitle(); + console.log("Found a tab:", tabTitle); + if (tabTitle.includes(title)) { + return tab; + } + } + }, + {timeout: 5000} + ); +} + +export async function waitForInput() { + const workbench = await browser.getWorkbench(); + let input: InputBox | undefined; + await browser.waitUntil( + async () => { + if (!input) { + input = await new InputBox(workbench.locatorMap).wait(); + } + if (input) { + return !(await input.hasProgress()); + } + return false; + }, + {timeout: 10000} + ); + return input!; +} + +export async function waitForLogin(profileName: string) { + await browser.waitUntil( + async () => { + await dismissNotifications(); + const section = (await getViewSection( + "CONFIGURATION" + )) as CustomTreeSection; + assert(section, "CONFIGURATION section doesn't exist"); + const items = await section.getVisibleItems(); + for (const item of items) { + const label = await item.getLabel(); + if (label.toLowerCase().includes("auth type")) { + const desc = await item.getDescription(); + return desc?.includes(profileName); + } + } + }, + {timeout: 60_000, interval: 2_000, timeoutMsg: "Login didn't finish"} + ); +} + +export function getStaticResourceName(name: string) { + return `vscode_integration_test_${name}`; +} + +export function getUniqueResourceName(name?: string) { + const uniqueName = name + ? `${randomUUID().slice(0, 8)}_${name}` + : randomUUID().slice(0, 8); + return getStaticResourceName(uniqueName); +} + +export async function waitForWorkflowWebview(expectedOutput: string) { + const workbench = await browser.getWorkbench(); + const title = /Databricks Job Run/; + await browser.waitUntil( + async () => { + try { + const webView = await workbench.getWebviewByTitle(title); + return webView !== undefined; + } catch (e) { + return false; + } + }, + { + timeout: 5_000, + interval: 1_000, + timeoutMsg: "Webview did not open", + } + ); + const webView = await workbench.getWebviewByTitle(title); + await webView.open(); + + await browser.waitUntil( + async () => { + const runId = await browser.getTextByLabel("task-run-id"); + return /N\\A/.test(runId) === false; + }, + { + timeoutMsg: "Job did not start", + } + ); + + const startTime = await browser.getTextByLabel("run-start-time"); + expect(startTime).not.toHaveText("-"); + + await browser.waitUntil( + async () => { + const status = await browser.getTextByLabel("run-status"); + return status.includes("Succeeded"); + }, + { + timeout: 60_000, + interval: 100, + timeoutMsg: "Job did not reach succeeded status after 60s.", + } + ); + + const iframe = browser.$("#frame"); + browser.switchToFrame(iframe); + const iframeRoot = await browser.$("html"); + expect(webView.activeFrame); + expect(iframeRoot).toHaveText(expectedOutput); + browser.switchToParentFrame(); + await webView.close(); +} + +export async function openFile(fileName: string) { + const workbench = await driver.getWorkbench(); + const editorView = workbench.getEditorView(); + await editorView.closeAllEditors(); + const input = await workbench.openCommandPrompt(); + await input.setText(fileName); + await input.confirm(); + await browser.waitUntil(async () => { + const editorView = workbench.getEditorView(); + const activeTab = await editorView.getActiveTab(); + if (!activeTab) { + return; + } + const title = await activeTab.getTitle(); + return title.includes(fileName); + }); +} + +export async function executeCommandWhenAvailable(command: string) { + const workbench = await driver.getWorkbench(); + return browser.waitUntil(async () => { + try { + await workbench.executeQuickPick(command); + return true; + } catch (e) { + return false; + } + }); +} diff --git a/packages/databricks-vscode/src/test/e2e/utils/dabsExplorerUtils.ts b/packages/databricks-vscode/src/test/e2e/utils/dabsExplorerUtils.ts new file mode 100644 index 000000000..2b3df6b4f --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/utils/dabsExplorerUtils.ts @@ -0,0 +1,34 @@ +import assert from "assert"; +import {CustomTreeSection} from "wdio-vscode-service"; + +export async function getJobViewItem( + resourceExplorer: CustomTreeSection, + jobDisplayName: string +) { + const jobs = await resourceExplorer.openItem("Workflows"); + for (const job of jobs) { + if ((await job.elem.getText()).includes(jobDisplayName)) { + return job; + } + } +} + +export async function geTaskViewItem( + resourceExplorerView: CustomTreeSection, + jobName: string, + taskName: string +) { + const jobViewItem = await getJobViewItem(resourceExplorerView, jobName); + assert(jobViewItem, `Job view item with name ${jobName} not found`); + + const tasks = await resourceExplorerView.openItem( + "Workflows", + await (await jobViewItem!.elem).getText(), + "Tasks" + ); + for (const task of tasks) { + if ((await task.elem.getText()).includes(taskName)) { + return task; + } + } +} diff --git a/packages/databricks-vscode/src/test/e2e/utils/dabsFixtures.ts b/packages/databricks-vscode/src/test/e2e/utils/dabsFixtures.ts new file mode 100644 index 000000000..3b62fb86b --- /dev/null +++ b/packages/databricks-vscode/src/test/e2e/utils/dabsFixtures.ts @@ -0,0 +1,90 @@ +/* eslint-disable @typescript-eslint/naming-convention */ +import {Resource, BundleTarget, BundleSchema} from "../../../bundle/types.ts"; +import path from "path"; +import assert from "assert"; +import {writeFile, unlink} from "fs/promises"; +import {getUniqueResourceName} from "./commonUtils.ts"; +import yaml from "yaml"; +import lodash from "lodash"; + +type SimpleJob = Pick< + Resource, + "name" | "tasks" | "job_clusters" +>; + +export function getSimpleJobsResource(def: Omit) { + const defaultSimpleJob: SimpleJob = { + name: getUniqueResourceName(), + tasks: undefined, + job_clusters: [ + { + job_cluster_key: "job_cluster", + new_cluster: { + spark_version: "13.3.x-scala2.12", + node_type_id: "Standard_D3_v2", + autoscale: { + min_workers: 1, + max_workers: 2, + }, + }, + }, + ], + }; + def = Object.assign({}, def); + + def.tasks = def.tasks?.map((task) => { + if ( + task.job_cluster_key === undefined && + task.new_cluster === undefined && + task.existing_cluster_id === undefined + ) { + task.job_cluster_key = "job_cluster"; + } + return task; + }); + + return lodash.merge(defaultSimpleJob, def); +} + +export function getBasicBundleConfig( + overrides: BundleSchema = {}, + topLevelComputeId = true +): BundleSchema { + assert(process.env.DATABRICKS_HOST, "DATABRICKS_HOST doesn't exist"); + assert( + process.env.TEST_DEFAULT_CLUSTER_ID, + "TEST_DEFAULT_CLUSTER_ID doesn't exist" + ); + const defaultBundleConfig = { + bundle: { + name: getUniqueResourceName("basic_bundle"), + compute_id: topLevelComputeId + ? process.env.TEST_DEFAULT_CLUSTER_ID + : undefined, + }, + targets: { + dev_test: { + mode: "development", + default: true, + workspace: { + host: process.env.DATABRICKS_HOST, + }, + }, + }, + }; + + return lodash.merge(defaultBundleConfig, overrides); +} + +export async function writeRootBundleConfig( + config: BundleSchema, + workspacePath: string +) { + const bundleConfig = path.join(workspacePath, "databricks.yml"); + await writeFile(bundleConfig, yaml.stringify(config)); +} + +export async function clearRootBundleConfig(workspacePath: string) { + const bundleConfig = path.join(workspacePath, "databricks.yml"); + await unlink(bundleConfig); +} diff --git a/packages/databricks-vscode/src/test/e2e/wdio.conf.ts b/packages/databricks-vscode/src/test/e2e/wdio.conf.ts index 62dad5722..9a715fc24 100644 --- a/packages/databricks-vscode/src/test/e2e/wdio.conf.ts +++ b/packages/databricks-vscode/src/test/e2e/wdio.conf.ts @@ -8,28 +8,24 @@ import path from "node:path"; import {fileURLToPath} from "url"; import assert from "assert"; import fs from "fs/promises"; -import { - ApiError, - Config, - WorkspaceClient, - workspace, -} from "@databricks/databricks-sdk"; +import {Config, WorkspaceClient} from "@databricks/databricks-sdk"; import * as ElementCustomCommands from "./customCommands/elementCustomCommands.ts"; -import {execFile, ExecFileOptions} from "node:child_process"; +import {execFile as execFileCb} from "node:child_process"; import {cpSync, mkdirSync, rmSync} from "node:fs"; import {tmpdir} from "node:os"; import packageJson from "../../../package.json" assert {type: "json"}; import {sleep} from "wdio-vscode-service"; import {glob} from "glob"; +import {getUniqueResourceName} from "./utils/commonUtils.ts"; +import {promisify} from "node:util"; -const WORKSPACE_PATH = path.resolve(tmpdir(), "workspace"); +const WORKSPACE_PATH = path.resolve(tmpdir(), "test-root"); const __filename = fileURLToPath(import.meta.url); const __dirname = path.dirname(__filename); const {version, name, engines} = packageJson; -const REPO_NAME = "vscode-integ-test"; -const EXTENSION_DIR = path.resolve(tmpdir(), "extension-test", "extension"); +const EXTENSION_DIR = path.resolve(tmpdir(), "extension test", "extension"); const VSIX_PATH = path.resolve( __dirname, "..", @@ -39,6 +35,63 @@ const VSIX_PATH = path.resolve( ); const VSCODE_STORAGE_DIR = path.resolve(tmpdir(), "user-data-dir"); +const metaCharsRegExp = /([()\][%!^"`<>&|;, *?])/g; + +export function escapeCommand(arg: string): string { + // Escape meta chars + arg = arg.replace(metaCharsRegExp, "^$1"); + + return arg; +} + +export function escapeArgument(arg: string): string { + // Convert to string + arg = `${arg}`; + + // Algorithm below is based on https://qntm.org/cmd + + // Sequence of backslashes followed by a double quote: + // double up all the backslashes and escape the double quote + arg = arg.replace(/(\\*)"/g, '$1$1\\"'); + + // Sequence of backslashes followed by the end of the string + // (which will become a double quote later): + // double up all the backslashes + arg = arg.replace(/(\\*)$/, "$1$1"); + + // All other backslashes occur literally + + // Quote the whole thing: + arg = `"${arg}"`; + + // Escape meta chars + arg = arg.replace(metaCharsRegExp, "^$1"); + + return arg; +} + +const execFile = async ( + file: string, + args: string[], + options: any = {} +): Promise<{ + stdout: string; + stderr: string; +}> => { + if (process.platform === "win32") { + const realArgs = [escapeCommand(file)] + .concat(args.map(escapeArgument).join(" ")) + .join(" "); + + file = "cmd.exe"; + args = ["/d", "/s", "/c", `"${realArgs}"`]; + console.log("execFile", file, args); + options = {...options, windowsVerbatimArguments: true}; + } + const res = await promisify(execFileCb)(file, args, options); + return {stdout: res.stdout.toString(), stderr: res.stderr.toString()}; +}; + export const config: Options.Testrunner = { // // ==================== @@ -84,7 +137,7 @@ export const config: Options.Testrunner = { // then the current working directory is where your `package.json` resides, so `wdio` // will be called from there. // - specs: [__dirname + "/**/*.e2e.ts"], + specs: [path.join(__dirname, "**", "*.e2e.ts")], // Patterns to exclude. exclude: [ // 'path/to/excluded/files' @@ -194,7 +247,15 @@ export const config: Options.Testrunner = { // Services take over a specific job you don't want to take care of. They enhance // your test setup with almost no effort. Unlike plugins, they don't add new // commands. Instead, they hook themselves up into the test process. - services: [["vscode", {cachePath: "/tmp/wdio-vscode-service"}]], + services: [ + [ + "vscode", + {cachePath: path.join(process.cwd(), "tmp", "wdio-vscode-service")}, + ], + ], + + // cahePath above is for vscode binaries, this one is for the chromedriver + cacheDir: path.join(process.cwd(), "tmp", "wdio-vscode-service"), // Framework you want to run your specs with. // The following are supported: Mocha, Jasmine, and Cucumber @@ -205,7 +266,7 @@ export const config: Options.Testrunner = { framework: "mocha", // // The number of times to retry the entire specfile when it fails as a whole - specFileRetries: 1, + specFileRetries: 0, // // Delay in seconds between the spec file retry attempts specFileRetriesDelay: 0, @@ -263,19 +324,14 @@ export const config: Options.Testrunner = { ); await fs.rm(WORKSPACE_PATH, {recursive: true, force: true}); - await fs.mkdir(WORKSPACE_PATH); + console.log(`Creating vscode workspace folder: ${WORKSPACE_PATH}`); + await fs.mkdir(WORKSPACE_PATH, {recursive: true}); const client = getWorkspaceClient(config); - const repoPath = await createRepo(client); - const workspaceFolderPath = await createWsFolder(client); - const configFile = await writeDatabricksConfig(config); await startCluster(client, process.env["TEST_DEFAULT_CLUSTER_ID"]); process.env.DATABRICKS_HOST = config.host!; - process.env.DATABRICKS_CONFIG_FILE = configFile; - process.env.WORKSPACE_PATH = WORKSPACE_PATH; - process.env.TEST_REPO_PATH = repoPath; - process.env.TEST_WORKSPACE_FOLDER_PATH = workspaceFolderPath; + process.env.DATABRICKS_VSCODE_INTEGRATION_TEST = "true"; } catch (e) { console.error(e); process.exit(1); @@ -286,13 +342,30 @@ export const config: Options.Testrunner = { * Gets executed before a worker process is spawned and can be used to initialise specific service * for that worker as well as modify runtime environments in an async fashion. * @param {String} cid capability id (e.g 0-0) - * @param {[type]} caps object containing capabilities for session that will be spawn in the worker + * @param {Array.} capabilities object containing capabilities for session that will be spawn in the worker * @param {[type]} specs specs to be run in the worker process * @param {[type]} args object that will be merged with the main configuration once worker is initialized * @param {[type]} execArgv list of string arguments passed to the worker process */ - // onWorkerStart: function (cid, caps, specs, args, execArgv) { - // }, + onWorkerStart: async function (cid, capabilities) { + const sdkConfig = new Config({}); + await sdkConfig.ensureResolved(); + + const testRoot = path.join( + WORKSPACE_PATH, + getUniqueResourceName("root_dir") + ); + await fs.mkdir(testRoot, { + recursive: true, + }); + const configFile = await writeDatabricksConfig(sdkConfig, testRoot); + + process.env.DATABRICKS_CONFIG_FILE = configFile; + process.env.WORKSPACE_PATH = testRoot; + if (capabilities["wdio:vscodeOptions"]) { + capabilities["wdio:vscodeOptions"].workspacePath = testRoot; + } + }, /** * Gets executed just after a worker process has exited. @@ -315,14 +388,10 @@ export const config: Options.Testrunner = { beforeSession: async function (config, capabilities) { const binary: string = capabilities["wdio:vscodeOptions"] .binary as string; - let cli: string; - let spawnArgs: ExecFileOptions; + let cli: string = ""; switch (process.platform) { case "win32": cli = path.resolve(binary, "..", "bin", "code"); - spawnArgs = { - shell: true, - }; break; case "darwin": cli = path.resolve( @@ -331,56 +400,23 @@ export const config: Options.Testrunner = { "..", "Resources/app/bin/code" ); - spawnArgs = { - shell: false, - }; break; } - for (let i = 0; i < 2; i++) { - try { - await new Promise((resolve, reject) => { - const extensionDependencies = - packageJson.extensionDependencies.flatMap((item) => [ - "--install-extension", - item, - ]); - execFile( - cli, - [ - "--extensions-dir", - EXTENSION_DIR, - ...extensionDependencies, - "--install-extension", - VSIX_PATH, - "--force", - ], - spawnArgs, - (error, stdout, stderr) => { - if (stdout) { - console.log(stdout); - } - if (error) { - console.error(stderr); - console.error(error); - reject(error); - } - resolve(undefined); - } - ); - }); - } catch (error) { - if (i === 1) { - throw error; - } - continue; - } - break; - } - - await fs.rm(path.join(WORKSPACE_PATH, ".databricks"), { - recursive: true, - force: true, - }); + const extensionDependencies = packageJson.extensionDependencies.flatMap( + (item) => ["--install-extension", item] + ); + + console.log("running vscode cli"); + const res = await execFile(cli, [ + "--extensions-dir", + EXTENSION_DIR, + ...extensionDependencies, + "--install-extension", + VSIX_PATH, + "--force", + ]); + + console.log(res.stdout, res.stderr); }, /** @@ -480,7 +516,7 @@ export const config: Options.Testrunner = { afterSession: async function (config, capabilities, specs) { await sleep(2000); try { - const fileList = await glob( + const logFileList = await glob( path.join( VSCODE_STORAGE_DIR, "**", @@ -488,8 +524,8 @@ export const config: Options.Testrunner = { "*.json" ) ); - console.log(fileList); - fileList.forEach((file) => { + console.log(logFileList); + logFileList.forEach((file) => { cpSync( file, path.join( @@ -530,20 +566,14 @@ export const config: Options.Testrunner = { // } }; -async function writeDatabricksConfig(config: Config) { - assert( - process.env["TEST_DEFAULT_CLUSTER_ID"], - "Environment variable TEST_DEFAULT_CLUSTER_ID must be set" - ); - - const configFile = path.join(WORKSPACE_PATH, ".databrickscfg"); +async function writeDatabricksConfig(config: Config, rootPath: string) { + const configFile = path.join(rootPath, ".databrickscfg"); await fs.writeFile( configFile, `[DEFAULT] host = ${config.host!} token = ${config.token!}` ); - return configFile; } @@ -556,74 +586,46 @@ function getWorkspaceClient(config: Config) { return client; } -/** - * Create a repo for the integration tests to use - */ -async function createRepo(workspaceClient: WorkspaceClient): Promise { - const me = (await workspaceClient.currentUser.me()).userName!; - const repoPath = `/Repos/${me}/${REPO_NAME}`; - - console.log(`Creating test Repo: ${repoPath}`); - - let repo: workspace.RepoInfo | undefined; - try { - for await (const r of workspaceClient.repos.list({ - path_prefix: repoPath, - })) { - if (r.path === repoPath) { - repo = r; - break; - } - } - assert(repo, `Couldn't find repo at ${repoPath}`); - } catch (e) { - repo = await workspaceClient.repos.create({ - path: repoPath, - url: "https://github.com/fjakobs/empty-repo.git", - provider: "github", - }); - } - - return repo.path!; -} - -/** - * Create a workspace folder for the integration tests to use - */ -async function createWsFolder( - workspaceClient: WorkspaceClient -): Promise { - const me = (await workspaceClient.currentUser.me()).userName!; - const wsFolderPath = `/Users/${me}/.ide/${REPO_NAME}`; - - console.log(`Creating test Workspace Folder: ${wsFolderPath}`); - - await workspaceClient.workspace.mkdirs({path: wsFolderPath}); - const status = await workspaceClient.workspace.getStatus({ - path: wsFolderPath, - }); - - assert.equal(status.object_type, "DIRECTORY"); - return status.path!; -} - async function startCluster( workspaceClient: WorkspaceClient, - clusterId: string + clusterId: string, + attempt = 0 ) { - console.log(`Starting cluster: ${clusterId}`); - - try { - await ( - await workspaceClient.clusters.start({ - cluster_id: clusterId, - }) - ).wait(); - } catch (e: unknown) { - if (!