diff --git a/.github/workflows/test_destination_databricks.yml b/.github/workflows/test_destination_databricks.yml new file mode 100644 index 0000000000..f301a1b9ed --- /dev/null +++ b/.github/workflows/test_destination_databricks.yml @@ -0,0 +1,88 @@ + +name: test databricks + +on: + pull_request: + branches: + - master + - devel + workflow_dispatch: + +env: + DLT_SECRETS_TOML: ${{ secrets.DLT_SECRETS_TOML }} + + RUNTIME__SENTRY_DSN: https://6f6f7b6f8e0f458a89be4187603b55fe@o1061158.ingest.sentry.io/4504819859914752 + RUNTIME__LOG_LEVEL: ERROR + + ACTIVE_DESTINATIONS: "[\"databricks\"]" + ALL_FILESYSTEM_DRIVERS: "[\"memory\"]" + +jobs: + get_docs_changes: + uses: ./.github/workflows/get_docs_changes.yml + if: ${{ !github.event.pull_request.head.repo.fork }} + + run_loader: + name: Tests Databricks loader + needs: get_docs_changes + if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' + strategy: + fail-fast: false + matrix: + os: ["ubuntu-latest"] + # os: ["ubuntu-latest", "macos-latest", "windows-latest"] + defaults: + run: + shell: bash + runs-on: ${{ matrix.os }} + + steps: + + - name: Check out + uses: actions/checkout@master + + - name: Setup Python + uses: actions/setup-python@v4 + with: + python-version: "3.10.x" + + - name: Install Poetry + uses: snok/install-poetry@v1.3.2 + with: + virtualenvs-create: true + virtualenvs-in-project: true + installer-parallel: true + + - name: Load cached venv + id: cached-poetry-dependencies + uses: actions/cache@v3 + with: + path: .venv + key: venv-${{ runner.os }}-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('**/poetry.lock') }}-gcp + + - name: Install dependencies + run: poetry install --no-interaction -E databricks -E s3 -E gs -E az -E parquet --with sentry-sdk --with pipeline + + - name: create secrets.toml + run: pwd && echo "$DLT_SECRETS_TOML" > tests/.dlt/secrets.toml + + - run: | + poetry run pytest tests/load + if: runner.os != 'Windows' + name: Run tests Linux/MAC + - run: | + poetry run pytest tests/load + if: runner.os == 'Windows' + name: Run tests Windows + shell: cmd + + matrix_job_required_check: + name: Databricks loader tests + needs: run_loader + runs-on: ubuntu-latest + if: always() + steps: + - name: Check matrix job results + if: contains(needs.*.result, 'failure') || contains(needs.*.result, 'cancelled') + run: | + echo "One or more matrix job tests failed or were cancelled. You may need to re-run them." && exit 1 diff --git a/.github/workflows/test_destination_mssql.yml b/.github/workflows/test_destination_mssql.yml index b8ea1db2d4..d1da25c067 100644 --- a/.github/workflows/test_destination_mssql.yml +++ b/.github/workflows/test_destination_mssql.yml @@ -71,11 +71,11 @@ jobs: run: pwd && echo "$DLT_SECRETS_TOML" > tests/.dlt/secrets.toml - run: | - poetry run pytest tests/load --ignore tests/load/pipeline/test_dbt_helper.py + poetry run pytest tests/load if: runner.os != 'Windows' name: Run tests Linux/MAC - run: | - poetry run pytest tests/load --ignore tests/load/pipeline/test_dbt_helper.py + poetry run pytest tests/load if: runner.os == 'Windows' name: Run tests Windows shell: cmd diff --git a/.github/workflows/test_destination_synapse.yml b/.github/workflows/test_destination_synapse.yml new file mode 100644 index 0000000000..ecd890d32a --- /dev/null +++ b/.github/workflows/test_destination_synapse.yml @@ -0,0 +1,90 @@ +name: test synapse + +on: + pull_request: + branches: + - master + - devel + workflow_dispatch: + +env: + DLT_SECRETS_TOML: ${{ secrets.DLT_SECRETS_TOML }} + + RUNTIME__SENTRY_DSN: https://cf6086f7d263462088b9fb9f9947caee@o4505514867163136.ingest.sentry.io/4505516212682752 + RUNTIME__LOG_LEVEL: ERROR + + ACTIVE_DESTINATIONS: "[\"synapse\"]" + ALL_FILESYSTEM_DRIVERS: "[\"memory\"]" + +jobs: + get_docs_changes: + uses: ./.github/workflows/get_docs_changes.yml + if: ${{ !github.event.pull_request.head.repo.fork }} + + run_loader: + name: Tests Synapse loader + needs: get_docs_changes + if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' + strategy: + fail-fast: false + matrix: + os: ["ubuntu-latest"] + defaults: + run: + shell: bash + runs-on: ${{ matrix.os }} + + steps: + + - name: Check out + uses: actions/checkout@master + + - name: Install ODBC driver for SQL Server + run: | + sudo ACCEPT_EULA=Y apt-get install --yes msodbcsql18 + + - name: Setup Python + uses: actions/setup-python@v4 + with: + python-version: "3.10.x" + + - name: Install Poetry + uses: snok/install-poetry@v1.3.2 + with: + virtualenvs-create: true + virtualenvs-in-project: true + installer-parallel: true + + - name: Load cached venv + id: cached-poetry-dependencies + uses: actions/cache@v3 + with: + path: .venv + key: venv-${{ runner.os }}-${{ steps.setup-python.outputs.python-version }}-${{ hashFiles('**/poetry.lock') }}-gcp + + - name: Install dependencies + run: poetry install --no-interaction -E synapse -E parquet --with sentry-sdk --with pipeline + + - name: create secrets.toml + run: pwd && echo "$DLT_SECRETS_TOML" > tests/.dlt/secrets.toml + + - run: | + poetry run pytest tests/load + if: runner.os != 'Windows' + name: Run tests Linux/MAC + - run: | + poetry run pytest tests/load + if: runner.os == 'Windows' + name: Run tests Windows + shell: cmd + + matrix_job_required_check: + name: Synapse loader tests + needs: run_loader + runs-on: ubuntu-latest + if: always() + steps: + - name: Check matrix job results + if: contains(needs.*.result, 'failure') || contains(needs.*.result, 'cancelled') + run: | + echo "One or more matrix job tests failed or were cancelled. You may need to re-run them." && exit 1 diff --git a/dlt/common/configuration/specs/aws_credentials.py b/dlt/common/configuration/specs/aws_credentials.py index f6df1d8cce..ee7360e2cb 100644 --- a/dlt/common/configuration/specs/aws_credentials.py +++ b/dlt/common/configuration/specs/aws_credentials.py @@ -38,6 +38,13 @@ def to_native_representation(self) -> Dict[str, Optional[str]]: """Return a dict that can be passed as kwargs to boto3 session""" return dict(self) + def to_session_credentials(self) -> Dict[str, str]: + return dict( + aws_access_key_id=self.aws_access_key_id, + aws_secret_access_key=self.aws_secret_access_key, + aws_session_token=self.aws_session_token, + ) + @configspec class AwsCredentials(AwsCredentialsWithoutDefaults, CredentialsWithDefault): @@ -47,6 +54,23 @@ def on_partial(self) -> None: if self._from_session(session) and not self.is_partial(): self.resolve() + def to_session_credentials(self) -> Dict[str, str]: + """Return configured or new aws session token""" + if self.aws_session_token and self.aws_access_key_id and self.aws_secret_access_key: + return dict( + aws_access_key_id=self.aws_access_key_id, + aws_secret_access_key=self.aws_secret_access_key, + aws_session_token=self.aws_session_token, + ) + sess = self._to_botocore_session() + client = sess.create_client("sts") + token = client.get_session_token() + return dict( + aws_access_key_id=token["Credentials"]["AccessKeyId"], + aws_secret_access_key=token["Credentials"]["SecretAccessKey"], + aws_session_token=token["Credentials"]["SessionToken"], + ) + def _to_botocore_session(self) -> Any: try: import botocore.session diff --git a/dlt/common/data_writers/escape.py b/dlt/common/data_writers/escape.py index 5bf8f29ccb..5460657253 100644 --- a/dlt/common/data_writers/escape.py +++ b/dlt/common/data_writers/escape.py @@ -98,8 +98,14 @@ def escape_mssql_literal(v: Any) -> Any: json.dumps(v), prefix="N'", escape_dict=MS_SQL_ESCAPE_DICT, escape_re=MS_SQL_ESCAPE_RE ) if isinstance(v, bytes): - base_64_string = base64.b64encode(v).decode("ascii") - return f"""CAST('' AS XML).value('xs:base64Binary("{base_64_string}")', 'VARBINARY(MAX)')""" + from dlt.destinations.impl.mssql.mssql import VARBINARY_MAX_N + + if len(v) <= VARBINARY_MAX_N: + n = str(len(v)) + else: + n = "MAX" + return f"CONVERT(VARBINARY({n}), '{v.hex()}', 2)" + if isinstance(v, bool): return str(int(v)) if v is None: @@ -124,3 +130,24 @@ def escape_snowflake_identifier(v: str) -> str: # Snowcase uppercase all identifiers unless quoted. Match this here so queries on information schema work without issue # See also https://docs.snowflake.com/en/sql-reference/identifiers-syntax#double-quoted-identifiers return escape_postgres_identifier(v.upper()) + + +escape_databricks_identifier = escape_bigquery_identifier + + +DATABRICKS_ESCAPE_DICT = {"'": "\\'", "\\": "\\\\", "\n": "\\n", "\r": "\\r"} + + +def escape_databricks_literal(v: Any) -> Any: + if isinstance(v, str): + return _escape_extended(v, prefix="'", escape_dict=DATABRICKS_ESCAPE_DICT) + if isinstance(v, (datetime, date, time)): + return f"'{v.isoformat()}'" + if isinstance(v, (list, dict)): + return _escape_extended(json.dumps(v), prefix="'", escape_dict=DATABRICKS_ESCAPE_DICT) + if isinstance(v, bytes): + return f"X'{v.hex()}'" + if v is None: + return "NULL" + + return str(v) diff --git a/dlt/common/data_writers/writers.py b/dlt/common/data_writers/writers.py index 0f9ff09259..0f3640da1e 100644 --- a/dlt/common/data_writers/writers.py +++ b/dlt/common/data_writers/writers.py @@ -175,18 +175,29 @@ def write_header(self, columns_schema: TTableSchemaColumns) -> None: # do not write INSERT INTO command, this must be added together with table name by the loader self._f.write("INSERT INTO {}(") self._f.write(",".join(map(self._caps.escape_identifier, headers))) - self._f.write(")\nVALUES\n") + if self._caps.insert_values_writer_type == "default": + self._f.write(")\nVALUES\n") + elif self._caps.insert_values_writer_type == "select_union": + self._f.write(")\n") def write_data(self, rows: Sequence[Any]) -> None: super().write_data(rows) - def write_row(row: StrAny) -> None: + def write_row(row: StrAny, last_row: bool = False) -> None: output = ["NULL"] * len(self._headers_lookup) for n, v in row.items(): output[self._headers_lookup[n]] = self._caps.escape_literal(v) - self._f.write("(") - self._f.write(",".join(output)) - self._f.write(")") + if self._caps.insert_values_writer_type == "default": + self._f.write("(") + self._f.write(",".join(output)) + self._f.write(")") + if not last_row: + self._f.write(",\n") + elif self._caps.insert_values_writer_type == "select_union": + self._f.write("SELECT ") + self._f.write(",".join(output)) + if not last_row: + self._f.write("\nUNION ALL\n") # if next chunk add separator if self._chunks_written > 0: @@ -195,10 +206,9 @@ def write_row(row: StrAny) -> None: # write rows for row in rows[:-1]: write_row(row) - self._f.write(",\n") # write last row without separator so we can write footer eventually - write_row(rows[-1]) + write_row(rows[-1], last_row=True) self._chunks_written += 1 def write_footer(self) -> None: diff --git a/dlt/common/destination/capabilities.py b/dlt/common/destination/capabilities.py index 2596b2bf99..a78a31fdf3 100644 --- a/dlt/common/destination/capabilities.py +++ b/dlt/common/destination/capabilities.py @@ -52,6 +52,10 @@ class DestinationCapabilitiesContext(ContainerInjectableContext): schema_supports_numeric_precision: bool = True timestamp_precision: int = 6 max_rows_per_insert: Optional[int] = None + insert_values_writer_type: str = "default" + supports_multiple_statements: bool = True + supports_clone_table: bool = False + """Destination supports CREATE TABLE ... CLONE ... statements""" # do not allow to create default value, destination caps must be always explicitly inserted into container can_create_default: ClassVar[bool] = False @@ -77,4 +81,5 @@ def generic_capabilities( caps.is_max_text_data_type_length_in_bytes = True caps.supports_ddl_transactions = True caps.supports_transactions = True + caps.supports_multiple_statements = True return caps diff --git a/dlt/common/schema/schema.py b/dlt/common/schema/schema.py index e95699b91e..ccfc038085 100644 --- a/dlt/common/schema/schema.py +++ b/dlt/common/schema/schema.py @@ -546,12 +546,20 @@ def data_tables(self, include_incomplete: bool = False) -> List[TTableSchema]: ) ] + def data_table_names(self) -> List[str]: + """Returns list of table table names. Excludes dlt table names.""" + return [t["name"] for t in self.data_tables()] + def dlt_tables(self) -> List[TTableSchema]: """Gets dlt tables""" return [ t for t in self._schema_tables.values() if t["name"].startswith(self._dlt_tables_prefix) ] + def dlt_table_names(self) -> List[str]: + """Returns list of dlt table names.""" + return [t["name"] for t in self.dlt_tables()] + def get_preferred_type(self, col_name: str) -> Optional[TDataType]: return next((m[1] for m in self._compiled_preferred_types if m[0].search(col_name)), None) diff --git a/dlt/common/time.py b/dlt/common/time.py index ed390c28bf..4f4dd05ef0 100644 --- a/dlt/common/time.py +++ b/dlt/common/time.py @@ -138,6 +138,43 @@ def ensure_pendulum_time(value: Union[str, datetime.time]) -> pendulum.Time: raise TypeError(f"Cannot coerce {value} to a pendulum.Time object.") +def to_py_datetime(value: datetime.datetime) -> datetime.datetime: + """Convert a pendulum.DateTime to a py datetime object. + + Args: + value: The value to convert. Can be a pendulum.DateTime or datetime. + + Returns: + A py datetime object + """ + if isinstance(value, pendulum.DateTime): + return datetime.datetime( + value.year, + value.month, + value.day, + value.hour, + value.minute, + value.second, + value.microsecond, + value.tzinfo, + ) + return value + + +def to_py_date(value: datetime.date) -> datetime.date: + """Convert a pendulum.Date to a py date object. + + Args: + value: The value to convert. Can be a pendulum.Date or date. + + Returns: + A py date object + """ + if isinstance(value, pendulum.Date): + return datetime.date(value.year, value.month, value.day) + return value + + def _datetime_from_ts_or_iso( value: Union[int, float, str] ) -> Union[pendulum.DateTime, pendulum.Date, pendulum.Time]: diff --git a/dlt/destinations/__init__.py b/dlt/destinations/__init__.py index 980c4ce7f2..c0a0b419c1 100644 --- a/dlt/destinations/__init__.py +++ b/dlt/destinations/__init__.py @@ -10,6 +10,8 @@ from dlt.destinations.impl.qdrant.factory import qdrant from dlt.destinations.impl.motherduck.factory import motherduck from dlt.destinations.impl.weaviate.factory import weaviate +from dlt.destinations.impl.synapse.factory import synapse +from dlt.destinations.impl.databricks.factory import databricks __all__ = [ @@ -25,4 +27,6 @@ "qdrant", "motherduck", "weaviate", + "synapse", + "databricks", ] diff --git a/dlt/destinations/adapters.py b/dlt/destinations/adapters.py index b8f12599dc..22c98d4f5a 100644 --- a/dlt/destinations/adapters.py +++ b/dlt/destinations/adapters.py @@ -2,5 +2,6 @@ from dlt.destinations.impl.weaviate import weaviate_adapter from dlt.destinations.impl.qdrant import qdrant_adapter +from dlt.destinations.impl.synapse import synapse_adapter -__all__ = ["weaviate_adapter", "qdrant_adapter"] +__all__ = ["weaviate_adapter", "qdrant_adapter", "synapse_adapter"] diff --git a/dlt/destinations/impl/athena/athena.py b/dlt/destinations/impl/athena/athena.py index 4837f0dbdf..91525d771c 100644 --- a/dlt/destinations/impl/athena/athena.py +++ b/dlt/destinations/impl/athena/athena.py @@ -232,7 +232,7 @@ def drop_tables(self, *tables: str) -> None: statements = [ f"DROP TABLE IF EXISTS {self.make_qualified_ddl_table_name(table)};" for table in tables ] - self.execute_fragments(statements) + self.execute_many(statements) @contextmanager @raise_database_error @@ -351,9 +351,7 @@ def _from_db_type( return self.type_mapper.from_db_type(hive_t, precision, scale) def _get_column_def_sql(self, c: TColumnSchema, table_format: TTableFormat = None) -> str: - return ( - f"{self.sql_client.escape_ddl_identifier(c['name'])} {self.type_mapper.to_db_type(c, table_format)}" - ) + return f"{self.sql_client.escape_ddl_identifier(c['name'])} {self.type_mapper.to_db_type(c, table_format)}" def _get_table_update_sql( self, table_name: str, new_columns: Sequence[TColumnSchema], generate_alter: bool @@ -378,15 +376,19 @@ def _get_table_update_sql( # use qualified table names qualified_table_name = self.sql_client.make_qualified_ddl_table_name(table_name) if is_iceberg and not generate_alter: - sql.append(f"""CREATE TABLE {qualified_table_name} + sql.append( + f"""CREATE TABLE {qualified_table_name} ({columns}) LOCATION '{location}' - TBLPROPERTIES ('table_type'='ICEBERG', 'format'='parquet');""") + TBLPROPERTIES ('table_type'='ICEBERG', 'format'='parquet');""" + ) elif not generate_alter: - sql.append(f"""CREATE EXTERNAL TABLE {qualified_table_name} + sql.append( + f"""CREATE EXTERNAL TABLE {qualified_table_name} ({columns}) STORED AS PARQUET - LOCATION '{location}';""") + LOCATION '{location}';""" + ) # alter table to add new columns at the end else: sql.append(f"""ALTER TABLE {qualified_table_name} ADD COLUMNS ({columns});""") diff --git a/dlt/destinations/impl/bigquery/__init__.py b/dlt/destinations/impl/bigquery/__init__.py index 1304bd72bb..6d1491817a 100644 --- a/dlt/destinations/impl/bigquery/__init__.py +++ b/dlt/destinations/impl/bigquery/__init__.py @@ -20,5 +20,6 @@ def capabilities() -> DestinationCapabilitiesContext: caps.max_text_data_type_length = 10 * 1024 * 1024 caps.is_max_text_data_type_length_in_bytes = True caps.supports_ddl_transactions = False + caps.supports_clone_table = True return caps diff --git a/dlt/destinations/impl/bigquery/bigquery.py b/dlt/destinations/impl/bigquery/bigquery.py index 254184b96d..1058b1d2c9 100644 --- a/dlt/destinations/impl/bigquery/bigquery.py +++ b/dlt/destinations/impl/bigquery/bigquery.py @@ -30,6 +30,7 @@ from dlt.destinations.impl.bigquery.configuration import BigQueryClientConfiguration from dlt.destinations.impl.bigquery.sql_client import BigQuerySqlClient, BQ_TERMINAL_REASONS from dlt.destinations.job_client_impl import SqlJobClientWithStaging +from dlt.destinations.sql_jobs import SqlMergeJob, SqlJobParams from dlt.destinations.job_impl import NewReferenceJob from dlt.destinations.sql_client import SqlClientBase from dlt.destinations.sql_jobs import SqlMergeJob, SqlStagingCopyJob, SqlJobParams @@ -149,28 +150,6 @@ def gen_key_table_clauses( return sql -class BigqueryStagingCopyJob(SqlStagingCopyJob): - @classmethod - def generate_sql( - cls, - table_chain: Sequence[TTableSchema], - sql_client: SqlClientBase[Any], - params: Optional[SqlJobParams] = None, - ) -> List[str]: - sql: List[str] = [] - for table in table_chain: - with sql_client.with_staging_dataset(staging=True): - staging_table_name = sql_client.make_qualified_table_name(table["name"]) - table_name = sql_client.make_qualified_table_name(table["name"]) - sql.extend( - ( - f"DROP TABLE IF EXISTS {table_name};", - f"CREATE TABLE {table_name} CLONE {staging_table_name};", - ) - ) - return sql - - class BigQueryClient(SqlJobClientWithStaging, SupportsStagingDestination): capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() @@ -190,13 +169,6 @@ def __init__(self, schema: Schema, config: BigQueryClientConfiguration) -> None: def _create_merge_followup_jobs(self, table_chain: Sequence[TTableSchema]) -> List[NewLoadJob]: return [BigQueryMergeJob.from_table_chain(table_chain, self.sql_client)] - def _create_replace_followup_jobs( - self, table_chain: Sequence[TTableSchema] - ) -> List[NewLoadJob]: - if self.config.replace_strategy == "staging-optimized": - return [BigqueryStagingCopyJob.from_table_chain(table_chain, self.sql_client)] - return super()._create_replace_followup_jobs(table_chain) - def restore_file_load(self, file_path: str) -> LoadJob: """Returns a completed SqlLoadJob or restored BigQueryLoadJob @@ -280,9 +252,9 @@ def _get_table_update_sql( elif (c := partition_list[0])["data_type"] == "date": sql[0] = f"{sql[0]}\nPARTITION BY {self.capabilities.escape_identifier(c['name'])}" elif (c := partition_list[0])["data_type"] == "timestamp": - sql[0] = ( - f"{sql[0]}\nPARTITION BY DATE({self.capabilities.escape_identifier(c['name'])})" - ) + sql[ + 0 + ] = f"{sql[0]}\nPARTITION BY DATE({self.capabilities.escape_identifier(c['name'])})" # Automatic partitioning of an INT64 type requires us to be prescriptive - we treat the column as a UNIX timestamp. # This is due to the bounds requirement of GENERATE_ARRAY function for partitioning. # The 10,000 partitions limit makes it infeasible to cover the entire `bigint` range. @@ -300,9 +272,7 @@ def _get_table_update_sql( def _get_column_def_sql(self, c: TColumnSchema, table_format: TTableFormat = None) -> str: name = self.capabilities.escape_identifier(c["name"]) - return ( - f"{name} {self.type_mapper.to_db_type(c, table_format)} {self._gen_not_null(c.get('nullable', True))}" - ) + return f"{name} {self.type_mapper.to_db_type(c, table_format)} {self._gen_not_null(c.get('nullable', True))}" def get_storage_table(self, table_name: str) -> Tuple[bool, TTableSchemaColumns]: schema_table: TTableSchemaColumns = {} diff --git a/dlt/destinations/impl/databricks/__init__.py b/dlt/destinations/impl/databricks/__init__.py new file mode 100644 index 0000000000..f63d294818 --- /dev/null +++ b/dlt/destinations/impl/databricks/__init__.py @@ -0,0 +1,30 @@ +from dlt.common.destination import DestinationCapabilitiesContext +from dlt.common.data_writers.escape import escape_databricks_identifier, escape_databricks_literal +from dlt.common.arithmetics import DEFAULT_NUMERIC_PRECISION, DEFAULT_NUMERIC_SCALE + +from dlt.destinations.impl.databricks.configuration import DatabricksClientConfiguration + + +def capabilities() -> DestinationCapabilitiesContext: + caps = DestinationCapabilitiesContext() + caps.preferred_loader_file_format = "insert_values" + caps.supported_loader_file_formats = ["insert_values"] + caps.preferred_staging_file_format = "jsonl" + caps.supported_staging_file_formats = ["jsonl", "parquet"] + caps.escape_identifier = escape_databricks_identifier + caps.escape_literal = escape_databricks_literal + caps.decimal_precision = (DEFAULT_NUMERIC_PRECISION, DEFAULT_NUMERIC_SCALE) + caps.wei_precision = (DEFAULT_NUMERIC_PRECISION, 0) + caps.max_identifier_length = 255 + caps.max_column_identifier_length = 255 + caps.max_query_length = 2 * 1024 * 1024 + caps.is_max_query_length_in_bytes = True + caps.max_text_data_type_length = 16 * 1024 * 1024 + caps.is_max_text_data_type_length_in_bytes = True + caps.supports_ddl_transactions = False + caps.supports_truncate_command = True + # caps.supports_transactions = False + caps.alter_add_multi_column = True + caps.supports_multiple_statements = False + caps.supports_clone_table = True + return caps diff --git a/dlt/destinations/impl/databricks/configuration.py b/dlt/destinations/impl/databricks/configuration.py new file mode 100644 index 0000000000..924047e30f --- /dev/null +++ b/dlt/destinations/impl/databricks/configuration.py @@ -0,0 +1,51 @@ +from typing import ClassVar, Final, Optional, Any, Dict, List + +from dlt.common.typing import TSecretStrValue +from dlt.common.configuration.exceptions import ConfigurationValueError +from dlt.common.configuration.specs.base_configuration import CredentialsConfiguration, configspec +from dlt.common.destination.reference import DestinationClientDwhWithStagingConfiguration + + +@configspec +class DatabricksCredentials(CredentialsConfiguration): + catalog: str = None + server_hostname: str = None + http_path: str = None + access_token: Optional[TSecretStrValue] = None + http_headers: Optional[Dict[str, str]] = None + session_configuration: Optional[Dict[str, Any]] = None + """Dict of session parameters that will be passed to `databricks.sql.connect`""" + connection_parameters: Optional[Dict[str, Any]] = None + """Additional keyword arguments that are passed to `databricks.sql.connect`""" + socket_timeout: Optional[int] = 180 + + __config_gen_annotations__: ClassVar[List[str]] = [ + "server_hostname", + "http_path", + "catalog", + "access_token", + ] + + def to_connector_params(self) -> Dict[str, Any]: + return dict( + catalog=self.catalog, + server_hostname=self.server_hostname, + http_path=self.http_path, + access_token=self.access_token, + session_configuration=self.session_configuration or {}, + _socket_timeout=self.socket_timeout, + **(self.connection_parameters or {}), + ) + + +@configspec +class DatabricksClientConfiguration(DestinationClientDwhWithStagingConfiguration): + destination_type: Final[str] = "databricks" # type: ignore[misc] + credentials: DatabricksCredentials + + def __str__(self) -> str: + """Return displayable destination location""" + if self.staging_config: + return str(self.staging_config.credentials) + else: + return "[no staging set]" diff --git a/dlt/destinations/impl/databricks/databricks.py b/dlt/destinations/impl/databricks/databricks.py new file mode 100644 index 0000000000..b5a404302f --- /dev/null +++ b/dlt/destinations/impl/databricks/databricks.py @@ -0,0 +1,317 @@ +from typing import ClassVar, Dict, Optional, Sequence, Tuple, List, Any, Iterable, Type, cast +from urllib.parse import urlparse, urlunparse + +from dlt.common.destination import DestinationCapabilitiesContext +from dlt.common.destination.reference import ( + FollowupJob, + NewLoadJob, + TLoadJobState, + LoadJob, + CredentialsConfiguration, + SupportsStagingDestination, +) +from dlt.common.configuration.specs import ( + AwsCredentialsWithoutDefaults, + AzureCredentials, + AzureCredentialsWithoutDefaults, +) +from dlt.common.data_types import TDataType +from dlt.common.storages.file_storage import FileStorage +from dlt.common.schema import TColumnSchema, Schema, TTableSchemaColumns +from dlt.common.schema.typing import TTableSchema, TColumnType, TSchemaTables, TTableFormat +from dlt.common.schema.utils import table_schema_has_type + + +from dlt.destinations.insert_job_client import InsertValuesJobClient +from dlt.destinations.job_impl import EmptyLoadJob +from dlt.destinations.exceptions import LoadJobTerminalException + +from dlt.destinations.impl.databricks import capabilities +from dlt.destinations.impl.databricks.configuration import DatabricksClientConfiguration +from dlt.destinations.impl.databricks.sql_client import DatabricksSqlClient +from dlt.destinations.sql_jobs import SqlMergeJob, SqlJobParams +from dlt.destinations.job_impl import NewReferenceJob +from dlt.destinations.sql_client import SqlClientBase +from dlt.destinations.type_mapping import TypeMapper +from dlt.common.storages import FilesystemConfiguration, fsspec_from_config +from dlt import config + + +class DatabricksTypeMapper(TypeMapper): + sct_to_unbound_dbt = { + "complex": "STRING", # Databricks supports complex types like ARRAY + "text": "STRING", + "double": "DOUBLE", + "bool": "BOOLEAN", + "date": "DATE", + "timestamp": "TIMESTAMP", # TIMESTAMP for local timezone + "bigint": "BIGINT", + "binary": "BINARY", + "decimal": "DECIMAL", # DECIMAL(p,s) format + "time": "STRING", + } + + dbt_to_sct = { + "STRING": "text", + "DOUBLE": "double", + "BOOLEAN": "bool", + "DATE": "date", + "TIMESTAMP": "timestamp", + "BIGINT": "bigint", + "INT": "bigint", + "SMALLINT": "bigint", + "TINYINT": "bigint", + "BINARY": "binary", + "DECIMAL": "decimal", + } + + sct_to_dbt = { + "decimal": "DECIMAL(%i,%i)", + "wei": "DECIMAL(%i,%i)", + } + + def to_db_integer_type( + self, precision: Optional[int], table_format: TTableFormat = None + ) -> str: + if precision is None: + return "BIGINT" + if precision <= 8: + return "TINYINT" + if precision <= 16: + return "SMALLINT" + if precision <= 32: + return "INT" + return "BIGINT" + + def from_db_type( + self, db_type: str, precision: Optional[int] = None, scale: Optional[int] = None + ) -> TColumnType: + # precision and scale arguments here are meaningless as they're not included separately in information schema + # We use full_data_type from databricks which is either in form "typename" or "typename(precision, scale)" + type_parts = db_type.split("(") + if len(type_parts) > 1: + db_type = type_parts[0] + scale_str = type_parts[1].strip(")") + precision, scale = [int(val) for val in scale_str.split(",")] + else: + scale = precision = None + db_type = db_type.upper() + if db_type == "DECIMAL": + if (precision, scale) == self.wei_precision(): + return dict(data_type="wei", precision=precision, scale=scale) + return super().from_db_type(db_type, precision, scale) + + +class DatabricksLoadJob(LoadJob, FollowupJob): + def __init__( + self, + table: TTableSchema, + file_path: str, + table_name: str, + load_id: str, + client: DatabricksSqlClient, + staging_config: FilesystemConfiguration, + ) -> None: + file_name = FileStorage.get_file_name_from_file_path(file_path) + super().