(e instanceof ApiError && e.message.includes("INVALID_STATE"))) { - throw e; - } + console.log(`Cluster ID: ${clusterId}`); + if (attempt > 100) { + throw new Error("Failed to start the cluster: too many attempts"); + } + const cluster = await workspaceClient.clusters.get({ + cluster_id: clusterId, + }); + console.log(`Cluster State: ${cluster.state}`); + switch (cluster.state) { + case "RUNNING": + console.log("Cluster is already running"); + break; + case "TERMINATED": + case "ERROR": + case "UNKNOWN": + console.log("Starting the cluster..."); + await ( + await workspaceClient.clusters.start({ + cluster_id: clusterId, + }) + ).wait({ + onProgress: async (state) => { + console.log(`Cluster state: ${state.state}`); + }, + }); + break; + case "PENDING": + case "RESIZING": + case "TERMINATING": + case "RESTARTING": + console.log("Waiting and retrying..."); + await sleep(10000); + await startCluster(workspaceClient, clusterId, attempt + 1); + break; + default: + throw new Error(`Unknown cluster state: ${cluster.state}`); } - - console.log(`Cluster started`); } diff --git a/packages/databricks-vscode/src/ui/DecorationProvider.ts b/packages/databricks-vscode/src/ui/DecorationProvider.ts new file mode 100644 index 000000000..6fcf7e704 --- /dev/null +++ b/packages/databricks-vscode/src/ui/DecorationProvider.ts @@ -0,0 +1,57 @@ +import { + Event, + FileDecoration, + FileDecorationProvider, + ProviderResult, + Uri, + EventEmitter, + Disposable, +} from "vscode"; +import {BundleResourceExplorerTreeDataProvider} from "./bundle-resource-explorer/BundleResourceExplorerTreeDataProvider"; +import {ConfigurationDataProvider} from "./configuration-view/ConfigurationDataProvider"; + +const SCHEME = "databricks-view-item"; +export class TreeItemDecorationProvider implements FileDecorationProvider { + private readonly disposables: Disposable[] = []; + private onDidChangeFileDecorationsEmitter: EventEmitter< + Uri | Uri[] | undefined + > = new EventEmitter(); + onDidChangeFileDecorations: Event = + this.onDidChangeFileDecorationsEmitter.event; + constructor( + private readonly bundleResourceExplorerTreeDataProvider: BundleResourceExplorerTreeDataProvider, + private readonly configrationViewTreeDataProvider: ConfigurationDataProvider + ) { + this.disposables.push( + this.bundleResourceExplorerTreeDataProvider.onDidChangeTreeData( + () => { + this.onDidChangeFileDecorationsEmitter.fire(undefined); + } + ), + this.configrationViewTreeDataProvider.onDidChangeTreeData(() => { + this.onDidChangeFileDecorationsEmitter.fire(undefined); + }) + ); + } + + provideFileDecoration(uri: Uri): ProviderResult { + if (uri.scheme !== SCHEME) { + return undefined; + } + return uri.query + ? (JSON.parse(uri.query) as FileDecoration) + : undefined; + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} + +export function asDecorationResourceUri(id: string, data: FileDecoration) { + return Uri.from({ + scheme: SCHEME, + path: id, + query: JSON.stringify(data), + }); +} diff --git a/packages/databricks-vscode/src/ui/wizard.ts b/packages/databricks-vscode/src/ui/MultiStepInputWizard.ts similarity index 73% rename from packages/databricks-vscode/src/ui/wizard.ts rename to packages/databricks-vscode/src/ui/MultiStepInputWizard.ts index 5a16df10d..9d362ffc9 100644 --- a/packages/databricks-vscode/src/ui/wizard.ts +++ b/packages/databricks-vscode/src/ui/MultiStepInputWizard.ts @@ -11,9 +11,10 @@ import { Disposable, window, QuickInputButtons, + InputBoxValidationSeverity, } from "vscode"; -class InputFlowAction { +export class InputFlowAction { static back = new InputFlowAction(); static cancel = new InputFlowAction(); static resume = new InputFlowAction(); @@ -26,17 +27,23 @@ interface EditItem { error: boolean; } -type InputStep = (input: MultiStepInput) => Thenable; +export type InputStep = (input: MultiStepInput) => Thenable; export type ValidationMessageType = { message: string; type: "error" | "warning"; }; +// eslint-disable-next-line @typescript-eslint/naming-convention +const ValidationMessageTypeToInputBoxSeverity = { + error: InputBoxValidationSeverity.Error, + warning: InputBoxValidationSeverity.Warning, +}; + interface QuickAutoCompleteParameters { title: string; step: number; totalSteps: number; - prompt: string; + placeholder: string; validate: ( value: string ) => Promise; @@ -58,6 +65,19 @@ interface QuickPickParameters { ignoreFocusOut: boolean; } +interface InputBoxParameters { + title: string; + step: number; + totalSteps: number; + placeholder: string; + initialValue?: string; + validate?: ( + value: string + ) => Promise; + buttons?: QuickInputButton[]; + ignoreFocusOut: boolean; +} + export class MultiStepInput { static async run(start: InputStep) { const input = new MultiStepInput(); @@ -67,6 +87,13 @@ export class MultiStepInput { private current?: QuickInput; private steps: InputStep[] = []; + public hide() { + this.current?.hide(); + } + public show() { + this.current?.show(); + } + private async stepThrough(start: InputStep) { let step: InputStep | void = start; while (step) { @@ -104,7 +131,7 @@ export class MultiStepInput { title, step, totalSteps, - prompt, + placeholder, validate, buttons, shouldResume, @@ -130,7 +157,7 @@ export class MultiStepInput { input.title = title; input.step = step; input.totalSteps = totalSteps; - input.placeholder = prompt; + input.placeholder = placeholder; input.items = [...items]; input.ignoreFocusOut = ignoreFocusOut; @@ -286,4 +313,75 @@ export class MultiStepInput { disposables.forEach((d) => d.dispose()); } } + + async showInputBox({ + title, + step, + totalSteps, + placeholder, + initialValue, + buttons, + validate, + ignoreFocusOut, + }: InputBoxParameters) { + const disposables: Disposable[] = []; + try { + return await new Promise((resolve, reject) => { + const input = window.createInputBox(); + input.title = title; + input.step = step; + input.totalSteps = totalSteps; + input.placeholder = placeholder; + input.ignoreFocusOut = ignoreFocusOut; + input.value = initialValue ?? ""; + input.buttons = [ + ...(this.steps.length > 1 ? [QuickInputButtons.Back] : []), + ...(buttons || []), + ]; + + disposables.push( + input.onDidTriggerButton((item) => { + if (item === QuickInputButtons.Back) { + reject(InputFlowAction.back); + } else { + // eslint-disable-next-line @typescript-eslint/no-explicit-any + resolve(item); + } + }), + input.onDidHide(() => reject(InputFlowAction.cancel)), + input.onDidChangeValue(async (value) => { + const validationMessage = validate + ? await validate(value) + : undefined; + + if ( + validationMessage === undefined || + typeof validationMessage === "string" + ) { + input.validationMessage = validationMessage; + } else { + input.validationMessage = { + message: validationMessage.message, + severity: + ValidationMessageTypeToInputBoxSeverity[ + validationMessage.type + ], + }; + } + }), + input.onDidAccept(() => { + resolve(input.value); + }) + ); + + if (this.current) { + this.current.dispose(); + } + this.current = input; + this.current.show(); + }); + } finally { + disposables.forEach((d) => d.dispose()); + } + } } diff --git a/packages/databricks-vscode/src/ui/TreeItemTreeNode.ts b/packages/databricks-vscode/src/ui/TreeItemTreeNode.ts new file mode 100644 index 000000000..8aebf013b --- /dev/null +++ b/packages/databricks-vscode/src/ui/TreeItemTreeNode.ts @@ -0,0 +1,17 @@ +import {TreeItem} from "vscode"; + +export class TreeItemTreeNode { + readonly type = "treeItem"; + constructor( + public readonly treeItem: TreeItem, + public readonly parent?: T + ) {} + + getTreeItem(): TreeItem { + return this.treeItem; + } + + getChildren(): T[] { + return []; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleCommands.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleCommands.ts new file mode 100644 index 000000000..faca2d6c8 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleCommands.ts @@ -0,0 +1,258 @@ +import {Disposable, ProgressLocation, window} from "vscode"; +import {BundleRemoteStateModel} from "../../bundle/models/BundleRemoteStateModel"; +import {onError} from "../../utils/onErrorDecorator"; +import {BundleResourceExplorerTreeNode} from "./types"; +import {BundleRunStatusManager} from "../../bundle/run/BundleRunStatusManager"; +import {Mutex} from "../../locking"; +import {BundleValidateModel} from "../../bundle/models/BundleValidateModel"; +import {PipelineTreeNode} from "./PipelineTreeNode"; +import {JobTreeNode} from "./JobTreeNode"; +import {CustomWhenContext} from "../../vscode-objs/CustomWhenContext"; +import {Events, Telemetry} from "../../telemetry"; +import * as lodash from "lodash"; +import {ProcessError} from "../../cli/CliWrapper"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {humaniseMode} from "../utils/BundleUtils"; +export const RUNNABLE_BUNDLE_RESOURCES = [ + "pipelines", + "jobs", +] satisfies BundleResourceExplorerTreeNode["type"][]; + +type RunnableTreeNodes = PipelineTreeNode | JobTreeNode; + +function isRunnable( + treeNode: BundleResourceExplorerTreeNode +): treeNode is RunnableTreeNodes { + return (RUNNABLE_BUNDLE_RESOURCES as string[]).includes(treeNode.type); +} + +export class BundleCommands implements Disposable { + private disposables: Disposable[] = []; + + constructor( + private readonly bundleRemoteStateModel: BundleRemoteStateModel, + private readonly bundleRunStatusManager: BundleRunStatusManager, + private readonly bundleValidateModel: BundleValidateModel, + private readonly configModel: ConfigModel, + private readonly whenContext: CustomWhenContext, + private readonly telemetry: Telemetry + ) { + this.disposables.push( + this.bundleValidateModel.onDidChange(async () => { + // Only refresh if both the validate model and the remote state model are using the same target and auth provider + if ( + this.bundleRemoteStateModel.target === + this.bundleValidateModel.target && + lodash.isEqual( + this.bundleRemoteStateModel.authProvider, + this.bundleValidateModel.authProvider + ) + ) { + await this.refreshRemoteState(); + } + }) + ); + } + + private refreshStateMutex = new Mutex(); + + @Mutex.synchronise("refreshStateMutex") + async refreshRemoteState() { + try { + await window.withProgress( + {location: {viewId: "dabsResourceExplorerView"}}, + async () => { + await this.bundleRemoteStateModel.refresh(); + } + ); + } catch (e: any) { + if (!(e instanceof Error)) { + throw e; + } + + if (e instanceof ProcessError) { + e.showErrorMessage("Error refreshing remote state."); + } + + throw e; + } + } + + @onError({log: true, popup: false}) + public async refreshCommand() { + await this.refreshRemoteState(); + } + + private deployMutex = new Mutex(); + + @Mutex.synchronise("deployMutex") + async sync() { + try { + this.whenContext.setDeploymentState("deploying"); + await window.withProgress( + { + location: ProgressLocation.Notification, + title: "Uploading bundle assets", + cancellable: true, + }, + async (progress, token) => { + await this.bundleRemoteStateModel.sync(token); + } + ); + } catch (e) { + if (!(e instanceof Error)) { + throw e; + } + if (e instanceof ProcessError) { + e.showErrorMessage("Error synchronising bundle assets."); + } + throw e; + } finally { + this.whenContext.setDeploymentState("idle"); + } + } + + @Mutex.synchronise("deployMutex") + async deploy(force = false) { + try { + this.whenContext.setDeploymentState("deploying"); + const mode = await this.configModel.get("mode"); + const target = this.configModel.target; + const prettyMode = humaniseMode(mode); + const title = `Deploying the bundle to ${prettyMode} target "${target}".`; + if (mode !== "development") { + const choice = await window.showInformationMessage( + title, + {modal: true}, + "Continue" + ); + if (choice !== "Continue") { + window.showErrorMessage( + "Databricks: Deployment cancelled." + ); + return; + } + } + await window.withProgress( + { + location: ProgressLocation.Notification, + title: title, + cancellable: true, + }, + async (progress, token) => { + await this.bundleRemoteStateModel.deploy(force, token); + } + ); + + await this.refreshRemoteState(); + } catch (e) { + if (!(e instanceof Error)) { + throw e; + } + if (e instanceof ProcessError) { + e.showErrorMessage("Error deploying bundle."); + } + throw e; + } finally { + this.whenContext.setDeploymentState("idle"); + } + } + + @onError({log: true, popup: false}) + public async deployCommand() { + await this.deploy(); + } + + @onError({log: true, popup: false}) + public async forceDeployCommand() { + await this.deploy(true); + } + + @onError({popup: {prefix: "Error running resource."}}) + async deployAndRun(treeNode: BundleResourceExplorerTreeNode) { + if (!isRunnable(treeNode)) { + throw new Error(`Cannot run resource of type ${treeNode.type}`); + } + const recordEvent = this.telemetry.start(Events.BUNDLE_RUN); + try { + // TODO: Don't deploy if there is no diff between local and remote state + await this.deploy(); + const result = await this.bundleRunStatusManager.run( + treeNode.resourceKey, + treeNode.type + ); + recordEvent({ + success: true, + resourceType: treeNode.type, + cancelled: result.cancelled, + }); + } catch (e) { + recordEvent({success: false, resourceType: treeNode.type}); + throw e; + } + } + + @onError({popup: {prefix: "Error cancelling run."}}) + async cancelRun(treeNode: BundleResourceExplorerTreeNode) { + if (!isRunnable(treeNode)) { + throw new Error(`Resource of ${treeNode.type} is not runnable`); + } + + this.bundleRunStatusManager.cancel(treeNode.resourceKey); + } + + async destroy(force = false) { + if ((await this.configModel.get("mode")) !== "development") { + const confirm = await window.showErrorMessage( + "Are you sure you want to destroy this bundle and all resources associated with it?", + {modal: true}, + "Yes, continue", + "No" + ); + + if (confirm !== "Yes, continue") { + return; + } + } + + try { + this.whenContext.setDeploymentState("deploying"); + await window.withProgress( + { + location: ProgressLocation.Notification, + title: "Destroying the bundle", + cancellable: true, + }, + async (progress, token) => { + await this.bundleRemoteStateModel.destroy(force, token); + } + ); + + await this.refreshRemoteState(); + } catch (e) { + if (!(e instanceof Error)) { + throw e; + } + if (e instanceof ProcessError) { + e.showErrorMessage("Error destroying bundle."); + } + throw e; + } finally { + this.whenContext.setDeploymentState("idle"); + } + } + + @onError({log: true, popup: false}) + public async destroyCommand() { + await this.destroy(); + } + + @onError({log: true, popup: false}) + public async forceDestroyCommand() { + await this.destroy(true); + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleResourceExplorerTreeDataProvider.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleResourceExplorerTreeDataProvider.ts new file mode 100644 index 000000000..94a6598e9 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/BundleResourceExplorerTreeDataProvider.ts @@ -0,0 +1,80 @@ +import { + Disposable, + Event, + EventEmitter, + ExtensionContext, + ProviderResult, + TreeDataProvider, +} from "vscode"; +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {BundleRunStatusManager} from "../../bundle/run/BundleRunStatusManager"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {ResourceTypeHeaderTreeNode} from "./ResourceTypeHeaderTreeNode"; + +export class BundleResourceExplorerTreeDataProvider + implements TreeDataProvider +{ + private disposables: Disposable[] = []; + private _onDidChangeTreeData: EventEmitter< + BundleResourceExplorerTreeNode | undefined | void + > = new EventEmitter(); + readonly onDidChangeTreeData: Event< + BundleResourceExplorerTreeNode | undefined | void + > = this._onDidChangeTreeData.event; + + constructor( + private readonly configModel: ConfigModel, + private readonly bundleRunStatusManager: BundleRunStatusManager, + private readonly context: ExtensionContext, + private readonly connectionManager: ConnectionManager + ) { + this.disposables.push( + this.configModel.onDidChangeTarget(() => { + this._onDidChangeTreeData.fire(); + }), + this.configModel.onDidChangeKey("remoteStateConfig")(async () => { + this._onDidChangeTreeData.fire(); + }), + this.bundleRunStatusManager.onDidChange(() => { + this._onDidChangeTreeData.fire(); + }) + ); + } + + async getTreeItem( + element: BundleResourceExplorerTreeNode + ): Promise { + return element.getTreeItem(); + } + + async getChildren(element?: BundleResourceExplorerTreeNode) { + if (element === undefined) { + const bundleRemoteState = + await this.configModel.get("remoteStateConfig"); + if (bundleRemoteState === undefined) { + return []; + } + return ResourceTypeHeaderTreeNode.getRoots( + this.context, + this.bundleRunStatusManager, + this.connectionManager, + bundleRemoteState + ); + } + return element.getChildren(); + } + + getParent( + element: BundleResourceExplorerTreeNode + ): ProviderResult { + return element.parent; + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobRunStatusTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobRunStatusTreeNode.ts new file mode 100644 index 000000000..5a6308077 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobRunStatusTreeNode.ts @@ -0,0 +1,108 @@ +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {TreeItemCollapsibleState} from "vscode"; +import {ContextUtils, JobRunStateUtils, RunStateUtils} from "./utils"; +import {jobs} from "@databricks/databricks-sdk"; +import {JobRunStatus} from "../../bundle/run/JobRunStatus"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; + +export class JobRunStatusTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "job_run_status"; + get url() { + return this.runDetails?.run_page_url; + } + + get runDetails(): jobs.Run | undefined { + return this.runMonitor?.data; + } + + constructor( + public parent: BundleResourceExplorerTreeNode, + public readonly runMonitor?: JobRunStatus + ) {} + + getChildren(): BundleResourceExplorerTreeNode[] { + if (this.runDetails === undefined) { + return []; + } + + const children: BundleResourceExplorerTreeNode[] = []; + + if (this.runDetails.state?.state_message) { + children.push( + new TreeItemTreeNode( + { + label: "State Message", + description: this.runDetails.state?.state_message, + tooltip: this.runDetails.state?.state_message, + contextValue: "state_message", + }, + this + ) + ); + } + children.push( + new TreeItemTreeNode( + { + label: "Start Time", + description: RunStateUtils.humaniseDate( + this.runDetails.start_time + ), + contextValue: "start_time", + }, + this + ), + new TreeItemTreeNode( + { + label: "Duration", + description: RunStateUtils.humaniseDuration( + this.runDetails.run_duration + ), + contextValue: "end_time", + }, + this + ) + ); + return children; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + const runMonitorRunStateTreeItem = + RunStateUtils.getTreeItemFromRunMonitorStatus( + this.type, + this.url, + this.runMonitor + ); + + if (runMonitorRunStateTreeItem) { + return runMonitorRunStateTreeItem; + } + + if (this.runDetails === undefined) { + return { + label: "Run Status", + iconPath: RunStateUtils.getThemeIconForStatus("Unknown"), + description: "Run status not available", + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + }), + collapsibleState: TreeItemCollapsibleState.None, + }; + } + + const status = JobRunStateUtils.getSimplifiedRunState(this.runDetails); + const icon = RunStateUtils.getThemeIconForStatus(status); + return { + label: "Run Status", + iconPath: icon, + description: status, + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + hasUrl: this.url !== undefined, + }), + collapsibleState: TreeItemCollapsibleState.Collapsed, + }; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobTreeNode.ts new file mode 100644 index 000000000..010f69f84 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/JobTreeNode.ts @@ -0,0 +1,123 @@ +import {ExtensionContext} from "vscode"; +import {BundleRemoteState} from "../../bundle/models/BundleRemoteStateModel"; +import { + BundleResourceExplorerResource, + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {BundleRunStatusManager} from "../../bundle/run/BundleRunStatusManager"; +import {ContextUtils} from "./utils"; +import {DecorationUtils} from "../utils"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {JobRunStatusTreeNode} from "./JobRunStatusTreeNode"; +import {JobRunStatus} from "../../bundle/run/JobRunStatus"; +import {TaskTreeNode} from "./TaskTreeNode"; +import {TaskHeaderTreeNode} from "./TaskHeaderTreeNode"; + +export class JobTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "jobs"; + get url(): string | undefined { + const host = this.connectionManager.databricksWorkspace?.host; + + if (!host || !this.data.id) { + return undefined; + } + + return `${host.toString()}#job/${this.data.id}`; + } + + constructor( + private readonly context: ExtensionContext, + private readonly bundleRunStatusManager: BundleRunStatusManager, + private readonly connectionManager: ConnectionManager, + public readonly resourceKey: string, + public readonly data: BundleResourceExplorerResource<"jobs">, + public parent?: BundleResourceExplorerTreeNode + ) {} + + get isRunning() { + const runner = this.bundleRunStatusManager.runStatuses.get( + this.resourceKey + ); + return runner?.runState === "running" || runner?.runState === "unknown"; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + return { + label: this.data.name, + contextValue: ContextUtils.getContextString({ + resourceType: this.type, + running: this.isRunning, + hasUrl: this.url !== undefined, + cancellable: this.isRunning, + nodeType: this.type, + modifiedStatus: this.data.modified_status, + }), + resourceUri: DecorationUtils.getModifiedStatusDecoration( + this.data.name ?? this.resourceKey, + this.data.modified_status + ), + collapsibleState: DecorationUtils.getCollapsibleState( + this.isRunning, + this.data.modified_status + ), + }; + } + + getChildren(): BundleResourceExplorerTreeNode[] { + if (this.data.tasks === undefined) { + return []; + } + + const children: BundleResourceExplorerTreeNode[] = []; + const runMonitor = this.bundleRunStatusManager.runStatuses.get( + this.resourceKey + ) as JobRunStatus | undefined; + + if (runMonitor) { + children.push(new JobRunStatusTreeNode(this, runMonitor)); + } + children.push( + new TaskHeaderTreeNode( + this.data.tasks.map((task, i) => { + return new TaskTreeNode( + this.context, + this.connectionManager, + task, + this.resourceKey, + `${this.resourceKey}.tasks.[${i}].${task.task_key}`, + this, + this.data.id, + runMonitor + ); + }), + this + ) + ); + + return children; + } + + static getRoots( + context: ExtensionContext, + bundleRunStatusManager: BundleRunStatusManager, + connectionManager: ConnectionManager, + remoteStateConfig: BundleRemoteState + ): BundleResourceExplorerTreeNode[] { + const jobs = remoteStateConfig?.resources?.jobs; + if (jobs === undefined) { + return []; + } + + return Object.keys(jobs).map((jobKey) => { + return new JobTreeNode( + context, + bundleRunStatusManager, + connectionManager, + `jobs.${jobKey}`, + jobs[jobKey], + undefined + ); + }); + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineRunStatusTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineRunStatusTreeNode.ts new file mode 100644 index 000000000..4ae26c45e --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineRunStatusTreeNode.ts @@ -0,0 +1,148 @@ +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {TreeItemCollapsibleState} from "vscode"; +import {ContextUtils, RunStateUtils} from "./utils"; +import {SimplifiedRunState, sentenceCase} from "./utils/RunStateUtils"; +import {GetUpdateResponse} from "@databricks/databricks-sdk/dist/apis/pipelines"; +import {PipelineRunStatus} from "../../bundle/run/PipelineRunStatus"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; + +function getSimplifiedUpdateState( + update?: GetUpdateResponse["update"] +): SimplifiedRunState { + if (update?.state === undefined) { + return "Unknown"; + } + + switch (update.state) { + case "RESETTING": + case "CREATED": + case "QUEUED": + case "INITIALIZING": + case "SETTING_UP_TABLES": + case "WAITING_FOR_RESOURCES": + return "Pending"; + case "RUNNING": + return "Running"; + case "COMPLETED": + return "Success"; + case "FAILED": + return "Failed"; + case "CANCELED": + return "Cancelled"; + case "STOPPING": + return "Terminating"; + default: + return "Unknown"; + } +} + +export class PipelineRunStatusTreeNode + implements BundleResourceExplorerTreeNode +{ + readonly type = "pipeline_run_status"; + private get update() { + return this.runMonitor?.data?.update; + } + public get url() { + if (this.type !== this.type) { + return undefined; + } + const host = this.connectionManager.databricksWorkspace?.host; + if ( + host === undefined || + this.update?.pipeline_id === undefined || + this.update?.update_id === undefined + ) { + return undefined; + } + return `${host.toString()}#joblist/pipelines/${ + this.update.pipeline_id + }/updates/${this.update.update_id}`; + } + + constructor( + private readonly connectionManager: ConnectionManager, + private readonly runMonitor: PipelineRunStatus, + public parent?: BundleResourceExplorerTreeNode + ) {} + + getChildren(): BundleResourceExplorerTreeNode[] { + if (this.update === undefined) { + return []; + } + const children: BundleResourceExplorerTreeNode[] = []; + + if (this.update.cause) { + children.push( + new TreeItemTreeNode( + { + label: "Cause", + description: this.update.cause, + contextValue: "update_cause", + }, + this + ) + ); + } + + if (this.update.creation_time) { + children.push( + new TreeItemTreeNode( + { + label: "Start Time", + description: RunStateUtils.humaniseDate( + this.update.creation_time + ), + contextValue: "start_time", + }, + this + ) + ); + } + + return children; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + const runMonitorRunStateTreeItem = + RunStateUtils.getTreeItemFromRunMonitorStatus( + this.type, + this.url, + this.runMonitor + ); + + if (runMonitorRunStateTreeItem) { + return runMonitorRunStateTreeItem; + } + + if (this.update === undefined) { + return { + label: "Run Status", + iconPath: RunStateUtils.getThemeIconForStatus("Unknown"), + description: "Run status not available", + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + }), + collapsibleState: TreeItemCollapsibleState.None, + }; + } + + const status = getSimplifiedUpdateState(this.update); + const icon = RunStateUtils.getThemeIconForStatus(status); + + return { + label: "Run Status", + iconPath: icon, + description: sentenceCase(this.update.state), + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + hasUrl: this.url !== undefined, + }), + collapsibleState: TreeItemCollapsibleState.Collapsed, + }; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineTreeNode.ts new file mode 100644 index 000000000..ae755f5e6 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/PipelineTreeNode.ts @@ -0,0 +1,129 @@ +import {BundleRemoteState} from "../../bundle/models/BundleRemoteStateModel"; +import { + BundleResourceExplorerResource, + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {BundleRunStatusManager} from "../../bundle/run/BundleRunStatusManager"; +import {ContextUtils} from "./utils"; +import {DecorationUtils} from "../utils"; + +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {PipelineRunStatus} from "../../bundle/run/PipelineRunStatus"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; +import {PipelineRunStatusTreeNode} from "./PipelineRunStatusTreeNode"; + +export class PipelineTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "pipelines"; + get url(): string | undefined { + const host = this.connectionManager.databricksWorkspace?.host; + + if (!host || !this.data.id) { + return undefined; + } + + return `${host.toString()}#joblist/pipelines/${this.data.id}`; + } + + constructor( + private readonly bundleRunStatusManager: BundleRunStatusManager, + private readonly connectionManager: ConnectionManager, + public readonly resourceKey: string, + public readonly data: BundleResourceExplorerResource<"pipelines">, + public parent?: BundleResourceExplorerTreeNode + ) {} + + isRunning(resourceKey: string) { + const runner = this.bundleRunStatusManager.runStatuses.get(resourceKey); + return runner?.runState === "running" || runner?.runState === "unknown"; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + const isRunning = this.isRunning(this.resourceKey); + + return { + label: this.data.name, + contextValue: ContextUtils.getContextString({ + resourceType: this.type, + running: isRunning, + hasUrl: this.url !== undefined, + cancellable: isRunning, + nodeType: this.type, + modifiedStatus: this.data.modified_status, + }), + resourceUri: DecorationUtils.getModifiedStatusDecoration( + this.data.name ?? this.resourceKey, + this.data.modified_status + ), + collapsibleState: DecorationUtils.getCollapsibleState( + isRunning, + this.data.modified_status + ), + }; + } + + getChildren(): BundleResourceExplorerTreeNode[] { + const children: BundleResourceExplorerTreeNode[] = []; + const runMonitor = this.bundleRunStatusManager.runStatuses.get( + this.resourceKey + ) as PipelineRunStatus | undefined; + if (runMonitor) { + children.push( + new PipelineRunStatusTreeNode( + this.connectionManager, + runMonitor, + this + ) + ); + } + + if (this.data.catalog) { + children.push( + new TreeItemTreeNode( + { + label: "Catalog", + description: this.data.catalog, + contextValue: "catalog", + }, + this + ) + ); + } + + if (this.data.target) { + children.push( + new TreeItemTreeNode( + { + label: "Target", + description: this.data.target, + contextValue: "target", + }, + this + ) + ); + } + + return children; + } + + static getRoots( + bundleRunStatusManager: BundleRunStatusManager, + connectionManager: ConnectionManager, + remoteStateConfig: BundleRemoteState + ): BundleResourceExplorerTreeNode[] { + const pipelines = remoteStateConfig?.resources?.pipelines; + if (pipelines === undefined) { + return []; + } + + return Object.keys(pipelines).map((pipelineKey) => { + return new PipelineTreeNode( + bundleRunStatusManager, + connectionManager, + `pipelines.${pipelineKey}`, + pipelines[pipelineKey], + undefined + ); + }); + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/ResourceTypeHeaderTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/ResourceTypeHeaderTreeNode.ts new file mode 100644 index 000000000..234e59300 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/ResourceTypeHeaderTreeNode.ts @@ -0,0 +1,101 @@ +import path from "path"; +import {BundleRemoteState} from "../../bundle/models/BundleRemoteStateModel"; +import {BundleRunStatusManager} from "../../bundle/run/BundleRunStatusManager"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {JobTreeNode} from "./JobTreeNode"; +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {ExtensionContext, TreeItemCollapsibleState} from "vscode"; +import {PipelineTreeNode} from "./PipelineTreeNode"; + +function humaniseResourceType(type: BundleResourceExplorerTreeNode["type"]) { + switch (type) { + case "pipelines": + return "Pipelines"; + case "jobs": + return "Workflows"; + default: + return type; + } +} +export class ResourceTypeHeaderTreeNode + implements BundleResourceExplorerTreeNode +{ + readonly type = "resource_type_header"; + constructor( + private readonly context: ExtensionContext, + private readonly resourceType: BundleResourceExplorerTreeNode["type"], + public readonly children: BundleResourceExplorerTreeNode[], + public parent?: BundleResourceExplorerTreeNode + ) { + this.children.forEach((child) => (child.parent = this)); + } + + private getIconPath(resourceType: string) { + return { + dark: this.context.asAbsolutePath( + path.join( + "resources", + "dark", + "resource-explorer", + `${resourceType}.svg` + ) + ), + light: this.context.asAbsolutePath( + path.join( + "resources", + "light", + "resource-explorer", + `${resourceType}.svg` + ) + ), + }; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + return { + label: humaniseResourceType(this.resourceType), + iconPath: this.getIconPath(this.resourceType), + contextValue: `${this.resourceType}-header`, + collapsibleState: TreeItemCollapsibleState.Expanded, + }; + } + + getChildren(): BundleResourceExplorerTreeNode[] { + return this.children; + } + + static getRoots( + context: ExtensionContext, + bundleRunStatusManager: BundleRunStatusManager, + connectionManager: ConnectionManager, + bundleRemoteState: BundleRemoteState + ) { + const roots: BundleResourceExplorerTreeNode[] = []; + + const jobs = JobTreeNode.getRoots( + context, + bundleRunStatusManager, + connectionManager, + bundleRemoteState + ); + if (jobs.length > 0) { + roots.push(new ResourceTypeHeaderTreeNode(context, "jobs", jobs)); + } + + const pipelines = PipelineTreeNode.getRoots( + bundleRunStatusManager, + connectionManager, + bundleRemoteState + ); + if (pipelines.length > 0) { + roots.push( + new ResourceTypeHeaderTreeNode(context, "pipelines", pipelines) + ); + } + + return roots; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskHeaderTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskHeaderTreeNode.ts new file mode 100644 index 000000000..26aebb913 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskHeaderTreeNode.ts @@ -0,0 +1,34 @@ +import {TaskTreeNode} from "./TaskTreeNode"; +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {TreeItemCollapsibleState} from "vscode"; + +export class TaskHeaderTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "task_header"; + + constructor( + public readonly children: TaskTreeNode[], + public readonly parent: BundleResourceExplorerTreeNode + ) { + this.children.forEach((child) => { + child.parent = this; + }); + } + + getTreeItem(): BundleResourceExplorerTreeItem { + return { + label: "Tasks", + contextValue: "task_header", + collapsibleState: + this.children.length > 0 + ? TreeItemCollapsibleState.Expanded + : TreeItemCollapsibleState.None, + }; + } + + getChildren(): BundleResourceExplorerTreeNode[] { + return this.children; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskRunStatusTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskRunStatusTreeNode.ts new file mode 100644 index 000000000..f5cb10f79 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskRunStatusTreeNode.ts @@ -0,0 +1,94 @@ +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {TreeItemCollapsibleState} from "vscode"; +import {ContextUtils, JobRunStateUtils, RunStateUtils} from "./utils"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {jobs} from "@databricks/databricks-sdk"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; +import {TaskTreeNode} from "./TaskTreeNode"; + +export class TaskRunStatusTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "task_run_status"; + get url() { + if (this.type !== this.type) { + return undefined; + } + const host = this.connectionManager.databricksWorkspace?.host; + if ( + host === undefined || + this.runDetails.run_id === undefined || + this.jobId === undefined + ) { + return undefined; + } + + return `${host.toString()}#job/${this.jobId}/run/${ + this.runDetails.run_id + }`; + } + + constructor( + private readonly connectionManager: ConnectionManager, + public readonly runDetails: jobs.RunTask, + public readonly parent: TaskTreeNode, + public readonly jobId?: string + ) {} + + getChildren(): BundleResourceExplorerTreeNode[] { + const children: BundleResourceExplorerTreeNode[] = []; + + if (this.runDetails.state?.state_message) { + children.push( + new TreeItemTreeNode( + { + label: "State Message", + description: this.runDetails.state?.state_message, + tooltip: this.runDetails.state?.state_message, + contextValue: "state_message", + }, + this + ) + ); + } + children.push( + new TreeItemTreeNode( + { + label: "Start Time", + description: RunStateUtils.humaniseDate( + this.runDetails.start_time + ), + contextValue: "start_time", + }, + this + ), + new TreeItemTreeNode( + { + label: "Duration", + description: RunStateUtils.humaniseDuration( + this.runDetails.execution_duration + ), + contextValue: "end_time", + }, + this + ) + ); + return children; + } + + getTreeItem(): BundleResourceExplorerTreeItem { + const status = JobRunStateUtils.getSimplifiedRunState(this.runDetails); + const icon = RunStateUtils.getThemeIconForStatus(status); + return { + label: "Run Status", + iconPath: icon, + description: status, + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + hasUrl: this.url !== undefined, + }), + collapsibleState: TreeItemCollapsibleState.Collapsed, + }; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskTreeNode.ts new file mode 100644 index 000000000..42bcf9f38 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/TaskTreeNode.ts @@ -0,0 +1,164 @@ +import path from "path"; +import { + BundleResourceExplorerResource, + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "./types"; +import {ExtensionContext, TreeItemCollapsibleState, ThemeIcon} from "vscode"; +import {JobRunStatus} from "../../bundle/run/JobRunStatus"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {jobs} from "@databricks/databricks-sdk"; +import {TaskRunStatusTreeNode} from "./TaskRunStatusTreeNode"; +import {ContextUtils} from "./utils"; + +type Task = Required>["tasks"][number]; +type TaskType = keyof { + [k in keyof Required as k extends `${string}_task` ? k : never]: k; +}; + +export class TaskTreeNode implements BundleResourceExplorerTreeNode { + readonly type = "task"; + get taskKey(): string { + return this.data.task_key; + } + get runDetails(): jobs.RunTask | undefined { + return this.runMonitor?.data?.tasks?.find( + (t) => t.task_key === this.taskKey + ); + } + + get url(): string | undefined { + const host = this.connectionManager.databricksWorkspace?.host; + if (!host || !this.jobId || !this.taskKey) { + return undefined; + } + + return `${host.toString()}#job/${this.jobId}/tasks/task/${ + this.taskKey + }`; + } + constructor( + private readonly context: ExtensionContext, + private readonly connectionManager: ConnectionManager, + public readonly data: Task, + public readonly jobResourceKey: string, + public readonly resourceKey: string, + public parent: BundleResourceExplorerTreeNode, + public readonly jobId?: string, + public readonly runMonitor?: JobRunStatus + ) {} + + private getIconPathForType(taskType: string) { + return { + dark: this.context.asAbsolutePath( + path.join( + "resources", + "dark", + "resource-explorer", + `${taskType}.svg` + ) + ), + light: this.context.asAbsolutePath( + path.join( + "resources", + "light", + "resource-explorer", + `${taskType}.svg` + ) + ), + }; + } + + get isRunning() { + return ( + this.runMonitor?.runId !