__init__(file_name) + staging_credentials = staging_config.credentials + + qualified_table_name = client.make_qualified_table_name(table_name) + + # extract and prepare some vars + bucket_path = orig_bucket_path = ( + NewReferenceJob.resolve_reference(file_path) + if NewReferenceJob.is_reference_job(file_path) + else "" + ) + file_name = ( + FileStorage.get_file_name_from_file_path(bucket_path) if bucket_path else file_name + ) + from_clause = "" + credentials_clause = "" + format_options_clause = "" + + if bucket_path: + bucket_url = urlparse(bucket_path) + bucket_scheme = bucket_url.scheme + # referencing an staged files via a bucket URL requires explicit AWS credentials + if bucket_scheme == "s3" and isinstance( + staging_credentials, AwsCredentialsWithoutDefaults + ): + s3_creds = staging_credentials.to_session_credentials() + credentials_clause = f"""WITH(CREDENTIAL( + AWS_ACCESS_KEY='{s3_creds["aws_access_key_id"]}', + AWS_SECRET_KEY='{s3_creds["aws_secret_access_key"]}', + + AWS_SESSION_TOKEN='{s3_creds["aws_session_token"]}' + )) + """ + from_clause = f"FROM '{bucket_path}'" + elif bucket_scheme in ["az", "abfs"] and isinstance( + staging_credentials, AzureCredentialsWithoutDefaults + ): + # Explicit azure credentials are needed to load from bucket without a named stage + credentials_clause = f"""WITH(CREDENTIAL(AZURE_SAS_TOKEN='{staging_credentials.azure_storage_sas_token}'))""" + # Converts an az:/// to abfss://@.dfs.core.windows.net/ + # as required by snowflake + _path = bucket_url.path + bucket_path = urlunparse( + bucket_url._replace( + scheme="abfss", + netloc=f"{bucket_url.netloc}@{staging_credentials.azure_storage_account_name}.dfs.core.windows.net", + path=_path, + ) + ) + from_clause = f"FROM '{bucket_path}'" + else: + raise LoadJobTerminalException( + file_path, + f"Databricks cannot load data from staging bucket {bucket_path}. Only s3 and azure buckets are supported", + ) + else: + raise LoadJobTerminalException( + file_path, + "Cannot load from local file. Databricks does not support loading from local files. Configure staging with an s3 or azure storage bucket.", + ) + + # decide on source format, stage_file_path will either be a local file or a bucket path + if file_name.endswith(".parquet"): + source_format = "PARQUET" # Only parquet is supported + elif file_name.endswith(".jsonl"): + if not config.get("data_writer.disable_compression"): + raise LoadJobTerminalException( + file_path, + "Databricks loader does not support gzip compressed JSON files. Please disable compression in the data writer configuration: https://dlthub.com/docs/reference/performance#disabling-and-enabling-file-compression", + ) + if table_schema_has_type(table, "decimal"): + raise LoadJobTerminalException( + file_path, + "Databricks loader cannot load DECIMAL type columns from json files. Switch to parquet format to load decimals.", + ) + if table_schema_has_type(table, "binary"): + raise LoadJobTerminalException( + file_path, + "Databricks loader cannot load BINARY type columns from json files. Switch to parquet format to load byte values.", + ) + if table_schema_has_type(table, "complex"): + raise LoadJobTerminalException( + file_path, + "Databricks loader cannot load complex columns (lists and dicts) from json files. Switch to parquet format to load complex types.", + ) + if table_schema_has_type(table, "date"): + raise LoadJobTerminalException( + file_path, + "Databricks loader cannot load DATE type columns from json files. Switch to parquet format to load dates.", + ) + + source_format = "JSON" + format_options_clause = "FORMAT_OPTIONS('inferTimestamp'='true')" + # Databricks fails when trying to load empty json files, so we have to check the file size + fs, _ = fsspec_from_config(staging_config) + file_size = fs.size(orig_bucket_path) + if file_size == 0: # Empty file, do nothing + return + + statement = f"""COPY INTO {qualified_table_name} + {from_clause} + {credentials_clause} + FILEFORMAT = {source_format} + {format_options_clause} + """ + client.execute_sql(statement) + + def state(self) -> TLoadJobState: + return "completed" + + def exception(self) -> str: + raise NotImplementedError() + + +class DatabricksMergeJob(SqlMergeJob): + @classmethod + def _to_temp_table(cls, select_sql: str, temp_table_name: str) -> str: + return f"CREATE TEMPORARY VIEW {temp_table_name} AS {select_sql};" + + @classmethod + def gen_delete_from_sql( + cls, table_name: str, column_name: str, temp_table_name: str, temp_table_column: str + ) -> str: + # Databricks does not support subqueries in DELETE FROM statements so we use a MERGE statement instead + return f"""MERGE INTO {table_name} + USING {temp_table_name} + ON {table_name}.{column_name} = {temp_table_name}.{temp_table_column} + WHEN MATCHED THEN DELETE; + """ + + +class DatabricksClient(InsertValuesJobClient, SupportsStagingDestination): + capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() + + def __init__(self, schema: Schema, config: DatabricksClientConfiguration) -> None: + sql_client = DatabricksSqlClient(config.normalize_dataset_name(schema), config.credentials) + super().__init__(schema, config, sql_client) + self.config: DatabricksClientConfiguration = config + self.sql_client: DatabricksSqlClient = sql_client + self.type_mapper = DatabricksTypeMapper(self.capabilities) + + def start_file_load(self, table: TTableSchema, file_path: str, load_id: str) -> LoadJob: + job = super().start_file_load(table, file_path, load_id) + + if not job: + job = DatabricksLoadJob( + table, + file_path, + table["name"], + load_id, + self.sql_client, + staging_config=cast(FilesystemConfiguration, self.config.staging_config), + ) + return job + + def restore_file_load(self, file_path: str) -> LoadJob: + return EmptyLoadJob.from_file_path(file_path, "completed") + + def _create_merge_followup_jobs(self, table_chain: Sequence[TTableSchema]) -> List[NewLoadJob]: + return [DatabricksMergeJob.from_table_chain(table_chain, self.sql_client)] + + def _make_add_column_sql( + self, new_columns: Sequence[TColumnSchema], table_format: TTableFormat = None + ) -> List[str]: + # Override because databricks requires multiple columns in a single ADD COLUMN clause + return ["ADD COLUMN\n" + ",\n".join(self._get_column_def_sql(c) for c in new_columns)] + + def _get_table_update_sql( + self, + table_name: str, + new_columns: Sequence[TColumnSchema], + generate_alter: bool, + separate_alters: bool = False, + ) -> List[str]: + sql = super()._get_table_update_sql(table_name, new_columns, generate_alter) + + cluster_list = [ + self.capabilities.escape_identifier(c["name"]) for c in new_columns if c.get("cluster") + ] + + if cluster_list: + sql[0] = sql[0] + "\nCLUSTER BY (" + ",".join(cluster_list) + ")" + + return sql + + def _from_db_type( + self, bq_t: str, precision: Optional[int], scale: Optional[int] + ) -> TColumnType: + return self.type_mapper.from_db_type(bq_t, precision, scale) + + def _get_column_def_sql(self, c: TColumnSchema, table_format: TTableFormat = None) -> str: + name = self.capabilities.escape_identifier(c["name"]) + return ( + f"{name} {self.type_mapper.to_db_type(c)} {self._gen_not_null(c.get('nullable', True))}" + ) + + def _get_storage_table_query_columns(self) -> List[str]: + fields = super()._get_storage_table_query_columns() + fields[ + 1 + ] = "full_data_type" # Override because this is the only way to get data type with precision + return fields diff --git a/dlt/destinations/impl/databricks/factory.py b/dlt/destinations/impl/databricks/factory.py new file mode 100644 index 0000000000..7c6c95137d --- /dev/null +++ b/dlt/destinations/impl/databricks/factory.py @@ -0,0 +1,48 @@ +import typing as t + +from dlt.common.destination import Destination, DestinationCapabilitiesContext + +from dlt.destinations.impl.databricks.configuration import ( + DatabricksCredentials, + DatabricksClientConfiguration, +) +from dlt.destinations.impl.databricks import capabilities + +if t.TYPE_CHECKING: + from dlt.destinations.impl.databricks.databricks import DatabricksClient + + +class databricks(Destination[DatabricksClientConfiguration, "DatabricksClient"]): + spec = DatabricksClientConfiguration + + def capabilities(self) -> DestinationCapabilitiesContext: + return capabilities() + + @property + def client_class(self) -> t.Type["DatabricksClient"]: + from dlt.destinations.impl.databricks.databricks import DatabricksClient + + return DatabricksClient + + def __init__( + self, + credentials: t.Union[DatabricksCredentials, t.Dict[str, t.Any], str] = None, + destination_name: t.Optional[str] = None, + environment: t.Optional[str] = None, + **kwargs: t.Any, + ) -> None: + """Configure the Databricks destination to use in a pipeline. + + All arguments provided here supersede other configuration sources such as environment variables and dlt config files. + + Args: + credentials: Credentials to connect to the databricks database. Can be an instance of `DatabricksCredentials` or + a connection string in the format `databricks://user:password@host:port/database` + **kwargs: Additional arguments passed to the destination config + """ + super().__init__( + credentials=credentials, + destination_name=destination_name, + environment=environment, + **kwargs, + ) diff --git a/dlt/destinations/impl/databricks/sql_client.py b/dlt/destinations/impl/databricks/sql_client.py new file mode 100644 index 0000000000..68ea863cc4 --- /dev/null +++ b/dlt/destinations/impl/databricks/sql_client.py @@ -0,0 +1,155 @@ +from contextlib import contextmanager, suppress +from typing import Any, AnyStr, ClassVar, Iterator, Optional, Sequence, List, Union, Dict + +from databricks import sql as databricks_lib +from databricks.sql.client import ( + Connection as DatabricksSqlConnection, + Cursor as DatabricksSqlCursor, +) +from databricks.sql.exc import Error as DatabricksSqlError + +from dlt.common import pendulum +from dlt.common import logger +from dlt.common.destination import DestinationCapabilitiesContext +from dlt.destinations.exceptions import ( + DatabaseTerminalException, + DatabaseTransientException, + DatabaseUndefinedRelation, +) +from dlt.destinations.sql_client import ( + DBApiCursorImpl, + SqlClientBase, + raise_database_error, + raise_open_connection_error, +) +from dlt.destinations.typing import DBApi, DBApiCursor, DBTransaction +from dlt.destinations.impl.databricks.configuration import DatabricksCredentials +from dlt.destinations.impl.databricks import capabilities +from dlt.common.time import to_py_date, to_py_datetime + + +class DatabricksSqlClient(SqlClientBase[DatabricksSqlConnection], DBTransaction): + dbapi: ClassVar[DBApi] = databricks_lib + capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() + + def __init__(self, dataset_name: str, credentials: DatabricksCredentials) -> None: + super().__init__(credentials.catalog, dataset_name) + self._conn: DatabricksSqlConnection = None + self.credentials = credentials + + def open_connection(self) -> DatabricksSqlConnection: + conn_params = self.credentials.to_connector_params() + self._conn = databricks_lib.connect(**conn_params, schema=self.dataset_name) + return self._conn + + @raise_open_connection_error + def close_connection(self) -> None: + if self._conn: + self._conn.close() + self._conn = None + + @contextmanager + def begin_transaction(self) -> Iterator[DBTransaction]: + # Databricks does not support transactions + yield self + + @raise_database_error + def commit_transaction(self) -> None: + # Databricks does not support transactions + pass + + @raise_database_error + def rollback_transaction(self) -> None: + # Databricks does not support transactions + pass + + @property + def native_connection(self) -> "DatabricksSqlConnection": + return self._conn + + def drop_dataset(self) -> None: + self.execute_sql("DROP SCHEMA IF EXISTS %s CASCADE;" % self.fully_qualified_dataset_name()) + + def drop_tables(self, *tables: str) -> None: + # Tables are drop with `IF EXISTS`, but databricks raises when the schema doesn't exist. + # Multi statement exec is safe and the error can be ignored since all tables are in the same schema. + with suppress(DatabaseUndefinedRelation): + super().drop_tables(*tables) + + def execute_sql( + self, sql: AnyStr, *args: Any, **kwargs: Any + ) -> Optional[Sequence[Sequence[Any]]]: + with self.execute_query(sql, *args, **kwargs) as curr: + if curr.description is None: + return None + else: + f = curr.fetchall() + return f + + @contextmanager + @raise_database_error + def execute_query(self, query: AnyStr, *args: Any, **kwargs: Any) -> Iterator[DBApiCursor]: + curr: DBApiCursor = None + # TODO: databricks connector 3.0.0 will use :named paramstyle only + # if args: + # keys = [f"arg{i}" for i in range(len(args))] + # # Replace position arguments (%s) with named arguments (:arg0, :arg1, ...) + # # query = query % tuple(f":{key}" for key in keys) + # db_args = {} + # for key, db_arg in zip(keys, args): + # # Databricks connector doesn't accept pendulum objects + # if isinstance(db_arg, pendulum.DateTime): + # db_arg = to_py_datetime(db_arg) + # elif isinstance(db_arg, pendulum.Date): + # db_arg = to_py_date(db_arg) + # db_args[key] = db_arg + # else: + # db_args = None + db_args: Optional[Union[Dict[str, Any], Sequence[Any]]] + if kwargs: + db_args = kwargs + elif args: + db_args = args + else: + db_args = None + with self._conn.cursor() as curr: + curr.execute(query, db_args) + yield DBApiCursorImpl(curr) # type: ignore[abstract] + + def fully_qualified_dataset_name(self, escape: bool = True) -> str: + if escape: + catalog = self.capabilities.escape_identifier(self.credentials.catalog) + dataset_name = self.capabilities.escape_identifier(self.dataset_name) + else: + catalog = self.credentials.catalog + dataset_name = self.dataset_name + return f"{catalog}.