== undefined && + this.runDetails !== undefined + ); + } + + get taskType(): TaskType | undefined { + return Object.keys(this.data).find( + (k) => + k.endsWith("_task") && this.data[k as keyof Task] !== undefined + ) as TaskType | undefined; + } + + get humanisedTaskType() { + if (this.taskType === undefined) { + return undefined; + } + + return this.taskType + .replace("_task", "") + .split("_") + .map((word) => word[0].toUpperCase() + word.slice(1)) + .join(" "); + } + + getTreeItem(): BundleResourceExplorerTreeItem { + let iconPath: BundleResourceExplorerTreeItem["iconPath"] = undefined; + switch (this.taskType) { + case "pipeline_task": + iconPath = this.getIconPathForType("pipelines"); + break; + case "spark_python_task": + iconPath = this.getIconPathForType("python"); + break; + case "notebook_task": + iconPath = new ThemeIcon("notebook"); + break; + case "condition_task": + iconPath = this.getIconPathForType("fork"); + break; + case "run_job_task": + iconPath = this.getIconPathForType("jobs"); + break; + case "python_wheel_task": + iconPath = this.getIconPathForType("python"); + break; + case "dbt_task": + case "spark_submit_task": + case "sql_task": + case "spark_jar_task": + break; + default: + break; + } + + return { + label: this.data.task_key, + id: `${this.data.task_key}-${this.jobId}-${this.jobResourceKey}`, + description: this.humanisedTaskType, + tooltip: this.data.description, + iconPath: iconPath, + contextValue: ContextUtils.getContextString({ + nodeType: this.type, + running: this.isRunning, + hasUrl: this.url !== undefined, + cancellable: false, + }), + collapsibleState: + this.runMonitor?.runId !== undefined + ? TreeItemCollapsibleState.Expanded + : TreeItemCollapsibleState.None, + }; + } + + getChildren(): BundleResourceExplorerTreeNode[] { + if ( + this.runMonitor?.runId === undefined || + this.runDetails === undefined + ) { + return []; + } + + return [ + new TaskRunStatusTreeNode( + this.connectionManager, + this.runDetails, + this, + this.jobId + ), + ]; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/types.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/types.ts new file mode 100644 index 000000000..a564dbf6c --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/types.ts @@ -0,0 +1,25 @@ +import {TreeItem} from "vscode"; +import {BundleRemoteState} from "../../bundle/models/BundleRemoteStateModel"; +import {Resource, ResourceKey} from "../../bundle/types"; + +export type BundleResourceExplorerResourceKey = ResourceKey; +export type BundleResourceExplorerResource< + K extends BundleResourceExplorerResourceKey, +> = Resource; + +export interface BundleResourceExplorerTreeItem extends TreeItem {} + +export interface BundleResourceExplorerTreeNode { + type: + | BundleResourceExplorerResourceKey + | "treeItem" + | "task_run_status" + | "pipeline_run_status" + | "resource_type_header" + | "task" + | "job_run_status" + | "task_header"; + parent?: BundleResourceExplorerTreeNode; + getTreeItem(): BundleResourceExplorerTreeItem; + getChildren(): BundleResourceExplorerTreeNode[]; +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/ContextUtils.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/ContextUtils.ts new file mode 100644 index 000000000..549ba0e59 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/ContextUtils.ts @@ -0,0 +1,47 @@ +import {BundleResourceModifiedStatus} from "../../../bundle/models/BundleRemoteStateModel"; +import {RUNNABLE_BUNDLE_RESOURCES} from "../BundleCommands"; +import { + BundleResourceExplorerResourceKey, + BundleResourceExplorerTreeNode, +} from "../types"; + +type BundleTreeItemContext = { + resourceType?: BundleResourceExplorerResourceKey; + nodeType: BundleResourceExplorerTreeNode["type"]; + running?: boolean; + cancellable?: boolean; + hasUrl?: boolean; + modifiedStatus?: BundleResourceModifiedStatus; +}; + +export function getContextString(context: BundleTreeItemContext) { + const parts = ["databricks", "bundle"]; + if (context.resourceType) { + parts.push(`resource=${context.resourceType}`); + + if ( + (RUNNABLE_BUNDLE_RESOURCES as string[]).includes( + context.resourceType + ) && + !context.running && + context.modifiedStatus !== "deleted" + ) { + parts.push("runnable"); + } + } + + if (context.running) { + parts.push("running"); + } + + if (context.cancellable) { + parts.push("cancellable"); + } + + if (context.hasUrl) { + parts.push("has-url"); + } + + parts.push(`nodeType=${context.nodeType}`); + return parts.join("."); +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/JobRunStateUtils.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/JobRunStateUtils.ts new file mode 100644 index 000000000..bcbe3b4d8 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/JobRunStateUtils.ts @@ -0,0 +1,48 @@ +import {Run} from "@databricks/databricks-sdk/dist/apis/jobs"; +import {SimplifiedRunState} from "./RunStateUtils"; + +export function getSimplifiedRunState(run?: Run): SimplifiedRunState { + if (run?.state?.life_cycle_state === undefined) { + return "Unknown"; + } + + switch (run.state.life_cycle_state) { + case "INTERNAL_ERROR": + return "Failed"; + case "SKIPPED": + return "Skipped"; + case "WAITING_FOR_RETRY": + case "BLOCKED": + case "PENDING": + return "Pending"; + case "RUNNING": + if (run.state.user_cancelled_or_timedout) { + return "Terminating"; + } + return "Running"; + case "TERMINATING": + return "Terminating"; + case "TERMINATED": + if (run.state.user_cancelled_or_timedout) { + return "Cancelled"; + } + switch (run.state.result_state) { + case "SUCCESS": + case "SUCCESS_WITH_FAILURES": + return "Success"; + case "MAXIMUM_CONCURRENT_RUNS_REACHED": + case "FAILED": + case "TIMEDOUT": + return "Failed"; + case "UPSTREAM_CANCELED": + case "UPSTREAM_FAILED": + case "EXCLUDED": + return "Skipped"; + case "CANCELED": + return "Cancelled"; + } + return "Terminated"; + } + + return "Unknown"; +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/RunStateUtils.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/RunStateUtils.ts new file mode 100644 index 000000000..3fe2d156b --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/RunStateUtils.ts @@ -0,0 +1,116 @@ +import {ThemeColor, ThemeIcon, TreeItemCollapsibleState} from "vscode"; +import {DateUtils} from "../../../utils"; +import {BundleRunStatus} from "../../../bundle/run/BundleRunStatus"; +import {ContextUtils} from "."; +import { + BundleResourceExplorerTreeItem, + BundleResourceExplorerTreeNode, +} from "../types"; + +export type SimplifiedRunState = + | "Terminated" + | "Failed" + | "Skipped" + | "Pending" + | "Running" + | "Terminating" + | "Cancelled" + | "Success" + | "Unknown" + | "Timeout"; + +export function humaniseDate(timestamp?: number) { + if (timestamp === undefined) { + return undefined; + } + const date = new Date(timestamp); + return DateUtils.toString(date); +} + +export function humaniseDuration(ms?: number) { + if (ms === undefined) { + return undefined; + } + const seconds = Math.floor(ms / 1000); + if (seconds < 60) { + return `${seconds}s`; + } + const minutes = Number((seconds / 60).toFixed(2)); + if (minutes < 60) { + return `${minutes}m`; + } + + const hours = Number((minutes / 60).toFixed(2)); + return `${hours}h`; +} + +export function getThemeIconForStatus(status: SimplifiedRunState): ThemeIcon { + switch (status) { + case "Failed": + return new ThemeIcon( + "testing-error-icon", + new ThemeColor("problemsErrorIcon.foreground") + ); + case "Skipped": + return new ThemeIcon("testing-skipped-icon"); + case "Pending": + return new ThemeIcon("watch"); + case "Running": + return new ThemeIcon("sync~spin", new ThemeColor("charts.green")); + case "Terminating": + return new ThemeIcon("sync-ignored", new ThemeColor("charts.red")); + case "Terminated": + case "Cancelled": + return new ThemeIcon("circle-slash"); + case "Success": + return new ThemeIcon("check-all", new ThemeColor("charts.green")); + case "Timeout": + return new ThemeIcon( + "warning", + new ThemeColor("problemsWarningIcon.foreground") + ); + default: + return new ThemeIcon("question"); + } +} + +export function sentenceCase(str?: string, sep: string = "_") { + if (str === undefined) { + return undefined; + } + + return (str.charAt(0).toUpperCase() + str.slice(1).toLowerCase()) + .split(sep) + .join(" "); +} + +export function getTreeItemFromRunMonitorStatus( + type: BundleResourceExplorerTreeNode["type"], + url?: string, + runMonitor?: BundleRunStatus +): BundleResourceExplorerTreeItem | undefined { + if (runMonitor?.runState === "timeout") { + return { + label: "Run Status", + iconPath: getThemeIconForStatus("Timeout"), + description: "Timeout while fetching run status", + contextValue: ContextUtils.getContextString({ + nodeType: type, + }), + collapsibleState: TreeItemCollapsibleState.None, + }; + } + + if (runMonitor?.runState === "cancelled") { + return { + label: "Run Status", + iconPath: getThemeIconForStatus("Cancelled"), + description: "Cancelled", + contextValue: ContextUtils.getContextString({ + nodeType: type, + hasUrl: url !== undefined, + }), + collapsibleState: TreeItemCollapsibleState.None, + }; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/index.ts b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/index.ts new file mode 100644 index 000000000..a8d029386 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-resource-explorer/utils/index.ts @@ -0,0 +1,3 @@ +export * as JobRunStateUtils from "./JobRunStateUtils"; +export * as RunStateUtils from "./RunStateUtils"; +export * as ContextUtils from "./ContextUtils"; diff --git a/packages/databricks-vscode/src/ui/bundle-variables/BundleVariableTreeDataProvider.ts b/packages/databricks-vscode/src/ui/bundle-variables/BundleVariableTreeDataProvider.ts new file mode 100644 index 000000000..da2a64a4b --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-variables/BundleVariableTreeDataProvider.ts @@ -0,0 +1,60 @@ +import {EventEmitter, TreeDataProvider, TreeItem} from "vscode"; +import { + BundleVariable, + BundleVariableModel, +} from "../../bundle/models/BundleVariableModel"; +import {BundleVariableTreeNode} from "./types"; +import {LookupVariableTreeNode} from "./LookupVariableTreeNode"; +import {VariableTreeNode} from "./VariableTreeNode"; + +export class BundleVariableTreeDataProvider + implements TreeDataProvider +{ + constructor(private readonly bundleVariableModel: BundleVariableModel) { + this.bundleVariableModel.onDidChangeKey("variables")(async () => { + this.onDidChangeTreeDataEmitter.fire(); + }); + } + private readonly onDidChangeTreeDataEmitter = new EventEmitter< + | void + | BundleVariableTreeNode + | BundleVariableTreeNode[] + | null + | undefined + >(); + onDidChangeTreeData = this.onDidChangeTreeDataEmitter.event; + + getTreeItem( + element: BundleVariableTreeNode + ): TreeItem | Thenable { + return element.getTreeItem(); + } + + async getChildren(element?: BundleVariableTreeNode | undefined) { + if (element !== undefined) { + return element.getChildren(); + } + + const variables: Record = + (await this.bundleVariableModel.get("variables")) ?? {}; + + const children: BundleVariableTreeNode[] = []; + for (const key in variables) { + const variable = variables[key]; + if (variable === undefined) { + continue; + } + + if (variable.lookup !== undefined) { + children.push( + new LookupVariableTreeNode(key, variable, undefined) + ); + continue; + } + + children.push(new VariableTreeNode(key, variable, undefined)); + } + + return children; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-variables/LookupVariableTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-variables/LookupVariableTreeNode.ts new file mode 100644 index 000000000..b48c95e62 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-variables/LookupVariableTreeNode.ts @@ -0,0 +1,39 @@ +import {TreeItemCollapsibleState} from "vscode"; +import {BundleVariable} from "../../bundle/models/BundleVariableModel"; +import {BundleVariableTreeItem, BundleVariableTreeNode} from "./types"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; + +export class LookupVariableTreeNode implements BundleVariableTreeNode { + constructor( + public readonly key: string, + public readonly value: BundleVariable, + public readonly parent?: BundleVariableTreeNode + ) {} + + getTreeItem(): BundleVariableTreeItem { + const lookup = this.value.lookup as any; + const lookupValue = Object.values(lookup).find( + (v) => v !== undefined + ) as string | undefined; + + return { + label: this.key, + description: lookupValue, + collapsibleState: TreeItemCollapsibleState.Collapsed, + }; + } + + getChildren(): BundleVariableTreeNode[] { + const lookup = this.value.lookup as any; + const lookupKey = Object.keys(lookup).find( + (key) => lookup[key] !== undefined + ); + + return [ + new TreeItemTreeNode({ + label: lookupKey, + description: this.value.valueInTarget, + }), + ]; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-variables/VariableTreeNode.ts b/packages/databricks-vscode/src/ui/bundle-variables/VariableTreeNode.ts new file mode 100644 index 000000000..515417a86 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-variables/VariableTreeNode.ts @@ -0,0 +1,37 @@ +import {TreeItemCollapsibleState} from "vscode"; +import {BundleVariable} from "../../bundle/models/BundleVariableModel"; +import {BundleVariableTreeItem, BundleVariableTreeNode} from "./types"; +import {TreeItemTreeNode} from "../TreeItemTreeNode"; + +export class VariableTreeNode implements BundleVariableTreeNode { + constructor( + public readonly key: string, + public readonly value: BundleVariable, + public readonly parent?: BundleVariableTreeNode + ) {} + + getTreeItem(): BundleVariableTreeItem { + return { + label: this.key, + description: + this.value.vscodeOverrideValue ?? + this.value.valueInTarget ?? + "", + collapsibleState: this.value.valueInTarget + ? TreeItemCollapsibleState.Collapsed + : TreeItemCollapsibleState.None, + }; + } + + getChildren(): BundleVariableTreeNode[] { + if (this.value.valueInTarget !== undefined) { + return [ + new TreeItemTreeNode({ + label: "Default", + description: this.value.default ?? this.value.valueInTarget, + }), + ]; + } + return []; + } +} diff --git a/packages/databricks-vscode/src/ui/bundle-variables/types.ts b/packages/databricks-vscode/src/ui/bundle-variables/types.ts new file mode 100644 index 000000000..fd816a291 --- /dev/null +++ b/packages/databricks-vscode/src/ui/bundle-variables/types.ts @@ -0,0 +1,12 @@ +import {TreeItem} from "vscode"; +import {BundleVariable} from "../../bundle/models/BundleVariableModel"; + +export interface BundleVariableTreeItem extends TreeItem {} + +export interface BundleVariableTreeNode { + readonly key?: string; + readonly value?: BundleVariable; + parent?: BundleVariableTreeNode; + getTreeItem(): BundleVariableTreeItem; + getChildren(): BundleVariableTreeNode[]; +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/AuthTypeComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/AuthTypeComponent.ts new file mode 100644 index 000000000..21ab7e4ec --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/AuthTypeComponent.ts @@ -0,0 +1,111 @@ +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {ThemeIcon, ThemeColor} from "vscode"; +import {getProfilesForHost} from "../../configuration/LoginWizard"; +import {CliWrapper} from "../../cli/CliWrapper"; +import {LabelUtils} from "../utils"; + +export const AUTH_TYPE_SWITCH_ID = "AUTH-TYPE"; +export const AUTH_TYPE_LOGIN_ID = "LOGIN"; + +function getContextValue(key: string) { + return `databricks.configuration.authType.${key}`; +} + +export class AuthTypeComponent extends BaseComponent { + constructor( + private readonly connectionManager: ConnectionManager, + private readonly configModel: ConfigModel, + private readonly cli: CliWrapper + ) { + super(); + this.disposables.push( + this.connectionManager.onDidChangeState(() => { + this.onDidChangeEmitter.fire(); + }), + this.configModel.onDidChangeTarget(() => { + this.onDidChangeEmitter.fire(); + }) + ); + } + + private async getRoot(): Promise { + if (this.configModel.target === undefined) { + return []; + } + + const authProvider = + this.connectionManager.databricksWorkspace?.authProvider; + + if (this.connectionManager.state === "CONNECTING") { + return [ + { + label: "Connecting to the workspace", + iconPath: new ThemeIcon("sync~spin"), + }, + ]; + } + + if (authProvider === undefined) { + const host = await this.configModel.get("host"); + if (host === undefined) { + return []; + } + + const profiles = await getProfilesForHost(host, this.cli); + let label = "Login to Databricks"; + if (profiles.length > 1) { + label = + "Multiple login profiles available. Click to select a profile."; + } + return [ + { + label: LabelUtils.highlightedLabel(label), + iconPath: new ThemeIcon( + "account", + new ThemeColor("notificationsErrorIcon.foreground") + ), + contextValue: getContextValue("none"), + id: AUTH_TYPE_SWITCH_ID, + command: { + title: "Sign in to Databricks", + command: "databricks.connection.configureLogin", + arguments: [{id: AUTH_TYPE_LOGIN_ID}], + }, + }, + ]; + } + + const config = + (await this.configModel.get("authProfile")) ?? + (await this.configModel.get("authParams")); + if (config === undefined) { + // This case can never happen. This is just to make ts happy. + return []; + } + + return [ + { + label: "Auth Type", + iconPath: new ThemeIcon( + "account", + new ThemeColor("debugIcon.startForeground") + ), + description: authProvider.describe(), + contextValue: getContextValue(authProvider.authType), + id: AUTH_TYPE_SWITCH_ID, + }, + ]; + } + public async getChildren( + parent?: ConfigurationTreeItem + ): Promise { + if (parent === undefined) { + return this.getRoot(); + } + + return []; + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/BaseComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/BaseComponent.ts new file mode 100644 index 000000000..f33465cf8 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/BaseComponent.ts @@ -0,0 +1,17 @@ +import {Disposable, EventEmitter} from "vscode"; +import {ConfigurationTreeItem} from "./types"; + +export abstract class BaseComponent implements Disposable { + protected disposables: Disposable[] = []; + protected onDidChangeEmitter = new EventEmitter(); + public readonly onDidChange = this.onDidChangeEmitter.event; + constructor() {} + + public abstract getChildren( + parent?: ConfigurationTreeItem + ): Promise; + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/BundleTargetComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/BundleTargetComponent.ts new file mode 100644 index 000000000..4a9161217 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/BundleTargetComponent.ts @@ -0,0 +1,132 @@ +import {ThemeIcon, ThemeColor, TreeItemCollapsibleState, window} from "vscode"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {UrlError} from "../../utils/urlUtils"; +import {LabelUtils} from "../utils"; +import {humaniseMode} from "../utils/BundleUtils"; + +const TREE_ICON_ID = "TARGET"; + +function getTreeIconId(key: string) { + return `${TREE_ICON_ID}.${key}`; +} + +export class BundleTargetComponent extends BaseComponent { + constructor(private readonly configModel: ConfigModel) { + super(); + this.disposables.push( + this.configModel.onDidChangeTarget(() => { + this.onDidChangeEmitter.fire(); + }) + ); + } + + private async getRoot(): Promise { + const target = this.configModel.target; + if (target === undefined) { + return [ + { + label: LabelUtils.highlightedLabel( + "Select a bundle target" + ), + id: TREE_ICON_ID, + iconPath: new ThemeIcon( + "plug", + new ThemeColor("notificationsErrorIcon.foreground") + ), + contextValue: "databricks.configuration.target.none", + collapsibleState: TreeItemCollapsibleState.None, + command: { + title: "Select a bundle target", + command: "databricks.connection.bundle.selectTarget", + }, + }, + ]; + } + + try { + const humanisedMode = humaniseMode( + await this.configModel.get("mode") + ); + if (humanisedMode === undefined) { + window.showErrorMessage( + `Could not find "mode" for target ${target}` + ); + return []; + } + + if ((await this.configModel.get("host")) === undefined) { + throw new UrlError("Host not found"); + } + + return [ + { + label: "Target", + id: TREE_ICON_ID, + iconPath: new ThemeIcon( + "target", + new ThemeColor("debugIcon.startForeground") + ), + description: target, + contextValue: `databricks.configuration.target.${humanisedMode.toLocaleLowerCase()}}`, + collapsibleState: TreeItemCollapsibleState.Collapsed, + }, + ]; + } catch (e) { + if (e instanceof UrlError) { + return [ + { + label: LabelUtils.highlightedLabel( + `Invalid host for target ${target}` + ), + id: TREE_ICON_ID, + iconPath: new ThemeIcon( + "target", + new ThemeColor("debugIcon.startForeground") + ), + contextValue: `databricks.configuration.target.error`, + collapsibleState: TreeItemCollapsibleState.None, + command: { + title: "Select a bundle target", + command: + "databricks.connection.bundle.selectTarget", + }, + }, + ]; + } + + throw e; + } + } + + public async getChildren( + parent?: ConfigurationTreeItem + ): Promise { + if (parent === undefined) { + return this.getRoot(); + } + + if (parent.id !== TREE_ICON_ID) { + return []; + } + + const host = await this.configModel.get("host"); + + return [ + { + label: "Host", + id: getTreeIconId("host"), + description: host?.toString(), + collapsibleState: TreeItemCollapsibleState.None, + url: host?.toString(), + }, + { + label: "Mode", + id: getTreeIconId("mode"), + description: humaniseMode(await this.configModel.get("mode")), + collapsibleState: TreeItemCollapsibleState.None, + }, + ]; + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/ClusterComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/ClusterComponent.ts new file mode 100644 index 000000000..716042383 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/ClusterComponent.ts @@ -0,0 +1,228 @@ +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {BaseComponent} from "./BaseComponent"; +import { + TreeItem, + TreeItemCollapsibleState, + ThemeIcon, + ThemeColor, + TreeItemCheckboxState, +} from "vscode"; +import {ConfigurationTreeItem} from "./types"; +import {Cluster} from "../../sdk-extensions"; +import {onError} from "../../utils/onErrorDecorator"; +import {DecorationUtils} from "../utils"; +import {LabelUtils} from "../utils"; + +const TREE_ICON_ID = "CLUSTER"; +export const CLUSTER_OVERRIDE_CHECKBOX_ID = "OVERRIDE_CLUSTER"; + +function getContextValue(key: string) { + return `databricks.configuration.cluster.${key}`; +} + +function getTreeItemsForClusterState(cluster: Cluster) { + let icon, contextValue; + switch (cluster.state) { + case "RESIZING": + case "RUNNING": + icon = new ThemeIcon("debug-start"); + contextValue = getContextValue("running"); + break; + + case "RESTARTING": + case "PENDING": + icon = new ThemeIcon( + "sync~spin", + new ThemeColor("debugIcon.startForeground") + ); + contextValue = getContextValue("pending"); + break; + + case "TERMINATING": + icon = new ThemeIcon( + "sync~spin", + new ThemeColor("notificationsErrorIcon.foreground") + ); + contextValue = getContextValue("terminating"); + break; + + case "TERMINATED": + icon = new ThemeIcon( + "stop-circle", + new ThemeColor("notificationsErrorIcon.foreground") + ); + contextValue = getContextValue("terminated"); + break; + + case "ERROR": + icon = new ThemeIcon( + "testing-error-icon", + new ThemeColor("notificationsErrorIcon.foreground") + ); + contextValue = getContextValue("error"); + break; + + default: + icon = new ThemeIcon("question"); + contextValue = getContextValue("unknown"); + break; + } + + return {icon, contextValue}; +} + +export class ClusterComponent extends BaseComponent { + constructor( + private readonly connectionManager: ConnectionManager, + private readonly configModel: ConfigModel + ) { + super(); + this.disposables.push( + this.connectionManager.onDidChangeCluster(() => { + this.onDidChangeEmitter.fire(); + }), + this.connectionManager.onDidChangeState(() => { + this.onDidChangeEmitter.fire(); + }), + this.configModel.onDidChangeKey("useClusterOverride")(async () => { + this.onDidChangeEmitter.fire(); + }) + ); + } + + @onError({popup: true}) + private async getRoot(): Promise { + const config = await this.configModel.get("clusterId"); + + if (config === undefined) { + // Cluster is not set in bundle and override + // We are logged in -> Select cluster prompt + return [ + { + label: LabelUtils.highlightedLabel("Select a cluster"), + collapsibleState: TreeItemCollapsibleState.None, + contextValue: getContextValue("none"), + iconPath: new ThemeIcon( + "server", + new ThemeColor("notificationsErrorIcon.foreground") + ), + id: TREE_ICON_ID, + command: { + title: "Select a cluster", + command: "databricks.connection.attachClusterQuickPick", + }, + }, + ]; + } + + // Cluster is set in bundle / override + // We are logged in -> load cluster details + const cluster = this.connectionManager.cluster; + if (cluster === undefined) { + // can never happen. Just need it for typescript type coercing. + return []; + } + const {icon, contextValue} = getTreeItemsForClusterState(cluster); + const url = await cluster.url; + const useClusterOverride = + await this.configModel.get("useClusterOverride"); + const overrideClusterLabel = "Override Jobs cluster in bundle"; + const clusterOverrideTooltip = + "Use the selected cluster for all jobs in the bundle"; + return [ + { + label: "Cluster", + tooltip: url ? undefined : "Created after deploy", + description: cluster.name, + collapsibleState: TreeItemCollapsibleState.Collapsed, + contextValue: url ? `${contextValue}.has-url` : contextValue, + resourceUri: url + ? undefined + : DecorationUtils.getModifiedStatusDecoration( + TREE_ICON_ID, + "created" + ), + iconPath: icon, + id: TREE_ICON_ID, + url, + }, + { + label: useClusterOverride + ? LabelUtils.highlightedLabel(overrideClusterLabel) + : overrideClusterLabel, + checkboxState: { + state: useClusterOverride + ? TreeItemCheckboxState.Checked + : TreeItemCheckboxState.Unchecked, + tooltip: clusterOverrideTooltip, + }, + tooltip: clusterOverrideTooltip, + id: CLUSTER_OVERRIDE_CHECKBOX_ID, + collapsibleState: TreeItemCollapsibleState.None, + }, + ]; + } + + public async getChildren( + parent?: TreeItem + ): Promise { + // Only show cluster details when we are connected and in dev mode. In other modes + // there is no concept of a global interactive cluster + if ( + this.connectionManager.state !== "CONNECTED" || + (await this.configModel.get("mode")) !== "development" + ) { + return []; + } + if (parent === undefined) { + return this.getRoot(); + } + + if (parent.id !== TREE_ICON_ID) { + return []; + } + + // If there is no cluster, we don't have to show cluster details + if (this.connectionManager.cluster === undefined) { + return []; + } + const cluster = this.connectionManager.cluster; + const children: ConfigurationTreeItem[] = [ + { + label: "Cluster ID", + description: cluster.id, + }, + ]; + + children.push( + { + label: "Databricks Runtime", + description: cluster.dbrVersion.join("."), + }, + { + label: "Creator", + description: cluster.details.creator_user_name, + } + ); + + if (cluster.stateMessage && cluster.state !== "RUNNING") { + children.push({ + label: "State", + description: `${cluster.state} - ${cluster.stateMessage}`, + }); + } + + if (cluster.accessMode) { + const description = cluster.isSingleUser() + ? `${cluster.accessMode} - ${cluster.details.single_user_name}` + : `${cluster.accessMode}`; + children.push({ + label: "Access Mode", + description: description, + }); + } + + return children; + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/ConfigurationDataProvider.ts b/packages/databricks-vscode/src/ui/configuration-view/ConfigurationDataProvider.ts new file mode 100644 index 000000000..475463893 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/ConfigurationDataProvider.ts @@ -0,0 +1,121 @@ +import { + Disposable, + Event, + EventEmitter, + TreeDataProvider, + TreeItem, +} from "vscode"; + +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {BundleTargetComponent} from "./BundleTargetComponent"; +import {AuthTypeComponent} from "./AuthTypeComponent"; +import {ClusterComponent} from "./ClusterComponent"; +import {SyncDestinationComponent} from "./SyncDestinationComponent"; +import {BundleProjectManager} from "../../bundle/BundleProjectManager"; +import {CliWrapper} from "../../cli/CliWrapper"; +import {logging} from "@databricks/databricks-sdk"; +import {Loggers} from "../../logger"; +import {FeatureManager} from "../../feature-manager/FeatureManager"; +import {EnvironmentComponent} from "./EnvironmentComponent"; +import {WorkspaceFolderComponent} from "./WorkspaceFolderComponent"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; +import {CodeSynchronizer} from "../../sync"; + +/** + * Data provider for the cluster tree view + */ +export class ConfigurationDataProvider + implements TreeDataProvider, Disposable +{ + private _onDidChangeTreeData: EventEmitter< + ConfigurationTreeItem | undefined | void + > = new EventEmitter(); + private _onDidChangeCheckState: EventEmitter< + ConfigurationTreeItem | undefined | void + > = new EventEmitter(); + + readonly onDidChangeTreeData: Event< + ConfigurationTreeItem | undefined | void + > = this._onDidChangeTreeData.event; + + private disposables: Array = []; + private components: Array = [ + new WorkspaceFolderComponent(this.workspaceFolderManager), + new BundleTargetComponent(this.configModel), + new AuthTypeComponent( + this.connectionManager, + this.configModel, + this.cli + ), + new ClusterComponent(this.connectionManager, this.configModel), + new SyncDestinationComponent( + this.connectionManager, + this.configModel, + this.codeSynchronizer + ), + new EnvironmentComponent( + this.featureManager, + this.connectionManager, + this.configModel + ), + ]; + constructor( + private readonly connectionManager: ConnectionManager, + private readonly codeSynchronizer: CodeSynchronizer, + private readonly bundleProjectManager: BundleProjectManager, + private readonly configModel: ConfigModel, + private readonly cli: CliWrapper, + private readonly featureManager: FeatureManager, + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + this.disposables.push( + this.bundleProjectManager.onDidChangeStatus(async () => { + this._onDidChangeTreeData.fire(); + }), + ...this.components, + ...this.components.map((c) => + c.onDidChange(() => { + this._onDidChangeTreeData.fire(); + }) + ), + this.onDidChangeTreeData((e) => { + if (e?.collapsibleState !== undefined) { + logging.NamedLogger.getOrCreate(Loggers.Extension).info( + `ConfigurationDataProvider.onDidChangeTreeData: ${e.label}` + ); + } + }) + ); + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } + + getTreeItem(element: ConfigurationTreeItem): TreeItem | Thenable { + return element; + } + + async getChildren( + parent?: ConfigurationTreeItem | undefined + ): Promise> { + const isInBundleProject = + await this.bundleProjectManager.isBundleProject(); + if (!isInBundleProject) { + return []; + } + const children = this.components.map((c) => + c.getChildren(parent).catch((e) => { + logging.NamedLogger.getOrCreate(Loggers.Extension).error( + `Error getting children for ${c.constructor.name}`, + e + ); + return []; + }) + ); + return (await Promise.all(children)).flat(); + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/ConfigurationTreeViewManager.ts b/packages/databricks-vscode/src/ui/configuration-view/ConfigurationTreeViewManager.ts new file mode 100644 index 000000000..1204f2139 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/ConfigurationTreeViewManager.ts @@ -0,0 +1,38 @@ +import { + TreeView, + TreeCheckboxChangeEvent, + Disposable, + TreeItemCheckboxState, +} from "vscode"; +import {ConfigurationTreeItem} from "./types"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {CLUSTER_OVERRIDE_CHECKBOX_ID} from "./ClusterComponent"; + +export class ConfigurationTreeViewManager implements Disposable { + private readonly disposables: Disposable[] = []; + constructor( + readonly treeView: TreeView, + readonly configModel: ConfigModel + ) { + this.disposables.push( + treeView.onDidChangeCheckboxState( + async (e: TreeCheckboxChangeEvent) => { + await Promise.all( + e.items.map(async ([item, state]) => { + if (item.id === CLUSTER_OVERRIDE_CHECKBOX_ID) { + await this.configModel.set( + "useClusterOverride", + state === TreeItemCheckboxState.Checked + ); + } + }) + ); + } + ) + ); + } + + dispose() { + this.disposables.forEach((d) => d.dispose()); + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/EnvironmentComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/EnvironmentComponent.ts new file mode 100644 index 000000000..2d210b79a --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/EnvironmentComponent.ts @@ -0,0 +1,109 @@ +import {ThemeColor, ThemeIcon, TreeItemCollapsibleState} from "vscode"; +import {FeatureManager} from "../../feature-manager/FeatureManager"; +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {ConfigModel} from "../../configuration/models/ConfigModel"; + +const ENVIRONMENT_COMPONENT_ID = "ENVIRONMENT"; +const getItemContext = (key: string, available: boolean) => + `databricks.environment.${key}.${available ? "success" : "error"}`; + +export class EnvironmentComponent extends BaseComponent { + constructor( + private readonly featureManager: FeatureManager, + private readonly connectionManager: ConnectionManager, + private readonly configModel: ConfigModel + ) { + super(); + this.featureManager.onDidChangeState("environment.dependencies", () => + this.onDidChangeEmitter.fire() + ); + } + + public async getRoot(): Promise { + const environmentState = await this.featureManager.isEnabled( + "environment.dependencies" + ); + return [ + { + label: "Python Environment", + id: ENVIRONMENT_COMPONENT_ID, + contextValue: getItemContext( + "root", + environmentState.available + ), + iconPath: environmentState.available + ? new ThemeIcon( + "check", + new ThemeColor("debugIcon.startForeground") + ) + : new ThemeIcon("info", new ThemeColor("errorForeground")), + collapsibleState: environmentState.available + ? TreeItemCollapsibleState.Collapsed + : TreeItemCollapsibleState.Expanded, + }, + ]; + } + + public async getChildren( + parent?: ConfigurationTreeItem + ): Promise { + if ( + this.connectionManager.state !== "CONNECTED" || + (await this.configModel.get("mode")) !== "development" + ) { + return []; + } + if (parent === undefined) { + return this.getRoot(); + } + if (parent.id !