{dataset_name}" + + @staticmethod + def _make_database_exception(ex: Exception) -> Exception: + if isinstance(ex, databricks_lib.ServerOperationError): + if "TABLE_OR_VIEW_NOT_FOUND" in str(ex): + return DatabaseUndefinedRelation(ex) + elif "SCHEMA_NOT_FOUND" in str(ex): + return DatabaseUndefinedRelation(ex) + elif "PARSE_SYNTAX_ERROR" in str(ex): + return DatabaseTransientException(ex) + return DatabaseTerminalException(ex) + elif isinstance(ex, databricks_lib.OperationalError): + return DatabaseTerminalException(ex) + elif isinstance(ex, (databricks_lib.ProgrammingError, databricks_lib.IntegrityError)): + return DatabaseTerminalException(ex) + elif isinstance(ex, databricks_lib.DatabaseError): + return DatabaseTransientException(ex) + else: + return DatabaseTransientException(ex) + + @staticmethod + def _maybe_make_terminal_exception_from_data_error( + databricks_ex: databricks_lib.DatabaseError, + ) -> Optional[Exception]: + return None + + @staticmethod + def is_dbapi_exception(ex: Exception) -> bool: + return isinstance(ex, databricks_lib.DatabaseError) diff --git a/dlt/destinations/impl/mssql/configuration.py b/dlt/destinations/impl/mssql/configuration.py index f33aca4b82..f00998cfb2 100644 --- a/dlt/destinations/impl/mssql/configuration.py +++ b/dlt/destinations/impl/mssql/configuration.py @@ -1,4 +1,4 @@ -from typing import Final, ClassVar, Any, List, Optional, TYPE_CHECKING +from typing import Final, ClassVar, Any, List, Dict, Optional, TYPE_CHECKING from sqlalchemy.engine import URL from dlt.common.configuration import configspec @@ -10,9 +10,6 @@ from dlt.common.destination.reference import DestinationClientDwhWithStagingConfiguration -SUPPORTED_DRIVERS = ["ODBC Driver 18 for SQL Server", "ODBC Driver 17 for SQL Server"] - - @configspec class MsSqlCredentials(ConnectionStringCredentials): drivername: Final[str] = "mssql" # type: ignore @@ -24,22 +21,27 @@ class MsSqlCredentials(ConnectionStringCredentials): __config_gen_annotations__: ClassVar[List[str]] = ["port", "connect_timeout"] + SUPPORTED_DRIVERS: ClassVar[List[str]] = [ + "ODBC Driver 18 for SQL Server", + "ODBC Driver 17 for SQL Server", + ] + def parse_native_representation(self, native_value: Any) -> None: # TODO: Support ODBC connection string or sqlalchemy URL super().parse_native_representation(native_value) if self.query is not None: self.query = {k.lower(): v for k, v in self.query.items()} # Make case-insensitive. - if "driver" in self.query and self.query.get("driver") not in SUPPORTED_DRIVERS: - raise SystemConfigurationException( - f"""The specified driver "{self.query.get('driver')}" is not supported.""" - f" Choose one of the supported drivers: {', '.join(SUPPORTED_DRIVERS)}." - ) self.driver = self.query.get("driver", self.driver) self.connect_timeout = int(self.query.get("connect_timeout", self.connect_timeout)) if not self.is_partial(): self.resolve() def on_resolved(self) -> None: + if self.driver not in self.SUPPORTED_DRIVERS: + raise SystemConfigurationException( + f"""The specified driver "{self.driver}" is not supported.""" + f" Choose one of the supported drivers: {', '.join(self.SUPPORTED_DRIVERS)}." + ) self.database = self.database.lower() def to_url(self) -> URL: @@ -55,20 +57,21 @@ def on_partial(self) -> None: def _get_driver(self) -> str: if self.driver: return self.driver + # Pick a default driver if available import pyodbc available_drivers = pyodbc.drivers() - for d in SUPPORTED_DRIVERS: + for d in self.SUPPORTED_DRIVERS: if d in available_drivers: return d docs_url = "https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16" raise SystemConfigurationException( f"No supported ODBC driver found for MS SQL Server. See {docs_url} for information on" - f" how to install the '{SUPPORTED_DRIVERS[0]}' on your platform." + f" how to install the '{self.SUPPORTED_DRIVERS[0]}' on your platform." ) - def to_odbc_dsn(self) -> str: + def _get_odbc_dsn_dict(self) -> Dict[str, Any]: params = { "DRIVER": self.driver, "SERVER": f"{self.host},{self.port}", @@ -78,6 +81,10 @@ def to_odbc_dsn(self) -> str: } if self.query is not None: params.update({k.upper(): v for k, v in self.query.items()}) + return params + + def to_odbc_dsn(self) -> str: + params = self._get_odbc_dsn_dict() return ";".join([f"{k}={v}" for k, v in params.items()]) diff --git a/dlt/destinations/impl/mssql/mssql.py b/dlt/destinations/impl/mssql/mssql.py index e97389f185..b6af345e36 100644 --- a/dlt/destinations/impl/mssql/mssql.py +++ b/dlt/destinations/impl/mssql/mssql.py @@ -20,6 +20,8 @@ HINT_TO_MSSQL_ATTR: Dict[TColumnHint, str] = {"unique": "UNIQUE"} +VARCHAR_MAX_N: int = 4000 +VARBINARY_MAX_N: int = 8000 class MsSqlTypeMapper(TypeMapper): diff --git a/dlt/destinations/impl/mssql/sql_client.py b/dlt/destinations/impl/mssql/sql_client.py index 427518feeb..cd1699adea 100644 --- a/dlt/destinations/impl/mssql/sql_client.py +++ b/dlt/destinations/impl/mssql/sql_client.py @@ -106,8 +106,8 @@ def drop_dataset(self) -> None: ) table_names = [row[0] for row in rows] self.drop_tables(*table_names) - - self.execute_sql("DROP SCHEMA IF EXISTS %s;" % self.fully_qualified_dataset_name()) + # Drop schema + self._drop_schema() def _drop_views(self, *tables: str) -> None: if not tables: @@ -115,7 +115,10 @@ def _drop_views(self, *tables: str) -> None: statements = [ f"DROP VIEW IF EXISTS {self.make_qualified_table_name(table)};" for table in tables ] - self.execute_fragments(statements) + self.execute_many(statements) + + def _drop_schema(self) -> None: + self.execute_sql("DROP SCHEMA IF EXISTS %s;" % self.fully_qualified_dataset_name()) def execute_sql( self, sql: AnyStr, *args: Any, **kwargs: Any diff --git a/dlt/destinations/impl/qdrant/qdrant_adapter.py b/dlt/destinations/impl/qdrant/qdrant_adapter.py index 243cbd6c5b..215d87a920 100644 --- a/dlt/destinations/impl/qdrant/qdrant_adapter.py +++ b/dlt/destinations/impl/qdrant/qdrant_adapter.py @@ -2,6 +2,7 @@ from dlt.common.schema.typing import TColumnNames, TTableSchemaColumns from dlt.extract import DltResource, resource as make_resource +from dlt.destinations.utils import ensure_resource VECTORIZE_HINT = "x-qdrant-embed" @@ -31,15 +32,7 @@ def qdrant_adapter( >>> qdrant_adapter(data, embed="description") [DltResource with hints applied] """ - # wrap `data` in a resource if not an instance already - resource: DltResource - if not isinstance(data, DltResource): - resource_name: str = None - if not hasattr(data, "__name__"): - resource_name = "content" - resource = make_resource(data, name=resource_name) - else: - resource = data + resource = ensure_resource(data) column_hints: TTableSchemaColumns = {} diff --git a/dlt/destinations/impl/snowflake/__init__.py b/dlt/destinations/impl/snowflake/__init__.py index d6bebd3fdd..dde4d5a382 100644 --- a/dlt/destinations/impl/snowflake/__init__.py +++ b/dlt/destinations/impl/snowflake/__init__.py @@ -21,4 +21,5 @@ def capabilities() -> DestinationCapabilitiesContext: caps.is_max_text_data_type_length_in_bytes = True caps.supports_ddl_transactions = True caps.alter_add_multi_column = True + caps.supports_clone_table = True return caps diff --git a/dlt/destinations/impl/snowflake/snowflake.py b/dlt/destinations/impl/snowflake/snowflake.py index 67df78c138..fb51ab9d36 100644 --- a/dlt/destinations/impl/snowflake/snowflake.py +++ b/dlt/destinations/impl/snowflake/snowflake.py @@ -27,7 +27,7 @@ from dlt.destinations.impl.snowflake import capabilities from dlt.destinations.impl.snowflake.configuration import SnowflakeClientConfiguration from dlt.destinations.impl.snowflake.sql_client import SnowflakeSqlClient -from dlt.destinations.sql_jobs import SqlStagingCopyJob, SqlJobParams +from dlt.destinations.sql_jobs import SqlJobParams from dlt.destinations.impl.snowflake.sql_client import SnowflakeSqlClient from dlt.destinations.job_impl import NewReferenceJob from dlt.destinations.sql_client import SqlClientBase @@ -175,13 +175,15 @@ def __init__( f'PUT file://{file_path} @{stage_name}/"{load_id}" OVERWRITE = TRUE,' " AUTO_COMPRESS = FALSE" ) - client.execute_sql(f"""COPY INTO {qualified_table_name} + client.execute_sql( + f"""COPY INTO {qualified_table_name} {from_clause} {files_clause} {credentials_clause} FILE_FORMAT = {source_format} MATCH_BY_COLUMN_NAME='CASE_INSENSITIVE' - """) + """ + ) if stage_file_path and not keep_staged_files: client.execute_sql(f"REMOVE {stage_file_path}") @@ -192,25 +194,6 @@ def exception(self) -> str: raise NotImplementedError() -class SnowflakeStagingCopyJob(SqlStagingCopyJob): - @classmethod - def generate_sql( - cls, - table_chain: Sequence[TTableSchema], - sql_client: SqlClientBase[Any], - params: Optional[SqlJobParams] = None, - ) -> List[str]: - sql: List[str] = [] - for table in table_chain: - with sql_client.with_staging_dataset(staging=True): - staging_table_name = sql_client.make_qualified_table_name(table["name"]) - table_name = sql_client.make_qualified_table_name(table["name"]) - sql.append(f"DROP TABLE IF EXISTS {table_name};") - # recreate destination table with data cloned from staging table - sql.append(f"CREATE TABLE {table_name} CLONE {staging_table_name};") - return sql - - class SnowflakeClient(SqlJobClientWithStaging, SupportsStagingDestination): capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() @@ -250,13 +233,6 @@ def _make_add_column_sql( + ",\n".join(self._get_column_def_sql(c, table_format) for c in new_columns) ] - def _create_replace_followup_jobs( - self, table_chain: Sequence[TTableSchema] - ) -> List[NewLoadJob]: - if self.config.replace_strategy == "staging-optimized": - return [SnowflakeStagingCopyJob.from_table_chain(table_chain, self.sql_client)] - return super()._create_replace_followup_jobs(table_chain) - def _get_table_update_sql( self, table_name: str, diff --git a/dlt/destinations/impl/synapse/__init__.py b/dlt/destinations/impl/synapse/__init__.py new file mode 100644 index 0000000000..53dbabc090 --- /dev/null +++ b/dlt/destinations/impl/synapse/__init__.py @@ -0,0 +1,48 @@ +from dlt.common.data_writers.escape import escape_postgres_identifier, escape_mssql_literal +from dlt.common.destination import DestinationCapabilitiesContext +from dlt.common.arithmetics import DEFAULT_NUMERIC_PRECISION, DEFAULT_NUMERIC_SCALE +from dlt.common.wei import EVM_DECIMAL_PRECISION + +from dlt.destinations.impl.synapse.synapse_adapter import synapse_adapter + + +def capabilities() -> DestinationCapabilitiesContext: + caps = DestinationCapabilitiesContext() + + caps.preferred_loader_file_format = "insert_values" + caps.supported_loader_file_formats = ["insert_values"] + caps.preferred_staging_file_format = "parquet" + caps.supported_staging_file_formats = ["parquet"] + + caps.insert_values_writer_type = "select_union" # https://stackoverflow.com/a/77014299 + + caps.escape_identifier = escape_postgres_identifier + caps.escape_literal = escape_mssql_literal + + # Synapse has a max precision of 38 + # https://learn.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse?view=aps-pdw-2016-au7#DataTypes + caps.decimal_precision = (DEFAULT_NUMERIC_PRECISION, DEFAULT_NUMERIC_SCALE) + caps.wei_precision = (DEFAULT_NUMERIC_PRECISION, 0) + + # https://learn.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse?view=aps-pdw-2016-au7#LimitationsRestrictions + caps.max_identifier_length = 128 + caps.max_column_identifier_length = 128 + + # https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-service-capacity-limits#queries + caps.max_query_length = 65536 * 4096 + caps.is_max_query_length_in_bytes = True + + # nvarchar(max) can store 2 GB + # https://learn.microsoft.com/en-us/sql/t-sql/data-types/nchar-and-nvarchar-transact-sql?view=sql-server-ver16#nvarchar---n--max-- + caps.max_text_data_type_length = 2 * 1024 * 1024 * 1024 + caps.is_max_text_data_type_length_in_bytes = True + + # https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-develop-transactions + caps.supports_transactions = True + caps.supports_ddl_transactions = False + + # datetimeoffset can store 7 digits for fractional seconds + # https://learn.microsoft.com/en-us/sql/t-sql/data-types/datetimeoffset-transact-sql?view=sql-server-ver16 + caps.timestamp_precision = 7 + + return caps diff --git a/dlt/destinations/impl/synapse/configuration.py b/dlt/destinations/impl/synapse/configuration.py new file mode 100644 index 0000000000..bb1ba632dc --- /dev/null +++ b/dlt/destinations/impl/synapse/configuration.py @@ -0,0 +1,63 @@ +from typing import Final, Any, List, Dict, Optional, ClassVar + +from dlt.common import logger +from dlt.common.configuration import configspec +from dlt.common.schema.typing import TSchemaTables +from dlt.common.schema.utils import get_write_disposition + +from dlt.destinations.impl.mssql.configuration import ( + MsSqlCredentials, + MsSqlClientConfiguration, +) +from dlt.destinations.impl.mssql.configuration import MsSqlCredentials + +from dlt.destinations.impl.synapse.synapse_adapter import TTableIndexType + + +@configspec +class SynapseCredentials(MsSqlCredentials): + drivername: Final[str] = "synapse" # type: ignore + + # LongAsMax keyword got introduced in ODBC Driver 18 for SQL Server. + SUPPORTED_DRIVERS: ClassVar[List[str]] = ["ODBC Driver 18 for SQL Server"] + + def _get_odbc_dsn_dict(self) -> Dict[str, Any]: + params = super()._get_odbc_dsn_dict() + # Long types (text, ntext, image) are not supported on Synapse. + # Convert to max types using LongAsMax keyword. + # https://stackoverflow.com/a/57926224 + params["LONGASMAX"] = "yes" + return params + + +@configspec +class SynapseClientConfiguration(MsSqlClientConfiguration): + destination_type: Final[str] = "synapse" # type: ignore + credentials: SynapseCredentials + + # While Synapse uses CLUSTERED COLUMNSTORE INDEX tables by default, we use + # HEAP tables (no indexing) by default. HEAP is a more robust choice, because + # columnstore tables do not support varchar(max), nvarchar(max), and varbinary(max). + # https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index + default_table_index_type: Optional[TTableIndexType] = "heap" + """ + Table index type that is used if no table index type is specified on the resource. + This only affects data tables, dlt system tables ignore this setting and + are always created as "heap" tables. + """ + + # Set to False by default because the PRIMARY KEY and UNIQUE constraints + # are tricky in Synapse: they are NOT ENFORCED and can lead to innacurate + # results if the user does not ensure all column values are unique. + # https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints + create_indexes: bool = False + """Whether `primary_key` and `unique` column hints are applied.""" + + staging_use_msi: bool = False + """Whether the managed identity of the Synapse workspace is used to authorize access to the staging Storage Account.""" + + __config_gen_annotations__: ClassVar[List[str]] = [ + "default_table_index_type", + "create_indexes", + "staging_use_msi", + ] diff --git a/dlt/destinations/impl/synapse/factory.py b/dlt/destinations/impl/synapse/factory.py new file mode 100644 index 0000000000..b7eddd6ef7 --- /dev/null +++ b/dlt/destinations/impl/synapse/factory.py @@ -0,0 +1,58 @@ +import typing as t + +from dlt.common.destination import Destination, DestinationCapabilitiesContext + +from dlt.destinations.impl.synapse import capabilities +from dlt.destinations.impl.synapse.configuration import ( + SynapseCredentials, + SynapseClientConfiguration, +) +from dlt.destinations.impl.synapse.synapse_adapter import TTableIndexType + +if t.TYPE_CHECKING: + from dlt.destinations.impl.synapse.synapse import SynapseClient + + +class synapse(Destination[SynapseClientConfiguration, "SynapseClient"]): + spec = SynapseClientConfiguration + + def capabilities(self) -> DestinationCapabilitiesContext: + return capabilities() + + @property + def client_class(self) -> t.Type["SynapseClient"]: + from dlt.destinations.impl.synapse.synapse import SynapseClient + + return SynapseClient + + def __init__( + self, + credentials: t.Union[SynapseCredentials, t.Dict[str, t.Any], str] = None, + default_table_index_type: t.Optional[TTableIndexType] = "heap", + create_indexes: bool = False, + staging_use_msi: bool = False, + destination_name: t.Optional[str] = None, + environment: t.Optional[str] = None, + **kwargs: t.Any, + ) -> None: + """Configure the Synapse destination to use in a pipeline. + + All arguments provided here supersede other configuration sources such as environment variables and dlt config files. + + Args: + credentials: Credentials to connect to the Synapse dedicated pool. Can be an instance of `SynapseCredentials` or + a connection string in the format `synapse://user:password@host:port/database` + default_table_index_type: Maps directly to the default_table_index_type attribute of the SynapseClientConfiguration object. + create_indexes: Maps directly to the create_indexes attribute of the SynapseClientConfiguration object. + staging_use_msi: Maps directly to the staging_use_msi attribute of the SynapseClientConfiguration object. + **kwargs: Additional arguments passed to the destination config + """ + super().