== ENVIRONMENT_COMPONENT_ID) { + return []; + } + const environmentState = await this.featureManager.isEnabled( + "environment.dependencies" + ); + const children: ConfigurationTreeItem[] = []; + for (const [id, step] of environmentState.steps) { + if (!step.available) { + children.push({ + contextValue: getItemContext(id, false), + label: step.title, + tooltip: step.message, + iconPath: step.action + ? new ThemeIcon( + "run", + new ThemeColor("errorForeground") + ) + : new ThemeIcon( + "info", + new ThemeColor("errorForeground") + ), + command: { + title: "Setup python environment", + command: "databricks.environment.setup", + arguments: [step.id], + }, + }); + } else if (step.available && step.title) { + children.push({ + contextValue: getItemContext(id, true), + label: step.title, + tooltip: step.message, + iconPath: new ThemeIcon("check"), + }); + if (step.warning) { + children.push({ + contextValue: getItemContext(id, true), + label: step.warning, + iconPath: new ThemeIcon("warning"), + }); + } + } + } + return children; + } + + private async setupPythonEnvironment() {} +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/SyncDestinationComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/SyncDestinationComponent.ts new file mode 100644 index 000000000..22fe523bb --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/SyncDestinationComponent.ts @@ -0,0 +1,179 @@ +import {ConfigModel} from "../../configuration/models/ConfigModel"; +import {ConnectionManager} from "../../configuration/ConnectionManager"; +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {TreeItemCollapsibleState, ThemeIcon, ThemeColor, window} from "vscode"; +import {DecorationUtils} from "../utils"; +import {CodeSynchronizer} from "../../sync"; + +const TREE_ICON_ID = "WORKSPACE"; + +/** + * Component for displaying sync destination details. Sync destination is + * always pulled from the bundle. + */ + +function getIconForSyncState(codeSynchroniser: CodeSynchronizer) { + switch (codeSynchroniser.state) { + case "IN_PROGRESS": + return new ThemeIcon( + "sync~spin", + new ThemeColor("debugIcon.startForeground") + ); + + case "STOPPED": + return new ThemeIcon( + "folder-active", + new ThemeColor("charts.green") + ); + + case "WATCHING_FOR_CHANGES": + return new ThemeIcon( + "eye", + new ThemeColor("debugIcon.startForeground") + ); + + default: + return new ThemeIcon( + "testing-error-icon", + new ThemeColor("notificationsErrorIcon.foreground") + ); + } +} +export class SyncDestinationComponent extends BaseComponent { + constructor( + private readonly connectionManager: ConnectionManager, + private readonly configModel: ConfigModel, + private readonly codeSynchronizer: CodeSynchronizer + ) { + super(); + this.disposables.push( + this.configModel.onDidChangeTarget(() => { + this.onDidChangeEmitter.fire(); + }), + this.connectionManager.onDidChangeState(() => { + this.onDidChangeEmitter.fire(); + }), + this.configModel.onDidChangeKey("remoteRootPath")(async () => { + this.onDidChangeEmitter.fire(); + }), + this.configModel.onDidChangeKey("remoteStateConfig")(async () => { + this.onDidChangeEmitter.fire(); + }), + this.codeSynchronizer.onDidChangeState(() => { + this.onDidChangeEmitter.fire(); + }), + this.configModel.onDidChangeKey("mode")(async () => { + this.onDidChangeEmitter.fire(); + }) + ); + } + + async getUrl() { + return this.connectionManager.workspaceClient + ? await this.connectionManager.syncDestinationMapper?.remoteUri.getUrl( + this.connectionManager.workspaceClient + ) + : undefined; + } + private async getRoot(): Promise { + const workspaceFsPath = await this.configModel.get("remoteRootPath"); + const mode = await this.configModel.get("mode"); + if (workspaceFsPath === undefined) { + return []; + } + + let contextValue = "databricks.configuration.sync"; + const url = await this.getUrl(); + contextValue = url ? `${contextValue}.has-url` : contextValue; + contextValue = this.codeSynchronizer.isRunning + ? `${contextValue}.is-running` + : `${contextValue}.is-stopped`; + + return [ + { + label: "Workspace Folder", + tooltip: url ? undefined : "Created after deploy", + description: + mode === "development" ? undefined : workspaceFsPath, + collapsibleState: + mode === "development" + ? TreeItemCollapsibleState.Collapsed + : TreeItemCollapsibleState.None, + contextValue, + iconPath: getIconForSyncState(this.codeSynchronizer), + resourceUri: url + ? undefined + : DecorationUtils.getModifiedStatusDecoration( + TREE_ICON_ID, + "created" + ), + id: TREE_ICON_ID, + url: url, + }, + ]; + } + + public async getChildren( + parent?: ConfigurationTreeItem + ): Promise { + if (this.connectionManager.state !== "CONNECTED") { + return []; + } + + if (parent === undefined) { + return this.getRoot(); + } + + if ( + parent.id !== TREE_ICON_ID || + (await this.configModel.get("mode")) !== "development" + ) { + return []; + } + + const workspaceFsPath = await this.configModel.get("remoteRootPath"); + const pathTreeItem: ConfigurationTreeItem = { + label: "Path", + description: workspaceFsPath, + }; + + if ( + this.codeSynchronizer.state === "ERROR" && + this.codeSynchronizer.reason + ) { + return [ + pathTreeItem, + { + description: "Error - Click for more details", + iconPath: new ThemeIcon( + "alert", + new ThemeColor("errorForeground") + ), + tooltip: "Click for more details", + + command: { + title: "Call", + command: "databricks.call", + arguments: [ + () => { + window.showErrorMessage( + `Sync Error: ${this.codeSynchronizer.reason}` + ); + }, + ], + }, + }, + ]; + } + + return [ + pathTreeItem, + { + label: `State`, + description: this.codeSynchronizer.state, + collapsibleState: TreeItemCollapsibleState.None, + }, + ]; + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/WorkspaceFolderComponent.ts b/packages/databricks-vscode/src/ui/configuration-view/WorkspaceFolderComponent.ts new file mode 100644 index 000000000..b05af2a50 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/WorkspaceFolderComponent.ts @@ -0,0 +1,50 @@ +import {BaseComponent} from "./BaseComponent"; +import {ConfigurationTreeItem} from "./types"; +import {ThemeIcon} from "vscode"; +import {WorkspaceFolderManager} from "../../vscode-objs/WorkspaceFolderManager"; + +export class WorkspaceFolderComponent extends BaseComponent { + constructor( + private readonly workspaceFolderManager: WorkspaceFolderManager + ) { + super(); + this.disposables.push( + this.workspaceFolderManager.onDidChangeActiveWorkspaceFolder(() => { + this.onDidChangeEmitter.fire(); + }) + ); + } + + private async getRoot(): Promise { + const activeWorkspaceFolder = + this.workspaceFolderManager.activeWorkspaceFolder; + if ( + activeWorkspaceFolder === undefined || + !this.workspaceFolderManager.enableUi + ) { + return []; + } + + return [ + { + label: "Active Workspace Folder", + iconPath: new ThemeIcon("folder"), + description: activeWorkspaceFolder.name, + contextValue: "databricks.configuration.activeWorkspaceFolder", + command: { + title: "Select Workspace Folder", + command: "databricks.selectWorkspaceFolder", + }, + }, + ]; + } + public async getChildren( + parent?: ConfigurationTreeItem + ): Promise { + if (parent === undefined) { + return this.getRoot(); + } + + return []; + } +} diff --git a/packages/databricks-vscode/src/ui/configuration-view/types.ts b/packages/databricks-vscode/src/ui/configuration-view/types.ts new file mode 100644 index 000000000..0c3fde402 --- /dev/null +++ b/packages/databricks-vscode/src/ui/configuration-view/types.ts @@ -0,0 +1,6 @@ +import {TreeItem} from "vscode"; + +export interface ConfigurationTreeItem extends TreeItem { + url?: string; + copyText?: string; +} diff --git a/packages/databricks-vscode/src/ui/utils/BundleUtils.ts b/packages/databricks-vscode/src/ui/utils/BundleUtils.ts new file mode 100644 index 000000000..9a83260c6 --- /dev/null +++ b/packages/databricks-vscode/src/ui/utils/BundleUtils.ts @@ -0,0 +1,6 @@ +export function humaniseMode(mode?: string) { + if (mode === undefined) { + return ""; + } + return mode.charAt(0).toUpperCase() + mode.slice(1); +} diff --git a/packages/databricks-vscode/src/ui/utils/DecorationUtils.ts b/packages/databricks-vscode/src/ui/utils/DecorationUtils.ts new file mode 100644 index 000000000..206bc5c5f --- /dev/null +++ b/packages/databricks-vscode/src/ui/utils/DecorationUtils.ts @@ -0,0 +1,48 @@ +import {BundleResourceModifiedStatus} from "../../bundle/models/BundleRemoteStateModel"; +import {asDecorationResourceUri} from "../DecorationProvider"; +import {ThemeColor, TreeItemCollapsibleState} from "vscode"; + +export function getModifiedStatusDecoration( + id: string, + modifiedStatus?: BundleResourceModifiedStatus +) { + switch (modifiedStatus) { + case "created": + return asDecorationResourceUri(id, { + badge: "C", + color: new ThemeColor("gitDecoration.addedResourceForeground"), + tooltip: "Created after deploy", + }); + case "deleted": + return asDecorationResourceUri(id, { + badge: "D", + color: new ThemeColor( + "gitDecoration.deletedResourceForeground" + ), + tooltip: "Deleted after deploy", + }); + case "updated": + return asDecorationResourceUri(id, { + badge: "U", + color: new ThemeColor( + "gitDecoration.modifiedResourceForeground" + ), + tooltip: "Updated after deploy", + }); + } +} + +export function getCollapsibleState( + isRunning: boolean, + modifiedStatus?: BundleResourceModifiedStatus +): TreeItemCollapsibleState { + if (modifiedStatus === "deleted") { + return TreeItemCollapsibleState.None; + } + + if (isRunning) { + return TreeItemCollapsibleState.Collapsed; + } + + return TreeItemCollapsibleState.Expanded; +} diff --git a/packages/databricks-vscode/src/ui/utils/LabelUtils.ts b/packages/databricks-vscode/src/ui/utils/LabelUtils.ts new file mode 100644 index 000000000..8d43a0812 --- /dev/null +++ b/packages/databricks-vscode/src/ui/utils/LabelUtils.ts @@ -0,0 +1,8 @@ +import {TreeItemLabel} from "vscode"; + +export function highlightedLabel(label: string): TreeItemLabel { + return { + label, + highlights: [[0, label.length]], + }; +} diff --git a/packages/databricks-vscode/src/ui/utils/index.ts b/packages/databricks-vscode/src/ui/utils/index.ts new file mode 100644 index 000000000..faf734c55 --- /dev/null +++ b/packages/databricks-vscode/src/ui/utils/index.ts @@ -0,0 +1,2 @@ +export * as LabelUtils from "./LabelUtils"; +export * as DecorationUtils from "./DecorationUtils"; diff --git a/packages/databricks-vscode/src/utils/DateUtils.ts b/packages/databricks-vscode/src/utils/DateUtils.ts new file mode 100644 index 000000000..4691b7d3a --- /dev/null +++ b/packages/databricks-vscode/src/utils/DateUtils.ts @@ -0,0 +1,15 @@ +export function toString(date: Date): string { + return toDateString(date) + " " + toTimeString(date); +} + +export function toDateString(date: Date): string { + const day = date.getDay(); + const month = date.toLocaleString("default", {month: "short"}); + const year = date.getFullYear(); + + return `${day} ${month}, ${year}`; +} + +export function toTimeString(date: Date): string { + return date.toLocaleTimeString(); +} diff --git a/packages/databricks-vscode/src/utils/EventWithErrorHandler.ts b/packages/databricks-vscode/src/utils/EventWithErrorHandler.ts new file mode 100644 index 000000000..4183539e3 --- /dev/null +++ b/packages/databricks-vscode/src/utils/EventWithErrorHandler.ts @@ -0,0 +1,38 @@ +import {EventEmitter, Disposable} from "vscode"; +import {OnErrorProps, withOnErrorHandler} from "./onErrorDecorator"; +import lodash from "lodash"; + +export class EventEmitterWithErrorHandler { + private _eventEmitter = new EventEmitter(); + private _event = this._eventEmitter.event; + + constructor(private readonly onErrorDefaults: OnErrorProps = {}) {} + + get event() { + const fn = ( + listener: (e: T) => Promise, + opts: { + disposables?: Disposable[]; + onError?: OnErrorProps; + } = {} + ) => { + opts = lodash.merge({}, this.onErrorDefaults, opts); + + return this._event( + withOnErrorHandler(listener, opts.onError), + undefined, + opts.disposables + ); + }; + + return fn.bind(this); + } + + fire(event: T) { + this._eventEmitter.fire(event); + } + + dispose() { + this._eventEmitter.dispose(); + } +} diff --git a/packages/databricks-vscode/src/utils/UtilsCommands.ts b/packages/databricks-vscode/src/utils/UtilsCommands.ts index b1f50f9aa..51739a05c 100644 --- a/packages/databricks-vscode/src/utils/UtilsCommands.ts +++ b/packages/databricks-vscode/src/utils/UtilsCommands.ts @@ -1,28 +1,63 @@ -import {Cluster} from "../sdk-extensions"; -import {Disposable} from "vscode"; -import {ConfigurationTreeItem} from "../configuration/ConfigurationDataProvider"; +import {Disposable, window, env} from "vscode"; import {openExternal} from "./urlUtils"; export class UtilsCommands implements Disposable { private disposables: Disposable[] = []; openExternalCommand() { - return async (value: ConfigurationTreeItem | Cluster) => { + return async (value: any | undefined) => { let url: string | undefined; - if (value instanceof Cluster) { + if (value?.url instanceof Promise) { url = await value.url; - } else { + } else if (value?.url !== undefined) { url = value.url; } - if (!url) { + if (url === undefined) { + window.showErrorMessage( + "Databricks: Can't open external link. No URL found." + ); return; } await openExternal(url); }; } + copyToClipboardCommand() { + return async (value: any | undefined) => { + let text: string | undefined; + + if (value?.copyText instanceof Promise) { + text = await value.copyText; + } else if (value.copyText !== undefined) { + text = value.copyText; + } + + if (text === undefined && value?.getTreeItem !== undefined) { + const treeItem = value.getTreeItem(); + if (treeItem instanceof Promise) { + value = await treeItem; + } else { + value = treeItem; + } + } + + if (text === undefined) { + text = value?.copyText ?? value?.description ?? value?.label; + } + + if (text === undefined) { + window.showErrorMessage( + "Databricks: Can't copy to clipboard. No text found." + ); + return; + } + window.showInformationMessage("Copied to clipboard"); + await env.clipboard.writeText(text); + }; + } + dispose() { this.disposables.forEach((d) => d.dispose()); } diff --git a/packages/databricks-vscode/src/utils/developmentUtils.ts b/packages/databricks-vscode/src/utils/developmentUtils.ts index 2e7699b67..0deecac4b 100644 --- a/packages/databricks-vscode/src/utils/developmentUtils.ts +++ b/packages/databricks-vscode/src/utils/developmentUtils.ts @@ -3,3 +3,7 @@ export const EXTENSION_DEVELOPMENT = "EXTENSION_DEVELOPMENT"; export function isDevExtension(): boolean { return process.env.EXTENSION_DEVELOPMENT === "true"; } + +export function isIntegrationTest(): boolean { + return process.env.DATABRICKS_VSCODE_INTEGRATION_TEST === "true"; +} diff --git a/packages/databricks-vscode/src/utils/envVarGenerators.test.ts b/packages/databricks-vscode/src/utils/envVarGenerators.test.ts index 67785da12..e3538cd93 100644 --- a/packages/databricks-vscode/src/utils/envVarGenerators.test.ts +++ b/packages/databricks-vscode/src/utils/envVarGenerators.test.ts @@ -31,7 +31,7 @@ describe(__filename, () => { when(mockConnectionManager.databricksWorkspace).thenReturn( instance(mockDatabricksWorkspace) ); - when(mockDatabricksWorkspace.host).thenReturn(Uri.parse(mockHost)); + when(mockDatabricksWorkspace.host).thenReturn(new URL(mockHost)); when(mockCluster.id).thenReturn(mockClusterId); when(mockConnectionManager.cluster).thenReturn(instance(mockCluster)); @@ -41,7 +41,6 @@ describe(__filename, () => { ); when(mockApiClient.host).thenResolve(new URL(mockHost)); existingEnv = Object.assign({}, process.env); - process.env.SPARK_CONNECT_USER_AGENT = ""; }); afterEach(() => { @@ -59,7 +58,6 @@ describe(__filename, () => { DATABRICKS_AUTH_TYPE: "metadata-service", DATABRICKS_METADATA_SERVICE_URL: "http://example.com/metadata-service", - DATABRICKS_CLUSTER_ID: mockClusterId, }); }); @@ -105,12 +103,14 @@ describe(__filename, () => { const actual = await getDbConnectEnvVars( instance(mockConnectionManager), - mockWorkspacePath + mockWorkspacePath, + true ); assert.deepEqual(actual, { SPARK_CONNECT_USER_AGENT: "test/0.0.1", DATABRICKS_PROJECT_ROOT: mockWorkspacePath.fsPath, + SPARK_CONNECT_PROGRESS_BAR_ENABLED: "1", }); }); @@ -120,17 +120,18 @@ describe(__filename, () => { const actual = await getDbConnectEnvVars( instance(mockConnectionManager), - mockWorkspacePath + mockWorkspacePath, + true ); assert.deepEqual(actual, { SPARK_CONNECT_USER_AGENT: "existing test/0.0.1", DATABRICKS_PROJECT_ROOT: mockWorkspacePath.fsPath, + SPARK_CONNECT_PROGRESS_BAR_ENABLED: "1", }); }); - it("should generate correct dbconnect env vars when auth type is profile", async () => { - when(mockAuthProvider.authType).thenReturn("profile"); + it("should generate correct dbconnect env vars when auth type is pat", async () => { const mockConfig = mock(Config); when(mockApiClient.config).thenReturn(instance(mockConfig)); when(mockConfig.authenticate(anything())).thenCall( @@ -138,18 +139,45 @@ describe(__filename, () => { headers.set("Authorization", "Bearer token"); } ); + when(mockConnectionManager.authType).thenReturn("pat"); + const actual = await getDbConnectEnvVars( instance(mockConnectionManager), - mockWorkspacePath + mockWorkspacePath, + true ); assert.deepEqual(actual, { SPARK_CONNECT_USER_AGENT: "test/0.0.1", DATABRICKS_PROJECT_ROOT: mockWorkspacePath.fsPath, + SPARK_CONNECT_PROGRESS_BAR_ENABLED: "1", SPARK_REMOTE: `sc://${ Uri.parse(mockHost).authority }:443/;token=token;use_ssl=true;x-databricks-cluster-id=${mockClusterId}`, }); }); + + it("should generate correct dbconnect env vars when auth type is not pat", async () => { + const mockConfig = mock(Config); + when(mockApiClient.config).thenReturn(instance(mockConfig)); + when(mockConfig.authenticate(anything())).thenCall( + (headers: Headers) => { + headers.set("Authorization", "Bearer token"); + } + ); + when(mockConnectionManager.authType).thenReturn("azure-cli"); + + const actual = await getDbConnectEnvVars( + instance(mockConnectionManager), + mockWorkspacePath, + true + ); + + assert.deepEqual(actual, { + SPARK_CONNECT_USER_AGENT: "test/0.0.1", + DATABRICKS_PROJECT_ROOT: mockWorkspacePath.fsPath, + SPARK_CONNECT_PROGRESS_BAR_ENABLED: "1", + }); + }); }); }); diff --git a/packages/databricks-vscode/src/utils/envVarGenerators.ts b/packages/databricks-vscode/src/utils/envVarGenerators.ts index 70c43366f..3160e0030 100644 --- a/packages/databricks-vscode/src/utils/envVarGenerators.ts +++ b/packages/databricks-vscode/src/utils/envVarGenerators.ts @@ -1,8 +1,16 @@ import {Loggers} from "../logger"; import {readFile} from "fs/promises"; -import {Uri} from "vscode"; -import {Headers, logging} from "@databricks/databricks-sdk"; +import {ExtensionContext, Uri} from "vscode"; +import {logging, Headers} from "@databricks/databricks-sdk"; import {ConnectionManager} from "../configuration/ConnectionManager"; +import {ConfigModel} from "../configuration/models/ConfigModel"; +import {TerraformMetadata} from "./terraformUtils"; + +// eslint-disable-next-line @typescript-eslint/no-var-requires +const packageJson = require("../../package.json"); + +const extensionVersion = packageJson.version; +const terraformMetadata = packageJson.terraformMetadata as TerraformMetadata; //Get env variables from user's .env file export async function getUserEnvVars(userEnvPath: Uri) { @@ -47,7 +55,6 @@ function getUserAgent(connectionManager: ConnectionManager) { } export function getAuthEnvVars(connectionManager: ConnectionManager) { - const cluster = connectionManager.cluster; const host = connectionManager.databricksWorkspace?.host.toString(); if (!host || !connectionManager.metadataServiceUrl) { return; @@ -58,18 +65,21 @@ export function getAuthEnvVars(connectionManager: ConnectionManager) { DATABRICKS_HOST: host, DATABRICKS_AUTH_TYPE: "metadata-service", DATABRICKS_METADATA_SERVICE_URL: connectionManager.metadataServiceUrl, - DATABRICKS_CLUSTER_ID: cluster?.id, }; /* eslint-enable @typescript-eslint/naming-convention */ } export function getCommonDatabricksEnvVars( - connectionManager: ConnectionManager + connectionManager: ConnectionManager, + configModel: ConfigModel ) { + const cluster = connectionManager.cluster; /* eslint-disable @typescript-eslint/naming-convention */ return { + DATABRICKS_BUNDLE_TARGET: configModel.target, ...(getAuthEnvVars(connectionManager) || {}), ...(getProxyEnvVars() || {}), + DATABRICKS_CLUSTER_ID: cluster?.id, }; /* eslint-enable @typescript-eslint/naming-convention */ } @@ -81,15 +91,14 @@ async function getPatToken(connectionManager: ConnectionManager) { } async function getSparkRemoteEnvVar(connectionManager: ConnectionManager) { - const host = connectionManager.databricksWorkspace?.host.authority; - const authType = - connectionManager.databricksWorkspace?.authProvider.authType; + const host = connectionManager.databricksWorkspace?.host.host; + const authType = connectionManager.authType; // We export spark remote only for profile auth type. This is to support // SparkSession builder in oss spark connect (and also dbconnect). // For all other auth types, we don't export spark remote and expect users // to use DatabricksSession for full functionality. - if (host && connectionManager.cluster && authType === "profile") { + if (host && connectionManager.cluster && authType === "pat") { const pat = await getPatToken(connectionManager); if (pat) { return { @@ -102,15 +111,20 @@ async function getSparkRemoteEnvVar(connectionManager: ConnectionManager) { export async function getDbConnectEnvVars( connectionManager: ConnectionManager, - workspacePath: Uri + workspacePath: Uri, + showDatabricksConnectProgess: boolean ) { const userAgent = getUserAgent(connectionManager); const existingSparkUa = process.env.SPARK_CONNECT_USER_AGENT ?? ""; + /* eslint-disable @typescript-eslint/naming-convention */ return { //We append our user agent to any existing SPARK_CONNECT_USER_AGENT defined in the //environment of the parent process of VS Code. SPARK_CONNECT_USER_AGENT: [existingSparkUa, userAgent].join(" ").trim(), + SPARK_CONNECT_PROGRESS_BAR_ENABLED: showDatabricksConnectProgess + ? "1" + : "0", DATABRICKS_PROJECT_ROOT: workspacePath.fsPath, ...((await getSparkRemoteEnvVar(connectionManager)) || {}), }; @@ -127,16 +141,48 @@ export function getProxyEnvVars() { }; } -export function removeUndefinedKeys< - T extends Record, ->(envVarMap?: T): T | undefined { - if (envVarMap === undefined) { - return; +export function getEnvVarsForCli( + extensionContext: ExtensionContext, + configfilePath?: string +) { + /* eslint-disable @typescript-eslint/naming-convention */ + return { + HOME: process.env.HOME, + PATH: process.env.PATH, + DATABRICKS_CONFIG_FILE: + configfilePath ?? process.env.DATABRICKS_CONFIG_FILE, + DATABRICKS_OUTPUT_FORMAT: "json", + DATABRICKS_CLI_UPSTREAM: "databricks-vscode", + DATABRICKS_CLI_UPSTREAM_VERSION: extensionVersion, + ...getCLIDependenciesEnvVars(extensionContext), + }; + /* eslint-enable @typescript-eslint/naming-convention */ +} + +export function getCLIDependenciesEnvVars(extensionContext: ExtensionContext) { + if (!terraformMetadata) { + return {}; } + /* eslint-disable @typescript-eslint/naming-convention */ + return { + DATABRICKS_TF_VERSION: terraformMetadata.version, + DATABRICKS_TF_EXEC_PATH: extensionContext.asAbsolutePath( + terraformMetadata.execRelPath + ), + DATABRICKS_TF_PROVIDER_VERSION: terraformMetadata.providerVersion, + DATABRICKS_TF_CLI_CONFIG_FILE: extensionContext.asAbsolutePath( + terraformMetadata.terraformCliConfigRelPath + ), + }; + /* eslint-enable @typescript-eslint/naming-convention */ +} +export function removeUndefinedKeys< + T extends Record, +>(envVarMap: T): Record { const filteredEntries = Object.entries(envVarMap).filter( (entry) => entry[1] !== undefined ) as [string, string][]; - return Object.fromEntries(filteredEntries) as T; + return Object.fromEntries(filteredEntries); } diff --git a/packages/databricks-vscode/src/utils/environmentUtils.ts b/packages/databricks-vscode/src/utils/environmentUtils.ts new file mode 100644 index 000000000..92529574d --- /dev/null +++ b/packages/databricks-vscode/src/utils/environmentUtils.ts @@ -0,0 +1,9 @@ +import {Environment} from "../language/MsPythonExtensionApi"; + +export function environmentName(env: Environment) { + const version = env.version + ? `${env.version.major}.${env.version.minor}.${env.version.micro} ` + : ""; + const name = env.environment?.name ?? env.path; + return `${version}${name}`; +} diff --git a/packages/databricks-vscode/src/utils/fileUtils.ts b/packages/databricks-vscode/src/utils/fileUtils.ts index 825d54c97..c82b31087 100644 --- a/packages/databricks-vscode/src/utils/fileUtils.ts +++ b/packages/databricks-vscode/src/utils/fileUtils.ts @@ -1,7 +1,8 @@ import {TextDecoder} from "util"; -import {Uri, workspace} from "vscode"; +import {Uri, workspace, FileSystemError, window} from "vscode"; import {LocalUri} from "../sync/SyncDestination"; -import {ConnectionManager} from "../configuration/ConnectionManager"; +import type {ConnectionManager} from "../configuration/ConnectionManager"; +import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {exists} from "fs-extra"; import path from "path"; import {homedir} from "os"; @@ -48,3 +49,31 @@ export async function waitForDatabricksProject( export function getHomedir() { return process.env.HOME ?? homedir(); } + +export function getDatabricksConfigFilePath() { + const homeDir = getHomedir(); + let filePath = + workspaceConfigs.databrickscfgLocation ?? + path.join(homeDir, ".databrickscfg"); + + if (filePath.startsWith("~/")) { + filePath = path.join(homeDir, filePath.slice(2)); + } + return Uri.file(path.normalize(filePath)); +} + +export async function openDatabricksConfigFile() { + const uri = getDatabricksConfigFilePath(); + try { + await workspace.fs.stat(uri); + } catch (e) { + if (e instanceof FileSystemError && e.code === "FileNotFound") { + await workspace.fs.writeFile(uri, Buffer.from("")); + } else { + throw e; + } + } + + const doc = await workspace.openTextDocument(uri); + await window.showTextDocument(doc); +} diff --git a/packages/databricks-vscode/src/utils/index.ts b/packages/databricks-vscode/src/utils/index.ts index ca1991149..70f581626 100644 --- a/packages/databricks-vscode/src/utils/index.ts +++ b/packages/databricks-vscode/src/utils/index.ts @@ -1,5 +1,8 @@ export * as FileUtils from "./fileUtils"; export * as UrlUtils from "./urlUtils"; +export * as ShellUtils from "./shellUtils"; export * as UtilsCommands from "./UtilsCommands"; export * as PackageJsonUtils from "./packageJsonUtils"; export * as EnvVarGenerators from "./envVarGenerators"; +export * as DateUtils from "./DateUtils"; +export * as TerraformUtils from "./terraformUtils"; diff --git a/packages/databricks-vscode/src/utils/onErrorDecorator.ts b/packages/databricks-vscode/src/utils/onErrorDecorator.ts new file mode 100644 index 000000000..0a53663db --- /dev/null +++ b/packages/databricks-vscode/src/utils/onErrorDecorator.ts @@ -0,0 +1,122 @@ +import {window} from "vscode"; +import { + getContextParamIndex, + logging, + Context, +} from "@databricks/databricks-sdk"; +import {Loggers} from "../logger"; + +interface Props { + popup?: { + prefix?: string; + }; + log?: { + prefix?: string; + logger?: logging.NamedLogger; + }; + throw?: boolean; +} + +export type OnErrorProps = { + [key in keyof Props]?: Props[key] | boolean; +}; + +const defaultProps: OnErrorProps = { + popup: false, + log: true, + throw: false, +}; + +export function onError(props: OnErrorProps) { + props = {...defaultProps, ...props}; + return function showErrorDecorator( + target: any, + propertyKey: string, + descriptor: PropertyDescriptor + ) { + let closureArgs: any[] = []; + let contextParamIndex: number = -1; + // Find the @context if it exists. We want to use it for logging whenever possible. + if ( + props.log !== undefined && + props.log !== false && + (props.log === true || props.log?.logger === undefined) + ) { + try { + // This will decorate the method with a log context. This allows us to search for the context parameter. + logging.withLogContext(Loggers.Extension)( + target, + propertyKey, + descriptor + ); + contextParamIndex = getContextParamIndex(target, propertyKey); + if (contextParamIndex !== -1) { + props.log = { + get logger() { + return (closureArgs[contextParamIndex] as Context) + .logger; + }, + }; + } + } catch (e) {} + } + const originalMethod = descriptor.value; + + descriptor.value = async function (...args: any[]) { + closureArgs = args; + return await withOnErrorHandler( + originalMethod.bind(this), + props + )(...args); + }; + }; +} + +export function withOnErrorHandler( + fn: (...args: T) => Promise, + props: OnErrorProps = {} +) { + props = {...defaultProps, ...props}; + + const onErrorProps: Props = {}; + + (["popup", "log"] as const).forEach((key) => { + if (props[key] === undefined || props[key] === false) { + onErrorProps[key] = undefined; + } else if (props[key] === true) { + onErrorProps[key] = {}; + } else { + onErrorProps[key] = props[key] as any; + } + }); + + return async function (...args: T): Promise { + try { + const result = fn(...args); + return result instanceof Promise ? await result : result; + } catch (e) { + if (!(e instanceof Error)) { + throw e; + } + + let prefix = ""; + if (onErrorProps.popup) { + prefix = onErrorProps.popup?.prefix ?? prefix; + window.showErrorMessage( + prefix.trimEnd() + " " + e.message.trimStart() + ); + } + if (onErrorProps.log) { + prefix = onErrorProps.log?.prefix ?? prefix; + const logger = + onErrorProps.log?.logger ?? + logging.NamedLogger.getOrCreate(Loggers.Extension); + logger.error(prefix.trimEnd() + " " + e.message.trimStart(), e); + } + + if (onErrorProps.throw) { + throw e; + } + } + }; +} diff --git a/packages/databricks-vscode/src/utils/shellUtils.ts b/packages/databricks-vscode/src/utils/shellUtils.ts new file mode 100644 index 000000000..4c5c42112 --- /dev/null +++ b/packages/databricks-vscode/src/utils/shellUtils.ts @@ -0,0 +1,23 @@ +import {env} from "vscode"; + +export function isPowershell() { + return env.shell.toLowerCase().includes("powershell"); +} + +export function readCmd() { + if (isPowershell()) { + return "Read-Host"; + } + return "read"; +} + +export function escapeExecutableForTerminal(exe: string): string { + if (isPowershell()) { + return `& "${exe}"`; + } + return `"${exe}"`; +} + +export function escapePathArgument(arg: string): string { + return `"${arg.replaceAll('"', '\\"')}"`; +} diff --git a/packages/databricks-vscode/src/utils/terraformUtils.ts b/packages/databricks-vscode/src/utils/terraformUtils.ts new file mode 100644 index 000000000..b0276f523 --- /dev/null +++ b/packages/databricks-vscode/src/utils/terraformUtils.ts @@ -0,0 +1,44 @@ +import {writeFile} from "fs/promises"; +import {ExtensionContext} from "vscode"; + +export type TerraformMetadataFromCli = { + version: string; + providerVersion: string; + providerSource: string; + providerHost: string; +}; + +export type TerraformMetadataExtra = { + execRelPath: string; + providersMirrorRelPath: string; + terraformCliConfigRelPath: string; +}; + +export type TerraformMetadata = TerraformMetadataFromCli & + TerraformMetadataExtra; + +function getTerraformCliConfig(mirrorPath: string) { + return `disable_checkpoint = true +provider_installation { + filesystem_mirror { + path = "${mirrorPath.replace(/\\/g, "\\\\")}" + } +}`; +} + +export async function updateTerraformCliConfig( + context: ExtensionContext, + terraformMetadata?: TerraformMetadata +) { + if (!terraformMetadata) { + return; + } + const configPath = context.asAbsolutePath( + terraformMetadata.terraformCliConfigRelPath + ); + const providersMirrorPath = context.asAbsolutePath( + terraformMetadata.providersMirrorRelPath + ); + const config = getTerraformCliConfig(providersMirrorPath); + await writeFile(configPath, config, {encoding: "utf-8"}); +} diff --git a/packages/databricks-vscode/src/utils/urlUtils.ts b/packages/databricks-vscode/src/utils/urlUtils.ts index 2f3005f87..03607a888 100644 --- a/packages/databricks-vscode/src/utils/urlUtils.ts +++ b/packages/databricks-vscode/src/utils/urlUtils.ts @@ -7,6 +7,13 @@ export async function openExternal(url: string) { await env.openExternal(Uri.parse(addHttpsIfNoProtocol(url), true)); } +export class UrlError extends Error { + constructor(message: string) { + super(message); + this.name = "UrlError"; + } +} + export function normalizeHost(host: string): URL { let url: URL; @@ -16,10 +23,10 @@ export function normalizeHost(host: string): URL { try { url = new URL(host); } catch (e) { - throw new Error("Invalid host name"); + throw new UrlError("Invalid host name"); } if (url.protocol !== "https:") { - throw new Error("Invalid protocol"); + throw new UrlError("Invalid protocol"); } return new URL(`https://${url.hostname}`); diff --git a/packages/databricks-vscode/src/vscode-objs/CustomWhenContext.ts b/packages/databricks-vscode/src/vscode-objs/CustomWhenContext.ts index 5f6eae52c..a5b09481c 100644 --- a/packages/databricks-vscode/src/vscode-objs/CustomWhenContext.ts +++ b/packages/databricks-vscode/src/vscode-objs/CustomWhenContext.ts @@ -2,14 +2,14 @@ import {commands} from "vscode"; import {workspaceConfigs} from "./WorkspaceConfigs"; // eslint-disable-next-line @typescript-eslint/naming-convention -export const CustomWhenContext = { +export class CustomWhenContext { setLoggedIn(value: boolean) { commands.executeCommand( "setContext", "databricks.context.loggedIn", value ); - }, + } setActivated(value: boolean) { commands.executeCommand( @@ -17,7 +17,63 @@ export const CustomWhenContext = { "databricks.context.activated", value ); - }, + } + + setDeploymentState(value: "idle" | "deploying") { + commands.executeCommand( + "setContext", + "databricks.context.bundle.deploymentState", + value + ); + } + + isTargetSet(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.bundle.isTargetSet", + value + ); + } + + isDevTarget(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.bundle.isDevTarget", + value + ); + } + + setIsBundleProject(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.isBundleProject", + value + ); + } + + setSubProjectsAvailable(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.subProjectsAvailable", + value + ); + } + + setPendingManualMigration(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.pendingManualMigration", + value + ); + } + + setInitialized() { + commands.executeCommand( + "setContext", + "databricks.context.initialized", + true + ); + } updateShowClusterView() { commands.executeCommand( @@ -27,7 +83,7 @@ export const CustomWhenContext = { "views.cluster" ) ); - }, + } updateShowWorkspaceView() { commands.executeCommand( @@ -37,5 +93,21 @@ export const CustomWhenContext = { "views.workspace" ) ); - }, -}; + } + + setIsActiveFileInActiveWorkspace(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.isActiveFileInActiveWorkspace", + value + ); + } + + setShowRunAsWorkflow(value: boolean) { + commands.executeCommand( + "setContext", + "databricks.context.showRunAsWorkflow", + value + ); + } +} diff --git a/packages/databricks-vscode/src/vscode-objs/StateStorage.ts b/packages/databricks-vscode/src/vscode-objs/StateStorage.ts index 3ef40e8dd..d003ad281 100644 --- a/packages/databricks-vscode/src/vscode-objs/StateStorage.ts +++ b/packages/databricks-vscode/src/vscode-objs/StateStorage.ts @@ -1,5 +1,8 @@ import {randomUUID} from "crypto"; -import {ExtensionContext} from "vscode"; +import {EventEmitter, ExtensionContext, Event} from "vscode"; +import {OverrideableConfigState} from "../configuration/models/OverrideableConfigModel"; +import {Mutex} from "../locking"; +import lodash from "lodash"; /* eslint-disable @typescript-eslint/naming-convention */ type KeyInfo = { @@ -15,9 +18,12 @@ function withType() { }; } -const Keys = { - "databricks.clusterId": withType()({ +const StorageConfigurations = { + "databricks.bundle.overrides": withType<{ + [k: string]: OverrideableConfigState; + }>()({ location: "workspace", + defaultValue: {}, }), "databricks.wsfs.skipSwitchToWorkspace": withType()({ @@ -52,21 +58,8 @@ const Keys = { }, }), - "databricks.debugging.skipDbConnectInstallForEnvs": withType()({ - location: "global", - defaultValue: [], - setter: (storage, value) => { - if (value === undefined || value.length === 0) { - return undefined; - } - const currentEnvs: string[] = storage.get( - "databricks.debugging.skipDbConnectInstallForEnvs" - ); - if (!currentEnvs.includes(value[0])) { - currentEnvs.push(value[0]); - } - return currentEnvs; - }, + "databricks.bundle.target": withType()({ + location: "workspace", }), "databricks.lastInstalledExtensionVersion": withType()({ @@ -75,17 +68,18 @@ const Keys = { }), }; -type ValueType = (typeof Keys)[K]["_type"]; +type Keys = keyof typeof StorageConfigurations; +type ValueType = (typeof StorageConfigurations)[K]["_type"]; type GetterReturnType> = D extends {getter: infer G} ? G extends (...args: any[]) => any ? ReturnType : undefined : undefined; -type DefaultValue = - "defaultValue" extends keyof (typeof Keys)[K] +type DefaultValue = + "defaultValue" extends keyof (typeof StorageConfigurations)[K] ? ValueType - : GetterReturnType<(typeof Keys)[K]>; + : GetterReturnType<(typeof StorageConfigurations)[K]>; type KeyInfoWithType = KeyInfo & { _type: V; @@ -94,6 +88,15 @@ type KeyInfoWithType = KeyInfo & { /* eslint-enable @typescript-eslint/naming-convention */ export class StateStorage { + private mutex = new Mutex(); + private readonly changeEmitters = new Map< + Keys, + { + emitter: EventEmitter; + onDidEmit: Event; + } + >(); + constructor(private context: ExtensionContext) {} get skippedEnvsForDatabricksSdk() { return this.context.globalState.get( @@ -121,26 +124,48 @@ export class StateStorage { } } - get(key: K): ValueType | DefaultValue { - const details = Keys[key] as KeyInfoWithType>; + onDidChange(key: K): Event { + if (!this.changeEmitters.has(key)) { + const emitter = new EventEmitter(); + this.changeEmitters.set(key, { + emitter, + onDidEmit: emitter.event, + }); + } + return this.changeEmitters.get(key)!.onDidEmit; + } + + get(key: K): ValueType | DefaultValue { + const details = StorageConfigurations[key] as KeyInfoWithType< + ValueType + >; const value = this.getStateObject(details.location).get>(key) ?? details.defaultValue; - return ( + const returnValue = ( details.getter !== undefined ? details.getter(this, value) : value ) as ValueType | DefaultValue; + + if (typeof value === "object") { + return lodash.cloneDeep(returnValue); + } + return returnValue; } - async set( - key: K, - value: ValueType | undefined - ) { - const details = Keys[key] as KeyInfoWithType>; + @Mutex.synchronise("mutex") + async set(key: K, value: ValueType | undefined) { + const details = StorageConfigurations[key] as KeyInfoWithType< + ValueType + >; value = details.setter !