__init__( + credentials=credentials, + default_table_index_type=default_table_index_type, + create_indexes=create_indexes, + staging_use_msi=staging_use_msi, + destination_name=destination_name, + environment=environment, + **kwargs, + ) diff --git a/dlt/destinations/impl/synapse/sql_client.py b/dlt/destinations/impl/synapse/sql_client.py new file mode 100644 index 0000000000..089c58e57c --- /dev/null +++ b/dlt/destinations/impl/synapse/sql_client.py @@ -0,0 +1,28 @@ +from typing import ClassVar +from contextlib import suppress + +from dlt.common.destination import DestinationCapabilitiesContext + +from dlt.destinations.impl.mssql.sql_client import PyOdbcMsSqlClient +from dlt.destinations.impl.mssql.configuration import MsSqlCredentials +from dlt.destinations.impl.synapse import capabilities +from dlt.destinations.impl.synapse.configuration import SynapseCredentials + +from dlt.destinations.exceptions import DatabaseUndefinedRelation + + +class SynapseSqlClient(PyOdbcMsSqlClient): + capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() + + def drop_tables(self, *tables: str) -> None: + if not tables: + return + # Synapse does not support DROP TABLE IF EXISTS. + # Workaround: use DROP TABLE and suppress non-existence errors. + statements = [f"DROP TABLE {self.make_qualified_table_name(table)};" for table in tables] + with suppress(DatabaseUndefinedRelation): + self.execute_fragments(statements) + + def _drop_schema(self) -> None: + # Synapse does not support DROP SCHEMA IF EXISTS. + self.execute_sql("DROP SCHEMA %s;" % self.fully_qualified_dataset_name()) diff --git a/dlt/destinations/impl/synapse/synapse.py b/dlt/destinations/impl/synapse/synapse.py new file mode 100644 index 0000000000..33e6194602 --- /dev/null +++ b/dlt/destinations/impl/synapse/synapse.py @@ -0,0 +1,297 @@ +import os +from typing import ClassVar, Sequence, List, Dict, Any, Optional, cast +from copy import deepcopy +from textwrap import dedent +from urllib.parse import urlparse, urlunparse + +from dlt import current + +from dlt.common.destination import DestinationCapabilitiesContext +from dlt.common.destination.reference import ( + SupportsStagingDestination, + NewLoadJob, + CredentialsConfiguration, +) + +from dlt.common.schema import TTableSchema, TColumnSchema, Schema, TColumnHint +from dlt.common.schema.utils import table_schema_has_type, get_inherited_table_hint +from dlt.common.schema.typing import TTableSchemaColumns + +from dlt.common.configuration.specs import AzureCredentialsWithoutDefaults + +from dlt.destinations.job_impl import NewReferenceJob +from dlt.destinations.sql_jobs import SqlStagingCopyJob, SqlJobParams +from dlt.destinations.sql_client import SqlClientBase +from dlt.destinations.insert_job_client import InsertValuesJobClient +from dlt.destinations.job_client_impl import SqlJobClientBase, LoadJob, CopyRemoteFileLoadJob +from dlt.destinations.exceptions import LoadJobTerminalException + +from dlt.destinations.impl.mssql.mssql import ( + MsSqlTypeMapper, + MsSqlClient, + VARCHAR_MAX_N, + VARBINARY_MAX_N, +) + +from dlt.destinations.impl.synapse import capabilities +from dlt.destinations.impl.synapse.sql_client import SynapseSqlClient +from dlt.destinations.impl.synapse.configuration import SynapseClientConfiguration +from dlt.destinations.impl.synapse.synapse_adapter import ( + TABLE_INDEX_TYPE_HINT, + TTableIndexType, +) + + +HINT_TO_SYNAPSE_ATTR: Dict[TColumnHint, str] = { + "primary_key": "PRIMARY KEY NONCLUSTERED NOT ENFORCED", + "unique": "UNIQUE NOT ENFORCED", +} +TABLE_INDEX_TYPE_TO_SYNAPSE_ATTR: Dict[TTableIndexType, str] = { + "heap": "HEAP", + "clustered_columnstore_index": "CLUSTERED COLUMNSTORE INDEX", +} + + +class SynapseClient(MsSqlClient, SupportsStagingDestination): + capabilities: ClassVar[DestinationCapabilitiesContext] = capabilities() + + def __init__(self, schema: Schema, config: SynapseClientConfiguration) -> None: + super().__init__(schema, config) + self.config: SynapseClientConfiguration = config + self.sql_client = SynapseSqlClient( + config.normalize_dataset_name(schema), config.credentials + ) + + self.active_hints = deepcopy(HINT_TO_SYNAPSE_ATTR) + if not self.config.create_indexes: + self.active_hints.pop("primary_key", None) + self.active_hints.pop("unique", None) + + def _get_table_update_sql( + self, table_name: str, new_columns: Sequence[TColumnSchema], generate_alter: bool + ) -> List[str]: + table = self.get_load_table(table_name, staging=self.in_staging_mode) + if table is None: + table_index_type = self.config.default_table_index_type + else: + table_index_type = cast(TTableIndexType, table.get(TABLE_INDEX_TYPE_HINT)) + if self.in_staging_mode: + final_table = self.get_load_table(table_name, staging=False) + final_table_index_type = cast( + TTableIndexType, final_table.get(TABLE_INDEX_TYPE_HINT) + ) + else: + final_table_index_type = table_index_type + if final_table_index_type == "clustered_columnstore_index": + # Even if the staging table has index type "heap", we still adjust + # the column data types to prevent errors when writing into the + # final table that has index type "clustered_columnstore_index". + new_columns = self._get_columstore_valid_columns(new_columns) + + _sql_result = SqlJobClientBase._get_table_update_sql( + self, table_name, new_columns, generate_alter + ) + if not generate_alter: + table_index_type_attr = TABLE_INDEX_TYPE_TO_SYNAPSE_ATTR[table_index_type] + sql_result = [_sql_result[0] + f"\n WITH ( {table_index_type_attr} );"] + else: + sql_result = _sql_result + return sql_result + + def _get_columstore_valid_columns( + self, columns: Sequence[TColumnSchema] + ) -> Sequence[TColumnSchema]: + return [self._get_columstore_valid_column(c) for c in columns] + + def _get_columstore_valid_column(self, c: TColumnSchema) -> TColumnSchema: + """ + Returns TColumnSchema that maps to a Synapse data type that can participate in a columnstore index. + + varchar(max), nvarchar(max), and varbinary(max) are replaced with + varchar(n), nvarchar(n), and varbinary(n), respectively, where + n equals the user-specified precision, or the maximum allowed + value if the user did not specify a precision. + """ + varchar_source_types = [ + sct + for sct, dbt in MsSqlTypeMapper.sct_to_unbound_dbt.items() + if dbt in ("varchar(max)", "nvarchar(max)") + ] + varbinary_source_types = [ + sct + for sct, dbt in MsSqlTypeMapper.sct_to_unbound_dbt.items() + if dbt == "varbinary(max)" + ] + if c["data_type"] in varchar_source_types and "precision" not in c: + return {**c, **{"precision": VARCHAR_MAX_N}} + elif c["data_type"] in varbinary_source_types and "precision" not in c: + return {**c, **{"precision": VARBINARY_MAX_N}} + return c + + def _create_replace_followup_jobs( + self, table_chain: Sequence[TTableSchema] + ) -> List[NewLoadJob]: + if self.config.replace_strategy == "staging-optimized": + return [SynapseStagingCopyJob.from_table_chain(table_chain, self.sql_client)] + return super()._create_replace_followup_jobs(table_chain) + + def get_load_table(self, table_name: str, staging: bool = False) -> TTableSchema: + table = super().get_load_table(table_name, staging) + if table is None: + return None + if staging and self.config.replace_strategy == "insert-from-staging": + # Staging tables should always be heap tables, because "when you are + # temporarily landing data in dedicated SQL pool, you may find that + # using a heap table makes the overall process faster." + # "staging-optimized" is not included, because in that strategy the + # staging table becomes the final table, so we should already create + # it with the desired index type. + table[TABLE_INDEX_TYPE_HINT] = "heap" # type: ignore[typeddict-unknown-key] + elif table_name in self.schema.dlt_table_names(): + # dlt tables should always be heap tables, because "for small lookup + # tables, less than 60 million rows, consider using HEAP or clustered + # index for faster query performance." + table[TABLE_INDEX_TYPE_HINT] = "heap" # type: ignore[typeddict-unknown-key] + # https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#heap-tables + elif table_name in self.schema.data_table_names(): + if TABLE_INDEX_TYPE_HINT not in table: + # If present in parent table, fetch hint from there. + table[TABLE_INDEX_TYPE_HINT] = get_inherited_table_hint( # type: ignore[typeddict-unknown-key] + self.schema.tables, table_name, TABLE_INDEX_TYPE_HINT, allow_none=True + ) + if table[TABLE_INDEX_TYPE_HINT] is None: # type: ignore[typeddict-item] + # Hint still not defined, fall back to default. + table[TABLE_INDEX_TYPE_HINT] = self.config.default_table_index_type # type: ignore[typeddict-unknown-key] + return table + + def start_file_load(self, table: TTableSchema, file_path: str, load_id: str) -> LoadJob: + job = super().start_file_load(table, file_path, load_id) + if not job: + assert NewReferenceJob.is_reference_job( + file_path + ), "Synapse must use staging to load files" + job = SynapseCopyFileLoadJob( + table, + file_path, + self.sql_client, + cast(AzureCredentialsWithoutDefaults, self.config.staging_config.credentials), + self.config.staging_use_msi, + ) + return job + + +class SynapseStagingCopyJob(SqlStagingCopyJob): + @classmethod + def generate_sql( + cls, + table_chain: Sequence[TTableSchema], + sql_client: SqlClientBase[Any], + params: Optional[SqlJobParams] = None, + ) -> List[str]: + sql: List[str] = [] + for table in table_chain: + with sql_client.with_staging_dataset(staging=True): + staging_table_name = sql_client.make_qualified_table_name(table["name"]) + table_name = sql_client.make_qualified_table_name(table["name"]) + # drop destination table + sql.append(f"DROP TABLE {table_name};") + # moving staging table to destination schema + sql.append( + f"ALTER SCHEMA {sql_client.fully_qualified_dataset_name()} TRANSFER" + f" {staging_table_name};" + ) + # recreate staging table + job_client = current.pipeline().destination_client() # type: ignore[operator] + with job_client.with_staging_dataset(): + # get table columns from schema + columns = [c for c in job_client.schema.get_table_columns(table["name"]).values()] + # generate CREATE TABLE statement + create_table_stmt = job_client._get_table_update_sql( + table["name"], columns, generate_alter=False + ) + sql.extend(create_table_stmt) + + return sql + + +class SynapseCopyFileLoadJob(CopyRemoteFileLoadJob): + def __init__( + self, + table: TTableSchema, + file_path: str, + sql_client: SqlClientBase[Any], + staging_credentials: Optional[AzureCredentialsWithoutDefaults] = None, + staging_use_msi: bool = False, + ) -> None: + self.staging_use_msi = staging_use_msi + super().__init__(table, file_path, sql_client, staging_credentials) + + def execute(self, table: TTableSchema, bucket_path: str) -> None: + # get format + ext = os.path.splitext(bucket_path)[1][1:] + if ext == "parquet": + if table_schema_has_type(table, "time"): + # Synapse interprets Parquet TIME columns as bigint, resulting in + # an incompatibility error. + raise LoadJobTerminalException( + self.file_name(), + "Synapse cannot load TIME columns from Parquet files. Switch to direct INSERT" + " file format or convert `datetime.time` objects in your data to `str` or" + " `datetime.datetime`", + ) + file_type = "PARQUET" + + # dlt-generated DDL statements will still create the table, but + # enabling AUTO_CREATE_TABLE prevents a MalformedInputException. + auto_create_table = "ON" + else: + raise ValueError(f"Unsupported file type {ext} for Synapse.") + + staging_credentials = self._staging_credentials + assert staging_credentials is not None + assert isinstance(staging_credentials, AzureCredentialsWithoutDefaults) + azure_storage_account_name = staging_credentials.azure_storage_account_name + https_path = self._get_https_path(bucket_path, azure_storage_account_name) + table_name = table["name"] + + if self.staging_use_msi: + credential = "IDENTITY = 'Managed Identity'" + else: + sas_token = staging_credentials.azure_storage_sas_token + credential = f"IDENTITY = 'Shared Access Signature', SECRET = '{sas_token}'" + + # Copy data from staging file into Synapse table. + with self._sql_client.begin_transaction(): + dataset_name = self._sql_client.dataset_name + sql = dedent(f""" + COPY INTO [{dataset_name}].[{table_name}] + FROM '{https_path}' + WITH ( + FILE_TYPE = '{file_type}', + CREDENTIAL = ({credential}), + AUTO_CREATE_TABLE = '{auto_create_table}' + ) + """) + self._sql_client.execute_sql(sql) + + def exception(self) -> str: + # this part of code should be never reached + raise NotImplementedError() + + def _get_https_path(self, bucket_path: str, storage_account_name: str) -> str: + """ + Converts a path in the form of az:/// to + https://.blob.core.windows.net// + as required by Synapse. + """ + bucket_url = urlparse(bucket_path) + # "blob" endpoint has better performance than "dfs" endoint + # https://learn.microsoft.com/en-us/sql/t-sql/statements/copy-into-transact-sql?view=azure-sqldw-latest#external-locations + endpoint = "blob" + _path = "/" + bucket_url.netloc + bucket_url.path + https_url = bucket_url._replace( + scheme="https", + netloc=f"{storage_account_name}.