== undefined ? details.setter(this, value) : value; + const oldValue = this.get(key); + if (lodash.isEqual(oldValue, value)) { + return; + } await this.getStateObject(details.location).update(key, value); - return; + this.changeEmitters.get(key)?.emitter.fire(); } } diff --git a/packages/databricks-vscode/src/vscode-objs/WorkspaceConfigs.ts b/packages/databricks-vscode/src/vscode-objs/WorkspaceConfigs.ts index 1a14ceb5d..9a23a4d29 100644 --- a/packages/databricks-vscode/src/vscode-objs/WorkspaceConfigs.ts +++ b/packages/databricks-vscode/src/vscode-objs/WorkspaceConfigs.ts @@ -1,5 +1,5 @@ import {ConfigurationTarget, workspace} from "vscode"; -import {SyncDestinationType} from "../sync/SyncDestination"; +import {Time, TimeUnits} from "@databricks/databricks-sdk"; export const workspaceConfigs = { get maxFieldLength() { @@ -37,46 +37,12 @@ export const workspaceConfigs = { .get("clusters.onlyShowAccessibleClusters") ?? false ); }, - get syncDestinationType() { - return ( - workspace - .getConfiguration("databricks") - .get("sync.destinationType") ?? "workspace" - ); - }, - get enableFilesInWorkspace() { - return this.syncDestinationType === "workspace"; - }, - - async setSyncDestinationType(destinationType: SyncDestinationType) { - await workspace - .getConfiguration("databricks") - .update( - "sync.destinationType", - destinationType, - ConfigurationTarget.Workspace - ); - }, get databrickscfgLocation() { const config = workspace .getConfiguration("databricks") .get("overrideDatabricksConfigFile"); - return config === "" || config === undefined ? undefined : config; - }, - - get userEnvFile() { - const config = workspace - .getConfiguration("databricks") - .get("python.envFile"); - - return config === "" || config === undefined ? undefined : config; - }, - - set userEnvFile(value: string | undefined) { - workspace - .getConfiguration("databricks") - .update("python.envFile", value, ConfigurationTarget.Workspace); + return config || process.env.DATABRICKS_CONFIG_FILE || undefined; }, get experimetalFeatureOverides() { @@ -139,6 +105,14 @@ export const workspaceConfigs = { ); }, + get showDatabricksConnectProgress(): boolean { + return ( + workspace + .getConfiguration("databricks") + .get("connect.progress") ?? true + ); + }, + get ipythonDir(): string | undefined { const dir = workspace .getConfiguration("databricks") @@ -148,4 +122,15 @@ export const workspaceConfigs = { } return dir; }, + + get bundleRemoteStateRefreshInterval(): number { + const config = + workspace + .getConfiguration("databricks") + .get("bundle.remoteStateRefreshInterval") ?? 5; + + return new Time(config, TimeUnits.minutes).toMillSeconds().value; + }, }; + +export type WorkspaceConfigs = typeof workspaceConfigs; diff --git a/packages/databricks-vscode/src/vscode-objs/WorkspaceFolderManager.ts b/packages/databricks-vscode/src/vscode-objs/WorkspaceFolderManager.ts new file mode 100644 index 000000000..b9c68ef15 --- /dev/null +++ b/packages/databricks-vscode/src/vscode-objs/WorkspaceFolderManager.ts @@ -0,0 +1,150 @@ +import { + Disposable, + EventEmitter, + QuickPickItem, + QuickPickItemKind, + StatusBarAlignment, + TextEditor, + WorkspaceFolder, + window, + workspace, +} from "vscode"; +import {CustomWhenContext} from "./CustomWhenContext"; + +export class WorkspaceFolderManager implements Disposable { + private disposables: Disposable[] = []; + private _activeWorkspaceFolder: WorkspaceFolder | undefined = + workspace.workspaceFolders?.[0]; + private readonly didChangeActiveWorkspaceFolder = new EventEmitter< + WorkspaceFolder | undefined + >(); + public readonly onDidChangeActiveWorkspaceFolder = + this.didChangeActiveWorkspaceFolder.event; + + private readonly button = window.createStatusBarItem( + StatusBarAlignment.Left, + 999 + ); + + constructor(public readonly customWhenContext: CustomWhenContext) { + if (this.enableUi) { + this.button.text = + this._activeWorkspaceFolder?.name ?? "No Databricks Project"; + this.button.tooltip = "Selected databricks project"; + this.button.command = "databricks.selectWorkspaceFolder"; + this.button.show(); + } + + this.setIsActiveFileInActiveWorkspace(window.activeTextEditor); + + this.disposables.push( + this.button, + workspace.onDidChangeWorkspaceFolders((e) => { + if ( + e.removed.find( + (v) => + v.uri.fsPath === + this._activeWorkspaceFolder?.uri.fsPath + ) || + this._activeWorkspaceFolder === undefined + ) { + this.setActiveWorkspaceFolder( + workspace.workspaceFolders?.[0] + ); + return; + } + }), + window.onDidChangeActiveTextEditor((editor) => { + this.setIsActiveFileInActiveWorkspace(editor); + }), + this.onDidChangeActiveWorkspaceFolder(() => { + this.setIsActiveFileInActiveWorkspace(window.activeTextEditor); + }) + ); + } + + private setIsActiveFileInActiveWorkspace(activeEditor?: TextEditor) { + const isActiveFileInActiveWorkspace = + this.activeWorkspaceFolder !== undefined && + activeEditor !== undefined && + activeEditor.document.uri.fsPath.startsWith( + this.activeWorkspaceFolder?.uri.fsPath + ); + this.customWhenContext.setIsActiveFileInActiveWorkspace( + isActiveFileInActiveWorkspace + ); + } + + get activeWorkspaceFolder() { + if (this._activeWorkspaceFolder === undefined) { + throw new Error("No active workspace folder"); + } + + return this._activeWorkspaceFolder; + } + + setActiveWorkspaceFolder(folder?: WorkspaceFolder) { + if (this._activeWorkspaceFolder?.uri.fsPath === folder?.uri.fsPath) { + return; + } + + this._activeWorkspaceFolder = folder; + this.didChangeActiveWorkspaceFolder.fire(folder); + + if (this.enableUi) { + this.button.text = folder?.name ?? "No Databricks Project"; + this.button.show(); + } + } + + get folders() { + return workspace.workspaceFolders; + } + + async selectDatabricksWorkspaceFolderCommand() { + const items: (QuickPickItem & { + workspaceFolder: WorkspaceFolder; + })[] = + this.folders + ?.filter((i) => i.name !== this.activeWorkspaceFolder.name) + .map((folder) => ({ + label: folder.name, + description: folder.uri.fsPath, + workspaceFolder: folder, + })) ?? []; + + const firstItem = this.activeWorkspaceFolder + ? [ + { + label: "Selected Databricks Workspace Folder", + kind: QuickPickItemKind.Separator, + }, + { + label: this.activeWorkspaceFolder.name, + description: this.activeWorkspaceFolder.uri.fsPath, + workspaceFolder: this.activeWorkspaceFolder, + }, + { + label: "", + kind: QuickPickItemKind.Separator, + }, + ] + : []; + + const choice = await window.showQuickPick([...firstItem, ...items], { + title: "Select Databricks Workspace Folder", + }); + if (!choice) { + return; + } + this.setActiveWorkspaceFolder(choice.workspaceFolder); + } + + get enableUi() { + return this.folders && this.folders?.length > 1; + } + + dispose() { + this.disposables.forEach((i) => i.dispose()); + } +} diff --git a/packages/databricks-vscode/src/whatsNewPopup.ts b/packages/databricks-vscode/src/whatsNewPopup.ts index 67f87c290..7db0f9f00 100644 --- a/packages/databricks-vscode/src/whatsNewPopup.ts +++ b/packages/databricks-vscode/src/whatsNewPopup.ts @@ -4,7 +4,6 @@ import {StateStorage} from "./vscode-objs/StateStorage"; import path from "path"; import {exists} from "fs-extra"; import * as semver from "semver"; -import {openExternal} from "./utils/urlUtils"; export async function findFileFowWhatsNew( context: ExtensionContext, @@ -34,18 +33,6 @@ export async function findFileFowWhatsNew( return context.asAbsolutePath("CHANGELOG.md"); } -async function showV2Notification() { - const choice = await window.showInformationMessage( - "Version 2 of the extension will soon be made the default. With this update it is easier to set up your project, integrate with Databricks Asset Bundles, and run your code remotely.", - "Learn more" - ); - if (choice === "Learn more") { - openExternal( - "https://docs.databricks.com/dev-tools/vscode-ext/index.html" - ); - } -} - export async function showWhatsNewPopup( context: ExtensionContext, storage: StateStorage @@ -75,7 +62,6 @@ export async function showWhatsNewPopup( if (window.state.focused) { commands.executeCommand("markdown.showPreview", Uri.file(markdownFile)); - showV2Notification(); return; } @@ -84,7 +70,6 @@ export async function showWhatsNewPopup( return; } commands.executeCommand("markdown.showPreview", Uri.file(markdownFile)); - showV2Notification(); listener.dispose(); }); context.subscriptions.push(listener); diff --git a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsAccessVerifier.ts b/packages/databricks-vscode/src/workspace-fs/WorkspaceFsAccessVerifier.ts deleted file mode 100644 index 79a28d33e..000000000 --- a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsAccessVerifier.ts +++ /dev/null @@ -1,217 +0,0 @@ -import {Cluster, WorkspaceFsEntity, WorkspaceFsUtils} from "../sdk-extensions"; -import {commands, Disposable, window, EventEmitter} from "vscode"; -import {ConnectionManager} from "../configuration/ConnectionManager"; -import {CodeSynchronizer} from "../sync"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; -import {StateStorage} from "../vscode-objs/StateStorage"; -import {Events, Telemetry} from "../telemetry"; - -export async function switchToRepos() { - await workspaceConfigs.setSyncDestinationType("repo"); - commands.executeCommand("workbench.action.reloadWindow"); -} - -export async function switchToWorkspace() { - await workspaceConfigs.setSyncDestinationType("workspace"); - commands.executeCommand("workbench.action.reloadWindow"); -} - -async function dbrBelowThreshold(cluster: Cluster) { - const dbrVersionParts = cluster.dbrVersion!; - return ( - (dbrVersionParts[0] !== "x" && dbrVersionParts[0] < 11) || - (dbrVersionParts[0] === 11 && - dbrVersionParts[1] !== "x" && - dbrVersionParts[1] < 2) - ); -} - -export async function switchToWorkspacePrompt( - stateStorage: StateStorage, - telemetry: Telemetry -) { - const message = - "Databricks recommends switching from Repos to Workspace as sync destination."; - const selection = await window.showErrorMessage( - message, - "Switch to Workspace", - "Ignore", - "Don't show again" - ); - telemetry.recordEvent(Events.SWITCH_TO_WORKSPACE_PROMPT, { - selection: selection ?? "undefined", - }); - - if (selection === "Don't show again") { - stateStorage.set("databricks.wsfs.skipSwitchToWorkspace", true); - return; - } - - if (selection === "Switch to Workspace") { - switchToWorkspace(); - } -} - -export class WorkspaceFsAccessVerifier implements Disposable { - private disposables: Disposable[] = []; - private currentCluster: Cluster | undefined; - private _isEnabled: boolean | undefined; - private readonly onDidChangeStateEmitter = new EventEmitter< - boolean | undefined - >(); - readonly onDidChangeState = this.onDidChangeStateEmitter.event; - - private set isEnabled(value: boolean | undefined) { - if (this._isEnabled !== value) { - this.onDidChangeStateEmitter.fire(value); - } - this._isEnabled = value; - } - - public get isEnabled() { - return this._isEnabled; - } - - constructor( - private connectionManager: ConnectionManager, - private readonly stateStorage: StateStorage, - private codeSynchroniser: CodeSynchronizer, - private readonly telemetry: Telemetry - ) { - this.disposables.push( - this.connectionManager.onDidChangeCluster(async (cluster) => { - if (this.currentCluster?.name === cluster?.name) { - return; - } - this.currentCluster = cluster; - this.verifyCluster(cluster); - }), - this.connectionManager.onDidChangeState(async (state) => { - if (state === "CONNECTED") { - await this.verifyWorkspaceConfigs(); - } else { - this.isEnabled = undefined; - } - }), - this.codeSynchroniser.onDidChangeState(async (state) => { - if ( - workspaceConfigs.syncDestinationType === "repo" && - state === "FILES_IN_REPOS_DISABLED" - ) { - await window.showErrorMessage( - "Sync failed. Files in Repos is disabled for the current workspace. Please contact your system admin to enable it for your workspace." - ); - } else if ( - workspaceConfigs.syncDestinationType === "workspace" && - state === "FILES_IN_WORKSPACE_DISABLED" - ) { - this.isEnabled = false; - const selection = await window.showErrorMessage( - "Sync failed. Files in Workspace is disabled for the current workspace.", - "Switch to Repos", - "Ignore" - ); - - if (selection === "Switch to Repos") { - switchToRepos(); - } - } - }) - ); - } - - async verifyCluster(cluster?: Cluster) { - if (cluster === undefined) { - return; - } - if (await dbrBelowThreshold(cluster)) { - if (workspaceConfigs.syncDestinationType === "repo") { - return; - } - const message = - "Files in workspace is not supported on clusters with DBR < 11.2."; - const selection = await window.showErrorMessage( - message, - "Switch to Repos", - "Ignore" - ); - if (selection === "Switch to Repos") { - switchToRepos(); - } - } else { - if ( - workspaceConfigs.enableFilesInWorkspace || - !(await this.isEnabledForWorkspace()) || - this.stateStorage.get("databricks.wsfs.skipSwitchToWorkspace") - ) { - return; - } - switchToWorkspacePrompt(this.stateStorage, this.telemetry); - } - } - - async isEnabledForWorkspace() { - if (this.connectionManager.state === "DISCONNECTED") { - return false; - } - await this.connectionManager.waitForConnect(); - if (this.isEnabled !== undefined) { - return this.isEnabled; - } - const rootPath = - this.connectionManager.databricksWorkspace?.workspaceFsRoot; - if (!rootPath || !this.connectionManager.workspaceClient) { - return false; - } - - const rootDir = await WorkspaceFsEntity.fromPath( - this.connectionManager.workspaceClient, - rootPath.path - ); - - if (!WorkspaceFsUtils.isDirectory(rootDir)) { - return false; - } - try { - await rootDir.createFile( - ".sentinal.tmp", - "This file is autogenerated by the Databricks Extension for VS Code" - ); - } catch (e: unknown) { - if (e instanceof Error) { - if ( - e.message.match( - /.*(Files in Workspace is disabled|FEATURE_DISABLED).*/ - ) - ) { - this.isEnabled = false; - return this.isEnabled; - } - } - } - - this.isEnabled = true; - return this.isEnabled; - } - - async verifyWorkspaceConfigs() { - if ( - workspaceConfigs.enableFilesInWorkspace && - !(await this.isEnabledForWorkspace()) - ) { - const selection = await window.showErrorMessage( - "Files in workspace is not enabled for your workspace", - "Switch to Repos", - "Ignore" - ); - - if (selection === "Switch to Repos") { - switchToRepos(); - } - } - } - - dispose() { - this.disposables.forEach((i) => i.dispose()); - } -} diff --git a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsCommands.ts b/packages/databricks-vscode/src/workspace-fs/WorkspaceFsCommands.ts index 08b95645d..b829664fe 100644 --- a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsCommands.ts +++ b/packages/databricks-vscode/src/workspace-fs/WorkspaceFsCommands.ts @@ -5,15 +5,12 @@ import { WorkspaceFsUtils, } from "../sdk-extensions"; import {context, Context} from "@databricks/databricks-sdk/dist/context"; -import {Disposable, Uri, window} from "vscode"; +import {Disposable, window} from "vscode"; import {ConnectionManager} from "../configuration/ConnectionManager"; -import {RemoteUri, REPO_NAME_SUFFIX} from "../sync/SyncDestination"; import {Loggers} from "../logger"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; import {createDirWizard} from "./createDirectoryWizard"; import {WorkspaceFsDataProvider} from "./WorkspaceFsDataProvider"; -import path from "node:path"; -import {StateStorage} from "../vscode-objs/StateStorage"; +import {WorkspaceFolderManager} from "../vscode-objs/WorkspaceFolderManager"; const withLogContext = logging.withLogContext; @@ -21,51 +18,16 @@ export class WorkspaceFsCommands implements Disposable { private disposables: Disposable[] = []; constructor( - private workspaceFolder: Uri, - private readonly stateStorage: StateStorage, + private workspaceFolderManager: WorkspaceFolderManager, private connectionManager: ConnectionManager, private workspaceFsDataProvider: WorkspaceFsDataProvider - ) { - this.disposables.push( - this.connectionManager.onDidChangeState(async (state) => { - if ( - state !== "CONNECTED" || - !workspaceConfigs.enableFilesInWorkspace || - this.connectionManager.syncDestinationMapper !== undefined - ) { - return; - } - - const root = await this.getValidRoot( - this.connectionManager.databricksWorkspace?.currentFsRoot - .path - ); - - const element = await root?.mkdir( - `${path.basename( - this.workspaceFolder.fsPath - )}-${this.stateStorage - .get("databricks.fixedUUID") - .slice(0, 8)}` - ); - if (element) { - await this.connectionManager.attachSyncDestination( - new RemoteUri(element.path) - ); - } - }) - ); - } + ) {} @withLogContext(Loggers.Extension) async getValidRoot( rootPath?: string, @context ctx?: Context ): Promise { - if (!workspaceConfigs.enableFilesInWorkspace) { - return; - } - if (!this.connectionManager.workspaceClient) { window.showErrorMessage( `Please login first to create a new directory` @@ -114,21 +76,15 @@ export class WorkspaceFsCommands implements Disposable { const root = await this.getValidRoot(rootPath, ctx); const inputPath = await createDirWizard( - this.workspaceFolder, - workspaceConfigs.enableFilesInWorkspace - ? "Directory Name" - : "Repo Name", + this.workspaceFolderManager.activeWorkspaceFolder.uri, + "Directory Name", root ); let created: WorkspaceFsEntity | undefined; if (inputPath !== undefined) { try { - if (!workspaceConfigs.enableFilesInWorkspace) { - created = await this.createRepo( - rootPath + "/" + inputPath + REPO_NAME_SUFFIX - ); - } else if (root) { + if (root) { created = await root.mkdir(inputPath); } } catch (e: unknown) { diff --git a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsWorkflowWrapper.test.ts b/packages/databricks-vscode/src/workspace-fs/WorkspaceFsWorkflowWrapper.test.ts index 0f08207b8..36c97d8ea 100644 --- a/packages/databricks-vscode/src/workspace-fs/WorkspaceFsWorkflowWrapper.test.ts +++ b/packages/databricks-vscode/src/workspace-fs/WorkspaceFsWorkflowWrapper.test.ts @@ -236,7 +236,7 @@ describe(__filename, async () => { "dbutils.library.restartPython()", "print('hello2')", ]; - writeFile( + await writeFile( localFilePath.path, comment.concat(data).join("\n"), "utf-8" @@ -443,7 +443,7 @@ describe(__filename, async () => { }, ], }; - writeFile( + await writeFile( localFilePath.path, JSON.stringify(originalData), "utf-8" diff --git a/packages/databricks-vscode/src/workspace-fs/createDirectoryWizard.ts b/packages/databricks-vscode/src/workspace-fs/createDirectoryWizard.ts index a53468b8d..a591b5d21 100644 --- a/packages/databricks-vscode/src/workspace-fs/createDirectoryWizard.ts +++ b/packages/databricks-vscode/src/workspace-fs/createDirectoryWizard.ts @@ -1,7 +1,6 @@ import {Uri, window} from "vscode"; import path from "path"; import {WorkspaceFsDir} from "../sdk-extensions"; -import {workspaceConfigs} from "../vscode-objs/WorkspaceConfigs"; export async function createDirWizard( workspaceFolder: Uri, @@ -13,7 +12,7 @@ export async function createDirWizard( placeHolder: path.basename(workspaceFolder.fsPath), value: path.basename(workspaceFolder.fsPath), validateInput: (input) => { - if (workspaceConfigs.enableFilesInWorkspace && root) { + if (root) { const childPath = root.getAbsoluteChildPath(input); if (childPath === undefined || childPath === root.path) { return `The path must be a child of ${root.path}`; diff --git a/packages/databricks-vscode/src/workspace-fs/index.ts b/packages/databricks-vscode/src/workspace-fs/index.ts index 0305fc1a5..e5f73a55e 100644 --- a/packages/databricks-vscode/src/workspace-fs/index.ts +++ b/packages/databricks-vscode/src/workspace-fs/index.ts @@ -1,3 +1,2 @@ export * from "./WorkspaceFsDataProvider"; export * from "./WorkspaceFsCommands"; -export * from "./WorkspaceFsAccessVerifier"; diff --git a/yarn.lock b/yarn.lock index 7280c9353..835ce02bc 100644 --- a/yarn.lock +++ b/yarn.lock @@ -22,97 +22,7 @@ __metadata: languageName: node linkType: hard -"@azure/abort-controller@npm:^1.0.0": - 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