{endpoint}.core.windows.net", + path=_path, + ) + return urlunparse(https_url) diff --git a/dlt/destinations/impl/synapse/synapse_adapter.py b/dlt/destinations/impl/synapse/synapse_adapter.py new file mode 100644 index 0000000000..24932736f9 --- /dev/null +++ b/dlt/destinations/impl/synapse/synapse_adapter.py @@ -0,0 +1,52 @@ +from typing import Any, Literal, Set, get_args, Final, Dict + +from dlt.extract import DltResource, resource as make_resource +from dlt.extract.typing import TTableHintTemplate +from dlt.extract.hints import TResourceHints +from dlt.destinations.utils import ensure_resource + +TTableIndexType = Literal["heap", "clustered_columnstore_index"] +""" +Table [index type](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index) used when creating the Synapse table. +This regards indexes specified at the table level, not the column level. +""" +TABLE_INDEX_TYPES: Set[TTableIndexType] = set(get_args(TTableIndexType)) + +TABLE_INDEX_TYPE_HINT: Literal["x-table-index-type"] = "x-table-index-type" + + +def synapse_adapter(data: Any, table_index_type: TTableIndexType = None) -> DltResource: + """Prepares data for the Synapse destination by specifying which table index + type should be used. + + Args: + data (Any): The data to be transformed. It can be raw data or an instance + of DltResource. If raw data, the function wraps it into a DltResource + object. + table_index_type (TTableIndexType, optional): The table index type used when creating + the Synapse table. + + Returns: + DltResource: A resource with applied Synapse-specific hints. + + Raises: + ValueError: If input for `table_index_type` is invalid. + + Examples: + >>> data = [{"name": "Anush", "description": "Integrations Hacker"}] + >>> synapse_adapter(data, table_index_type="clustered_columnstore_index") + [DltResource with hints applied] + """ + resource = ensure_resource(data) + + additional_table_hints: Dict[str, TTableHintTemplate[Any]] = {} + if table_index_type is not None: + if table_index_type not in TABLE_INDEX_TYPES: + allowed_types = ", ".join(TABLE_INDEX_TYPES) + raise ValueError( + f"Table index type {table_index_type} is invalid. Allowed table index" + f" types are: {allowed_types}." + ) + additional_table_hints[TABLE_INDEX_TYPE_HINT] = table_index_type + resource.apply_hints(additional_table_hints=additional_table_hints) + return resource diff --git a/dlt/destinations/impl/weaviate/weaviate_adapter.py b/dlt/destinations/impl/weaviate/weaviate_adapter.py index 2d5161d9e9..a290ac65b4 100644 --- a/dlt/destinations/impl/weaviate/weaviate_adapter.py +++ b/dlt/destinations/impl/weaviate/weaviate_adapter.py @@ -2,6 +2,7 @@ from dlt.common.schema.typing import TColumnNames, TTableSchemaColumns from dlt.extract import DltResource, resource as make_resource +from dlt.destinations.utils import ensure_resource TTokenizationTMethod = Literal["word", "lowercase", "whitespace", "field"] TOKENIZATION_METHODS: Set[TTokenizationTMethod] = set(get_args(TTokenizationTMethod)) @@ -53,15 +54,7 @@ def weaviate_adapter( >>> weaviate_adapter(data, vectorize="description", tokenization={"description": "word"}) [DltResource with hints applied] """ - # wrap `data` in a resource if not an instance already - resource: DltResource - if not isinstance(data, DltResource): - resource_name: str = None - if not hasattr(data, "__name__"): - resource_name = "content" - resource = make_resource(data, name=resource_name) - else: - resource = data + resource = ensure_resource(data) column_hints: TTableSchemaColumns = {} if vectorize: diff --git a/dlt/destinations/insert_job_client.py b/dlt/destinations/insert_job_client.py index 678ba43bcc..776176078e 100644 --- a/dlt/destinations/insert_job_client.py +++ b/dlt/destinations/insert_job_client.py @@ -36,9 +36,10 @@ def _insert(self, qualified_table_name: str, file_path: str) -> Iterator[List[st # the procedure below will split the inserts into max_query_length // 2 packs with FileStorage.open_zipsafe_ro(file_path, "r", encoding="utf-8") as f: header = f.readline() - values_mark = f.readline() - # properly formatted file has a values marker at the beginning - assert values_mark == "VALUES\n" + if self._sql_client.capabilities.insert_values_writer_type == "default": + # properly formatted file has a values marker at the beginning + values_mark = f.readline() + assert values_mark == "VALUES\n" max_rows = self._sql_client.capabilities.max_rows_per_insert @@ -67,7 +68,9 @@ def _insert(self, qualified_table_name: str, file_path: str) -> Iterator[List[st # Chunk by max_rows - 1 for simplicity because one more row may be added for chunk in chunks(values_rows, max_rows - 1): processed += len(chunk) - insert_sql.extend([header.format(qualified_table_name), values_mark]) + insert_sql.append(header.format(qualified_table_name)) + if self._sql_client.capabilities.insert_values_writer_type == "default": + insert_sql.append(values_mark) if processed == len_rows: # On the last chunk we need to add the extra row read insert_sql.append("".join(chunk) + until_nl) @@ -76,7 +79,12 @@ def _insert(self, qualified_table_name: str, file_path: str) -> Iterator[List[st insert_sql.append("".join(chunk).strip()[:-1] + ";\n") else: # otherwise write all content in a single INSERT INTO - insert_sql.extend([header.format(qualified_table_name), values_mark, content]) + if self._sql_client.capabilities.insert_values_writer_type == "default": + insert_sql.extend( + [header.format(qualified_table_name), values_mark, content] + ) + elif self._sql_client.capabilities.insert_values_writer_type == "select_union": + insert_sql.extend([header.format(qualified_table_name), content]) if until_nl: insert_sql.append(until_nl) diff --git a/dlt/destinations/job_client_impl.py b/dlt/destinations/job_client_impl.py index ac68cfea8a..e7dc4bcbe2 100644 --- a/dlt/destinations/job_client_impl.py +++ b/dlt/destinations/job_client_impl.py @@ -50,7 +50,6 @@ FollowupJob, CredentialsConfiguration, ) -from dlt.common.utils import concat_strings_with_limit from dlt.destinations.exceptions import ( DatabaseUndefinedRelation, DestinationSchemaTampered, @@ -76,15 +75,19 @@ def __init__(self, file_path: str, sql_client: SqlClientBase[Any]) -> None: with FileStorage.open_zipsafe_ro(file_path, "r", encoding="utf-8") as f: sql = f.read() + # Some clients (e.g. databricks) do not support multiple statements in one execute call + if not sql_client.capabilities.supports_multiple_statements: + sql_client.execute_many(self._split_fragments(sql)) # if we detect ddl transactions, only execute transaction if supported by client - if ( + elif ( not self._string_containts_ddl_queries(sql) or sql_client.capabilities.supports_ddl_transactions ): # with sql_client.begin_transaction(): sql_client.execute_sql(sql) else: - sql_client.execute_sql(sql) + # sql_client.execute_sql(sql) + sql_client.execute_many(self._split_fragments(sql)) def state(self) -> TLoadJobState: # this job is always done @@ -100,6 +103,9 @@ def _string_containts_ddl_queries(self, sql: str) -> bool: return True return False + def _split_fragments(self, sql: str) -> List[str]: + return [s + (";" if not s.endswith(";") else "") for s in sql.split(";") if s.strip()] + @staticmethod def is_sql_job(file_path: str) -> bool: return os.path.splitext(file_path)[1][1:] == "sql" @@ -295,6 +301,15 @@ def __exit__( ) -> None: self.sql_client.close_connection() + def _get_storage_table_query_columns(self) -> List[str]: + """Column names used when querying table from information schema. + Override for databases that use different namings. + """ + fields = ["column_name", "data_type", "is_nullable"] + if self.capabilities.schema_supports_numeric_precision: + fields += ["numeric_precision", "numeric_scale"] + return fields + def get_storage_table(self, table_name: str) -> Tuple[bool, TTableSchemaColumns]: def _null_to_bool(v: str) -> bool: if v == "NO": @@ -303,9 +318,7 @@ def _null_to_bool(v: str) -> bool: return True raise ValueError(v) - fields = ["column_name", "data_type", "is_nullable"] - if self.capabilities.schema_supports_numeric_precision: - fields += ["numeric_precision", "numeric_scale"] + fields = self._get_storage_table_query_columns() db_params = self.sql_client.make_qualified_table_name(table_name, escape=False).split( ".", 3 ) @@ -383,10 +396,7 @@ def _execute_schema_update_sql(self, only_tables: Iterable[str]) -> TSchemaTable sql_scripts, schema_update = self._build_schema_update_sql(only_tables) # stay within max query size when doing DDL. some db backends use bytes not characters so decrease limit by half # assuming that most of the characters in DDL encode into single bytes - for sql_fragment in concat_strings_with_limit( - sql_scripts, "\n", self.capabilities.max_query_length // 2 - ): - self.sql_client.execute_sql(sql_fragment) + self.sql_client.execute_many(sql_scripts) self._update_schema_in_storage(self.schema) return schema_update diff --git a/dlt/destinations/sql_client.py b/dlt/destinations/sql_client.py index 1e5f7031a5..695f1a0972 100644 --- a/dlt/destinations/sql_client.py +++ b/dlt/destinations/sql_client.py @@ -19,8 +19,13 @@ from dlt.common.typing import TFun from dlt.common.destination import DestinationCapabilitiesContext +from dlt.common.utils import concat_strings_with_limit -from dlt.destinations.exceptions import DestinationConnectionError, LoadClientNotConnected +from dlt.destinations.exceptions import ( + DestinationConnectionError, + LoadClientNotConnected, + DatabaseTerminalException, +) from dlt.destinations.typing import DBApi, TNativeConn, DBApiCursor, DataFrame, DBTransaction @@ -86,7 +91,7 @@ def drop_dataset(self) -> None: def truncate_tables(self, *tables: str) -> None: statements = [self._truncate_table_sql(self.make_qualified_table_name(t)) for t in tables] - self.execute_fragments(statements) + self.execute_many(statements) def drop_tables(self, *tables: str) -> None: if not tables: @@ -94,7 +99,7 @@ def drop_tables(self, *tables: str) -> None: statements = [ f"DROP TABLE IF EXISTS {self.make_qualified_table_name(table)};" for table in tables ] - self.execute_fragments(statements) + self.execute_many(statements) @abstractmethod def execute_sql( @@ -114,6 +119,25 @@ def execute_fragments( """Executes several SQL fragments as efficiently as possible to prevent data copying. Default implementation just joins the strings and executes them together.""" return self.execute_sql("".join(fragments), *args, **kwargs) # type: ignore + def execute_many( + self, statements: Sequence[str], *args: Any, **kwargs: Any + ) -> Optional[Sequence[Sequence[Any]]]: + """Executes multiple SQL statements as efficiently as possible. When client supports multiple statements in a single query + they are executed together in as few database calls as possible. + """ + ret = [] + if self.capabilities.supports_multiple_statements: + for sql_fragment in concat_strings_with_limit( + list(statements), "\n", self.capabilities.max_query_length // 2 + ): + ret.append(self.execute_sql(sql_fragment, *args, **kwargs)) + else: + for statement in statements: + result = self.execute_sql(statement, *args, **kwargs) + if result is not None: + ret.append(result) + return ret + @abstractmethod def fully_qualified_dataset_name(self, escape: bool = True) -> str: pass diff --git a/dlt/destinations/sql_jobs.py b/dlt/destinations/sql_jobs.py index d97a098669..d0911d0bea 100644 --- a/dlt/destinations/sql_jobs.py +++ b/dlt/destinations/sql_jobs.py @@ -74,11 +74,28 @@ class SqlStagingCopyJob(SqlBaseJob): failed_text: str = "Tried to generate a staging copy sql job for the following tables:" @classmethod - def generate_sql( + def _generate_clone_sql( cls, table_chain: Sequence[TTableSchema], sql_client: SqlClientBase[Any], - params: Optional[SqlJobParams] = None, + ) -> List[str]: + """Drop and clone the table for supported destinations""" + sql: List[str] = [] + for table in table_chain: + with sql_client.with_staging_dataset(staging=True): + staging_table_name = sql_client.make_qualified_table_name(table["name"]) + table_name = sql_client.make_qualified_table_name(table["name"]) + sql.append(f"DROP TABLE IF EXISTS {table_name};") + # recreate destination table with data cloned from staging table + sql.append(f"CREATE TABLE {table_name} CLONE {staging_table_name};") + return sql + + @classmethod + def _generate_insert_sql( + cls, + table_chain: Sequence[TTableSchema], + sql_client: SqlClientBase[Any], + params: SqlJobParams = None, ) -> List[str]: sql: List[str] = [] for table in table_chain: @@ -98,6 +115,17 @@ def generate_sql( ) return sql + @classmethod + def generate_sql( + cls, + table_chain: Sequence[TTableSchema], + sql_client: SqlClientBase[Any], + params: SqlJobParams = None, + ) -> List[str]: + if params["replace"] and sql_client.capabilities.supports_clone_table: + return cls._generate_clone_sql(table_chain, sql_client) + return cls._generate_insert_sql(table_chain, sql_client, params) + class SqlMergeJob(SqlBaseJob): """Generates a list of sql statements that merge the data from staging dataset into destination dataset.""" @@ -186,6 +214,21 @@ def gen_insert_temp_table_sql( """ return [cls._to_temp_table(select_statement, temp_table_name)], temp_table_name + @classmethod + def gen_delete_from_sql( + cls, + table_name: str, + unique_column: str, + delete_temp_table_name: str, + temp_table_column: str, + ) -> str: + """Generate DELETE FROM statement deleting the records found in the deletes temp table.""" + return f"""DELETE FROM {table_name} + WHERE {unique_column} IN ( + SELECT * FROM {delete_temp_table_name} + ); + """ + @classmethod def _new_temp_table_name(cls, name_prefix: str) -> str: return f"{name_prefix}_{uniq_id()}" @@ -261,12 +304,9 @@ def gen_merge_sql( unique_column, key_table_clauses ) sql.extend(create_delete_temp_table_sql) - # delete top table - sql.append( - f"DELETE FROM {root_table_name} WHERE {unique_column} IN (SELECT * FROM" - f" {delete_temp_table_name});" - ) - # delete other tables + + # delete from child tables first. This is important for databricks which does not support temporary tables, + # but uses temporary views instead for table in table_chain[1:]: table_name = sql_client.make_qualified_table_name(table["name"]) root_key_columns = get_columns_names_with_prop(table, "root_key") @@ -281,15 +321,25 @@ def gen_merge_sql( ) root_key_column = sql_client.capabilities.escape_identifier(root_key_columns[0]) sql.append( - f"DELETE FROM {table_name} WHERE {root_key_column} IN (SELECT * FROM" - f" {delete_temp_table_name});" + cls.gen_delete_from_sql( + table_name, root_key_column, delete_temp_table_name, unique_column + ) + ) + + # delete from top table now that child tables have been prcessed + sql.append( + cls.gen_delete_from_sql( + root_table_name, unique_column, delete_temp_table_name, unique_column ) + ) + # create temp table used to deduplicate, only when we have primary keys if primary_keys: - create_insert_temp_table_sql, insert_temp_table_name = ( - cls.gen_insert_temp_table_sql( - staging_root_table_name, primary_keys, unique_column - ) + ( + create_insert_temp_table_sql, + insert_temp_table_name, + ) = cls.gen_insert_temp_table_sql( + staging_root_table_name, primary_keys, unique_column ) sql.extend(create_insert_temp_table_sql) diff --git a/dlt/destinations/utils.py b/dlt/destinations/utils.py new file mode 100644 index 0000000000..d4b945a840 --- /dev/null +++ b/dlt/destinations/utils.py @@ -0,0 +1,16 @@ +from typing import Any + +from dlt.extract import DltResource, resource as make_resource + + +def ensure_resource(data: Any) -> DltResource: + """Wraps `data` in a DltResource if it's not a DltResource already.""" + resource: DltResource + if not isinstance(data, DltResource): + resource_name: str = None + if not hasattr(data, "__name__"): + resource_name = "content" + resource = make_resource(data, name=resource_name) + else: + resource = data + return resource diff --git a/dlt/extract/hints.py b/dlt/extract/hints.py index 437dbbc6bd..c1a39041d8 100644 --- a/dlt/extract/hints.py +++ b/dlt/extract/hints.py @@ -1,5 +1,5 @@ from copy import copy, deepcopy -from typing import List, TypedDict, cast, Any +from typing import List, TypedDict, cast, Any, Optional, Dict from dlt.common.schema.utils import DEFAULT_WRITE_DISPOSITION, merge_columns, new_column, new_table from dlt.common.schema.typing import ( @@ -125,6 +125,7 @@ def apply_hints( merge_key: TTableHintTemplate[TColumnNames] = None, incremental: Incremental[Any] = None, schema_contract: TTableHintTemplate[TSchemaContract] = None, + additional_table_hints: Optional[Dict[str, TTableHintTemplate[Any]]] = None, ) -> None: """Creates or modifies existing table schema by setting provided hints. Accepts both static and dynamic hints based on data. @@ -208,6 +209,14 @@ def apply_hints( t["incremental"] = None else: t["incremental"] = incremental + if additional_table_hints is not None: + # loop through provided hints and add, overwrite, or remove them + for k, v in additional_table_hints.items(): + if v is not None: + t[k] = v # type: ignore[literal-required] + else: + t.pop(k, None) # type: ignore[misc] + self.set_hints(t) def set_hints(self, hints_template: TResourceHints) -> None: diff --git a/dlt/helpers/dbt/profiles.yml b/dlt/helpers/dbt/profiles.yml index 2414222cbd..8f2ad22585 100644 --- a/dlt/helpers/dbt/profiles.yml +++ b/dlt/helpers/dbt/profiles.yml @@ -141,4 +141,33 @@ athena: schema: "{{ var('destination_dataset_name', var('source_dataset_name')) }}" database: "{{ env_var('DLT__AWS_DATA_CATALOG') }}" # aws_profile_name: "{{ env_var('DLT__CREDENTIALS__PROFILE_NAME', '') }}" - work_group: "{{ env_var('DLT__ATHENA_WORK_GROUP', '') }}" \ No newline at end of file + work_group: "{{ env_var('DLT__ATHENA_WORK_GROUP', '') }}" + + +# commented out because dbt for Synapse isn't currently properly supported. +# Leave config here for potential future use. +# synapse: +# target: analytics +# outputs: +# analytics: +# type: synapse +# driver: "{{ env_var('DLT__CREDENTIALS__DRIVER') }}" +# server: "{{ env_var('DLT__CREDENTIALS__HOST') }}" +# port: "{{ env_var('DLT__CREDENTIALS__PORT') | as_number }}" +# database: "{{ env_var('DLT__CREDENTIALS__DATABASE') }}" +# schema: "{{ var('destination_dataset_name', var('source_dataset_name')) }}" +# user: "{{ env_var('DLT__CREDENTIALS__USERNAME') }}" +# password: "{{ env_var('DLT__CREDENTIALS__PASSWORD') }}" + + +databricks: + target: analytics + outputs: + analytics: + type: databricks + catalog: "{{ env_var('DLT__CREDENTIALS__CATALOG') }}" + schema: "{{ var('destination_dataset_name', var('source_dataset_name')) }}" + host: "{{ env_var('DLT__CREDENTIALS__SERVER_HOSTNAME') }}" + http_path: "{{ env_var('DLT__CREDENTIALS__HTTP_PATH') }}" + token: "{{ env_var('DLT__CREDENTIALS__ACCESS_TOKEN') }}" + threads: 4 diff --git a/dlt/pipeline/pipeline.py b/dlt/pipeline/pipeline.py index 73c8f076d1..3fa8da6aee 100644 --- a/dlt/pipeline/pipeline.py +++ b/dlt/pipeline/pipeline.py @@ -1163,9 +1163,9 @@ def _set_context(self, is_active: bool) -> None: # set destination context on activation if self.destination: # inject capabilities context - self._container[DestinationCapabilitiesContext] = ( - self._get_destination_capabilities() - ) + self._container[ + DestinationCapabilitiesContext + ] = self._get_destination_capabilities() else: # remove destination context on deactivation if DestinationCapabilitiesContext in self._container: diff --git a/docs/website/docs/dlt-ecosystem/destinations/databricks.md b/docs/website/docs/dlt-ecosystem/destinations/databricks.md new file mode 100644 index 0000000000..679988f918 --- /dev/null +++ b/docs/website/docs/dlt-ecosystem/destinations/databricks.md @@ -0,0 +1,110 @@ +--- + +title: Databricks +description: Databricks `dlt` destination +keywords: [Databricks, destination, data warehouse] + +--- + +# Databricks + +## Install dlt with Databricks +**To install the DLT library with Databricks dependencies:** +``` +pip install dlt[databricks] +``` + +## Setup Guide + +**1. Initialize a project with a pipeline that loads to Databricks by running** +``` +dlt init chess databricks +``` + +**2. Install the necessary dependencies for Databricks by running** +``` +pip install -r requirements.txt +``` +This will install dlt with **databricks** extra which contains Databricks Python dbapi client. + +**4. Enter your credentials into `.dlt/secrets.toml`.** + +This should have your connection parameters and your personal access token. + +It should now look like: + +```toml +[destination.databricks.credentials] +server_hostname = "MY_DATABRICKS.azuredatabricks.net" +http_path = "/sql/1.0/warehouses/12345" +access_token "MY_ACCESS_TOKEN" +catalog = "my_catalog" +``` + +## Write disposition +All write dispositions are supported + +## Data loading +Data is loaded using `INSERT VALUES` statements by default. + +Efficient loading from a staging filesystem is also supported by configuring an Amazon S3 or Azure Blob Storage bucket as a staging destination. When staging is enabled `dlt` will upload data in `parquet` files to the bucket and then use `COPY INTO` statements to ingest the data into Databricks. +For more information on staging, see the [staging support](#staging-support) section below. + +## Supported file formats +* [insert-values](../file-formats/insert-format.md) is used by default +* [jsonl](../file-formats/jsonl.md) supported when staging is enabled (see limitations below) +* [parquet](../file-formats/parquet.md) supported when staging is enabled + +The `jsonl` format has some limitations when used with Databricks: + +1. Compression must be disabled to load jsonl files in databricks. Set `data_writer.disable_compression` to `true` in dlt config when using this format. +2. The following data types are not supported when using `jsonl` format with `databricks`: `decimal`, `complex`, `date`, `binary`. Use `parquet` if your data contains these types. +3. `bigint` data type with precision is not supported with `jsonl` format + + +## Staging support + +Databricks supports both Amazon S3 and Azure Blob Storage as staging locations. `dlt` will upload files in `parquet` format to the staging location and will instruct Databricks to load data from there. + +### Databricks and Amazon S3 + +Please refer to the [S3 documentation](./filesystem.md#aws-s3) for details on connecting your s3 bucket with the bucket_url and credentials. + +Example to set up Databricks with s3 as a staging destination: + +```python +import dlt + +# Create a dlt pipeline that will load +# chess player data to the Databricks destination +# via staging on s3 +pipeline = dlt.pipeline( + pipeline_name='chess_pipeline', + destination='databricks', + staging=dlt.destinations.filesystem('s3://your-bucket-name'), # add this to activate the staging location + dataset_name='player_data', +) +``` + +### Databricks and Azure Blob Storage + +Refer to the [Azure Blob Storage filesystem documentation](./filesystem.md#azure-blob-storage) for details on connecting your Azure Blob Storage container with the bucket_url and credentials. + +Example to set up Databricks with Azure as a staging destination: + +```python +# Create a dlt pipeline that will load +# chess player data to the Databricks destination +# via staging on Azure Blob Storage +pipeline = dlt.pipeline( + pipeline_name='chess_pipeline', + destination='databricks', + staging=dlt.destinations.filesystem('az://your-container-name'), # add this to activate the staging location + dataset_name='player_data' +) +``` +### dbt support +This destination [integrates with dbt](../transformations/dbt/dbt.md) via [dbt-databricks](https://github.com/databricks/dbt-databricks) + +### Syncing of `dlt` state +This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination). diff --git a/docs/website/docs/dlt-ecosystem/destinations/mssql.md b/docs/website/docs/dlt-ecosystem/destinations/mssql.md index d64cf9b400..e98f8bf256 100644 --- a/docs/website/docs/dlt-ecosystem/destinations/mssql.md +++ b/docs/website/docs/dlt-ecosystem/destinations/mssql.md @@ -16,16 +16,14 @@ pip install dlt[mssql] ### Prerequisites -Microsoft ODBC driver for SQL Server must be installed to use this destination. -This can't be included with `dlt`s python dependencies so you must installed it separately on your system. +_Microsoft ODBC Driver for SQL Server_ must be installed to use this destination. +This can't be included with `dlt`'s python dependencies, so you must install it separately on your system. You can find the official installation instructions [here](https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16). -See instructions here to [install Microsoft ODBC Driver 18 for SQL Server on Windows, Mac and Linux](https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16) +Supported driver versions: +* `ODBC Driver 18 for SQL Server` +* `ODBC Driver 17 for SQL Server` -Following ODBC drivers are supported: -* ODBC Driver 18 for SQL Server -* ODBC Driver 17 for SQL Server - -[You can configure driver name explicitly](#additional-destination-options) as well. +You can [configure driver name](#additional-destination-options) explicitly as well. ### Create a pipeline diff --git a/docs/website/docs/dlt-ecosystem/destinations/synapse.md b/docs/website/docs/dlt-ecosystem/destinations/synapse.md new file mode 100644 index 0000000000..8c1a7b29bc --- /dev/null +++ b/docs/website/docs/dlt-ecosystem/destinations/synapse.md @@ -0,0 +1,204 @@ +--- +title: Azure Synapse +description: Azure Synapse `dlt` destination +keywords: [synapse, destination, data warehouse] +--- + +# Synapse + +## Install dlt with Synapse +**To install the DLT library with Synapse dependencies:** +``` +pip install dlt[synapse] +``` + +## Setup guide + +### Prerequisites + +* **Microsoft ODBC Driver for SQL Server** + + _Microsoft ODBC Driver for SQL Server_ must be installed to use this destination. + This can't be included with `dlt`'s python dependencies, so you must install it separately on your system. You can find the official installation instructions [here](https://learn.microsoft.com/en-us/sql/connect/odbc/download-odbc-driver-for-sql-server?view=sql-server-ver16). + + Supported driver versions: + * `ODBC Driver 18 for SQL Server` + + > 💡 Older driver versions don't properly work, because they don't support the `LongAsMax` keyword that got [introduced](https://learn.microsoft.com/en-us/sql/connect/odbc/windows/features-of-the-microsoft-odbc-driver-for-sql-server-on-windows?view=sql-server-ver15#microsoft-odbc-driver-180-for-sql-server-on-windows) in `ODBC Driver 18 for SQL Server`. Synapse does not support the legacy ["long data types"](https://learn.microsoft.com/en-us/sql/t-sql/data-types/ntext-text-and-image-transact-sql), and requires "max data types" instead. `dlt` uses the `LongAsMax` keyword to automatically do the conversion. +* **Azure Synapse Workspace and dedicated SQL pool** + + You need an Azure Synapse workspace with a dedicated SQL pool to load data into. If you don't have one yet, you can use this [quickstart](https://learn.microsoft.com/en-us/azure/synapse-analytics/quickstart-create-sql-pool-studio). + +### Steps + +**1. Initialize a project with a pipeline that loads to Synapse by running** +``` +dlt init chess synapse +``` + +**2. Install the necessary dependencies for Synapse by running** +``` +pip install -r requirements.txt +``` +This will install `dlt` with the **synapse** extra that contains all dependencies required for the Synapse destination. + +**3. Create a loader user** + +Execute the following SQL statements to set up the [loader](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql/data-loading-best-practices#create-a-loading-user) user. Change the password and replace `yourpool` with the name of your dedicated SQL pool: +```sql +-- on master database, using a SQL admin account + +CREATE LOGIN loader WITH PASSWORD = 'your_loader_password'; +``` + +```sql +-- on yourpool database + +CREATE USER loader FOR LOGIN loader; + +-- DDL permissions +GRANT CREATE SCHEMA ON DATABASE :: yourpool TO loader; +GRANT CREATE TABLE ON DATABASE :: yourpool TO loader; +GRANT CREATE VIEW ON DATABASE :: yourpool TO loader; + +-- DML permissions +GRANT ADMINISTER DATABASE BULK OPERATIONS TO loader; -- only required when loading from staging Storage Account +``` + +Optionally, you can create a `WORKLOAD GROUP` and add the `loader` user as a member to manage [workload isolation](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-workload-isolation). See the [instructions](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql/data-loading-best-practices#create-a-loading-user) on setting up a loader user for an example of how to do this. + +**3. Enter your credentials into `.dlt/secrets.toml`.** + +Example, replace with your database connection info: +```toml +[destination.synapse.credentials] +database = "yourpool" +username = "loader" +password = "your_loader_password" +host = "your_synapse_workspace_name.sql.azuresynapse.net" +``` + +Equivalently, you can also pass a connection string as follows: + +```toml +# keep it at the top of your toml file! before any section starts +destination.synapse.credentials = "synapse://loader:your_loader_password@your_synapse_workspace_name.azuresynapse.net/yourpool" +``` + +To pass credentials directly you can use the `credentials` argument of `dlt.destinations.synapse(...)`: +```python +pipeline = dlt.pipeline( + pipeline_name='chess', + destination=dlt.destinations.synapse( + credentials='synapse://loader:your_loader_password@your_synapse_workspace_name.azuresynapse.net/yourpool' + ), + dataset_name='chess_data' +) +``` + +## Write disposition +All write dispositions are supported + +If you set the [`replace` strategy](../../general-usage/full-loading.md) to `staging-optimized`, the destination tables will be dropped and replaced by the staging tables with an `ALTER SCHEMA ... TRANSFER` command. Please note that this operation is **not** atomic—it involves multiple DDL commands and Synapse does not support DDL transactions. + +## Data loading +Data is loaded via `INSERT` statements by default. + +> 💡 Multi-row `INSERT INTO ... VALUES` statements are **not** possible in Synapse, because it doesn't support the [Table Value Constructor](https://learn.microsoft.com/en-us/sql/t-sql/queries/table-value-constructor-transact-sql). `dlt` uses `INSERT INTO ... SELECT ... UNION` statements as described [here](https://stackoverflow.com/a/73579830) to work around this limitation. + +## Supported file formats +* [insert-values](../file-formats/insert-format.md) is used by default +* [parquet](../file-formats/parquet.md) is used when [staging](#staging-support) is enabled + +## Data type limitations +* **Synapse cannot load `TIME` columns from `parquet` files**. `dlt` will fail such jobs permanently. Use the `insert_values` file format instead, or convert `datetime.time` objects to `str` or `datetime.datetime`, to load `TIME` columns. +* **Synapse does not have a complex/JSON/struct data type**. The `dlt` `complex` data type is mapped to the `nvarchar` type in Synapse. + +## Table index type +The [table index type](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index) of the created tables can be configured at the resource level with the `synapse_adapter`: + +```python +info = pipeline.run( + synapse_adapter( + data=your_resource, + table_index_type="clustered_columnstore_index", + ) +) +``` + +Possible values: +* `heap`: create [HEAP](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#heap-tables) tables that do not have an index **(default)** +* `clustered_columnstore_index`: create [CLUSTERED COLUMNSTORE INDEX](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#clustered-columnstore-indexes) tables + + +> ❗ Important: +>* **Set `default_table_index_type` to `"clustered_columnstore_index"` if you want to change the default** (see [additional destination options](#additional-destination-options)). +>* **CLUSTERED COLUMNSTORE INDEX tables do not support the `varchar(max)`, `nvarchar(max)`, and `varbinary(max)` data types.** If you don't specify the `precision` for columns that map to any of these types, `dlt` will use the maximum lengths `varchar(4000)`, `nvarchar(4000)`, and `varbinary(8000)`. +>* **While Synapse creates CLUSTERED COLUMNSTORE INDEXES by default, `dlt` creates HEAP tables by default.** HEAP is a more robust choice, because it supports all data types and doesn't require conversions. +>* **When using the `insert-from-staging` [`replace` strategy](../../general-usage/full-loading.md), the staging tables are always created as HEAP tables**—any configuration of the table index types is ignored. The HEAP strategy makes sense + for staging tables for reasons explained [here](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-index#heap-tables). +>* **When using the `staging-optimized` [`replace` strategy](../../general-usage/full-loading.md), the staging tables are already created with the configured table index type**, because the staging table becomes the final table. +>* **`dlt` system tables are always created as HEAP tables, regardless of any configuration.** This is in line with Microsoft's recommendation that "for small lookup tables, less than 60 million rows, consider using HEAP or clustered index for faster query performance." +>* Child tables, if any, inherent the table index type of their parent table. + +## Supported column hints + +Synapse supports the following [column hints](https://dlthub.com/docs/general-usage/schema#tables-and-columns): + +* `primary_key` - creates a `PRIMARY KEY NONCLUSTERED NOT ENFORCED` constraint on the column +* `unique` - creates a `UNIQUE NOT ENFORCED` constraint on the column + +> ❗ These hints are **disabled by default**. This is because the `PRIMARY KEY` and `UNIQUE` [constraints](https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints) are tricky in Synapse: they are **not enforced** and can lead to innacurate results if the user does not ensure all column values are unique. For the column hints to take effect, the `create_indexes` configuration needs to be set to `True`, see [additional destination options](#additional-destination-options). + +## Staging support +Synapse supports Azure Blob Storage (both standard and [ADLS Gen2](https://learn.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction)) as a file staging destination. `dlt` first uploads Parquet files to the blob container, and then instructs Synapse to read the Parquet file and load its data into a Synapse table using the [COPY INTO](https://learn.microsoft.com/en-us/sql/t-sql/statements/copy-into-transact-sql) statement. + +Please refer to the [Azure Blob Storage filesystem documentation](./filesystem.md#azure-blob-storage) to learn how to configure credentials for the staging destination. By default, `dlt` will use these credentials for both the write into the blob container, and the read from it to load into Synapse. Managed Identity authentication can be enabled through the `staging_use_msi` option (see [additional destination options](#additional-destination-options)). + +To run Synapse with staging on Azure Blob Storage: + +```python +# Create a dlt pipeline that will load +# chess player data to the snowflake destination +# via staging on Azure Blob Storage +pipeline = dlt.pipeline( + pipeline_name='chess_pipeline', + destination='synapse', + staging='filesystem', # add this to activate the staging location + dataset_name='player_data' +) +``` + +## Additional destination options +The following settings can optionally be configured: +```toml +[destination.synapse] +default_table_index_type = "heap" +create_indexes = "false" +staging_use_msi = "false" + +[destination.synapse.credentials] +port = "1433" +connect_timeout = 15 +``` + +`port` and `connect_timeout` can also be included in the connection string: + +```toml +# keep it at the top of your toml file! before any section starts +destination.synapse.credentials = "synapse://loader:your_loader_password@your_synapse_workspace_name.azuresynapse.net:1433/yourpool?connect_timeout=15" +``` + +Descriptions: +- `default_table_index_type` sets the [table index type](#table-index-type) that is used if no table index type is specified on the resource. +- `create_indexes` determines if `primary_key` and `unique` [column hints](#supported-column-hints) are applied. +- `staging_use_msi` determines if the Managed Identity of the Synapse workspace is used to authorize access to the [staging](#staging-support) Storage Account. Ensure the Managed Identity has the [Storage Blob Data Reader](https://learn.microsoft.com/en-us/azure/role-based-access-control/built-in-roles#storage-blob-data-reader) role (or a higher-priviliged role) assigned on the blob container if you set this option to `"true"`. +- `port` used for the ODBC connection. +- `connect_timeout` sets the timeout for the `pyodbc` connection attempt, in seconds. + +### dbt support +Integration with [dbt](../transformations/dbt/dbt.md) is currently not supported. + +### Syncing of `dlt` state +This destination fully supports [dlt state sync](../../general-usage/state#syncing-state-with-destination). + diff --git a/docs/website/docs/examples/transformers/index.md b/docs/website/docs/examples/transformers/index.md index 7ed8fd29c3..860e830aae 100644 --- a/docs/website/docs/examples/transformers/index.md +++ b/docs/website/docs/examples/transformers/index.md @@ -9,7 +9,7 @@ import Header from '../_examples-header.md';
diff --git a/docs/website/docs/general-usage/customising-pipelines/removing_columns.md b/docs/website/docs/general-usage/customising-pipelines/removing_columns.md new file mode 100644 index 0000000000..8493ffaec5 --- /dev/null +++ b/docs/website/docs/general-usage/customising-pipelines/removing_columns.md @@ -0,0 +1,91 @@ +--- +title: Removing columns +description: Removing columns by passing list of column names +keywords: [deleting, removing, columns, drop] +--- + +# Removing columns + +Removing columns before loading data into a database is a reliable method to eliminate sensitive or +unnecessary fields. For example, in the given scenario, a source is created with a "country_id" column, +which is then excluded from the database before loading. + +Let's create a sample pipeline demonstrating the process of removing a column. + +1. Create a source function that creates dummy data as follows: + + ```python + import dlt + + # This function creates a dummy data source. + @dlt.source + def dummy_source(): + @dlt.resource(write_disposition="replace") + def dummy_data(): + for i in range(3): + yield {"id": i, "name": f"Jane Washington {i}", "country_code": 40 + i} + + return dummy_data() + ``` + This function creates three columns `id`, `name` and `country_code`. + +1. Next, create a function to filter out columns from the data before loading it into a database as follows: + + ```python + from typing import Dict, List, Optional + + def remove_columns(doc: Dict, remove_columns: Optional[List[str]] = None) -> Dict: + if remove_columns is None: + remove_columns = [] + + # Iterating over the list of columns to be removed + for column_name in remove_columns: + # Removing the column if it exists in the document + if column_name in doc: + del doc[column_name] + + return doc + ``` + + `doc`: The document (dict) from which columns will be removed. + + `remove_columns`: List of column names to be removed, defaults to None. + +1. Next, declare the columns to be removed from the table, and then modify the source as follows: + + ```python + # Example columns to remove: + remove_columns_list = ["country_code"] + + # Create an instance of the source so you can edit it. + data_source = dummy_source() + + # Modify this source instance's resource + data_source = data_source.dummy_data.add_map( + lambda doc: remove_columns(doc, remove_columns_list) + ) + ``` +1. You can optionally inspect the result: + + ```python + for row in data_source: + print(row) + #{'id': 0, 'name': 'Jane Washington 0'} + #{'id': 1, 'name': 'Jane Washington 1'} + #{'id': 2, 'name': 'Jane Washington 2'} + ``` + +1. At last, create a pipeline: + + ```python + # Integrating with a DLT pipeline + pipeline = dlt.pipeline( + pipeline_name='example', + destination='bigquery', + dataset_name='filtered_data' + ) + # Run the pipeline with the transformed source + load_info = pipeline.run(data_source) + print(load_info) + ``` + diff --git a/docs/website/docs/general-usage/full-loading.md b/docs/website/docs/general-usage/full-loading.md index 92fdf064fd..4651d156f0 100644 --- a/docs/website/docs/general-usage/full-loading.md +++ b/docs/website/docs/general-usage/full-loading.md @@ -67,6 +67,4 @@ opportunities, you should use this strategy. The `staging-optimized` strategy be recreated with a [clone command](https://docs.snowflake.com/en/sql-reference/sql/create-clone) from the staging tables. This is a low cost and fast way to create a second independent table from the data of another. Learn more about [table cloning on snowflake](https://docs.snowflake.com/en/user-guide/object-clone). -For all other destinations the `staging-optimized` will fall back to the behavior of the `insert-from-staging` strategy. - - +For all other [destinations](../dlt-ecosystem/destinations/index.md), please look at their respective documentation pages to see if and how the `staging-optimized` strategy is implemented. If it is not implemented, `dlt` will fall back to the `insert-from-staging` strategy. diff --git a/docs/website/docs/general-usage/incremental-loading.md b/docs/website/docs/general-usage/incremental-loading.md index 0dc85332de..09b8ca7a96 100644 --- a/docs/website/docs/general-usage/incremental-loading.md +++ b/docs/website/docs/general-usage/incremental-loading.md @@ -290,7 +290,7 @@ def stripe(): yield data # create resources for several endpoints on a single decorator function - for endpoint in Endpoints: + for endpoint in endpoints: yield dlt.resource( get_resource, name=endpoint.value, diff --git a/docs/website/docs/general-usage/pipeline.md b/docs/website/docs/general-usage/pipeline.md index 4850027f24..095e03e96d 100644 --- a/docs/website/docs/general-usage/pipeline.md +++ b/docs/website/docs/general-usage/pipeline.md @@ -7,9 +7,9 @@ keywords: [pipeline, source, full refresh] # Pipeline A [pipeline](glossary.md#pipeline) is a connection that moves the data from your Python code to a -[destination](glossary.md#destination). Typically, you pass the `dlt` [sources](source.md) or -[resources](resource.md) to the pipeline. You can also pass generators, lists and other iterables to -it. When the pipeline runs, the resources get executed and the data is loaded at destination. +[destination](glossary.md#destination). The pipeline accepts `dlt` [sources](source.md) or +[resources](resource.md) as well as generators, async generators, lists and any iterables. +Once the pipeline runs, all resources get evaluated and the data is loaded at destination. Example: diff --git a/docs/website/sidebars.js b/docs/website/sidebars.js index 2e23c5ca45..a906526e95 100644 --- a/docs/website/sidebars.js +++ b/docs/website/sidebars.js @@ -88,6 +88,7 @@ const sidebars = { 'dlt-ecosystem/destinations/bigquery', 'dlt-ecosystem/destinations/duckdb', 'dlt-ecosystem/destinations/mssql', + 'dlt-ecosystem/destinations/synapse', 'dlt-ecosystem/destinations/filesystem', 'dlt-ecosystem/destinations/postgres', 'dlt-ecosystem/destinations/redshift', @@ -220,6 +221,7 @@ const sidebars = { items: [ 'general-usage/customising-pipelines/renaming_columns', 'general-usage/customising-pipelines/pseudonymizing_columns', + 'general-usage/customising-pipelines/removing_columns', ] }, { diff --git a/mypy.ini b/mypy.ini index 8a02cf80bd..d4da898a0f 100644 --- a/mypy.ini +++ b/mypy.ini @@ -104,4 +104,7 @@ ignore_missing_imports=true [mypy-s3fs.*] ignore_missing_imports=true [mypy-win_precise_time] +ignore_missing_imports=true + +[mypy-databricks.*] 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["duckdb"] +filesystem = ["botocore", "s3fs"] +gcp = ["gcsfs", "google-cloud-bigquery", "grpcio"] +gs = ["gcsfs"] +motherduck = ["duckdb", "pyarrow"] +mssql = ["pyodbc"] +parquet = ["pyarrow"] +postgres = ["psycopg2-binary", "psycopg2cffi"] +qdrant = ["qdrant-client"] +redshift = ["psycopg2-binary", "psycopg2cffi"] +s3 = ["botocore", "s3fs"] +snowflake = ["snowflake-connector-python"] +synapse = ["adlfs", "pyarrow", "pyodbc"] +weaviate = ["weaviate-client"] + +[metadata] +lock-version = "2.0" +python-versions = ">=3.8.1,<3.13" +content-hash = "7b829a75b59316147385e16456395bebf2155e68cdeac3f9fa70523c3c33924a" diff --git a/pyproject.toml b/pyproject.toml index 8e4c9dc015..0ca08b4727 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -76,11 +76,11 @@ weaviate-client = {version = ">=3.22", optional = true} adlfs = {version = ">=2022.4.0", optional = true} pyodbc = {version = "^4.0.39", optional = true} qdrant-client = {version = "^1.6.4", optional = true, extras = ["fastembed"]} -pydata-google-auth = "^1.8.2" -google-api-python-client = "^2.116.0" +databricks-sql-connector = {version = ">=2.9.3,<3.0.0", optional = true} +dbt-databricks = {version = "^1.7.3", optional = true} [tool.poetry.extras] -dbt = ["dbt-core", "dbt-redshift", "dbt-bigquery", "dbt-duckdb", "dbt-snowflake", "dbt-athena-community"] +dbt = ["dbt-core", "dbt-redshift", "dbt-bigquery", "dbt-duckdb", "dbt-snowflake", "dbt-athena-community", "dbt-databricks"] gcp = ["grpcio", "google-cloud-bigquery", "db-dtypes", "gcsfs"] # bigquery is alias on gcp extras bigquery = ["grpcio", "google-cloud-bigquery", "pyarrow", "db-dtypes", "gcsfs"] @@ -98,7 +98,9 @@ cli = ["pipdeptree", "cron-descriptor"] athena = ["pyathena", "pyarrow", "s3fs", "botocore"] weaviate = ["weaviate-client"] mssql = ["pyodbc"] +synapse = ["pyodbc", "adlfs", "pyarrow"] qdrant = ["qdrant-client"] +databricks = ["databricks-sql-connector"] [tool.poetry.scripts] dlt = "dlt.cli._dlt:_main" diff --git a/tests/common/storages/utils.py b/tests/common/storages/utils.py index 3146642536..bd30ad1d6f 100644 --- a/tests/common/storages/utils.py +++ b/tests/common/storages/utils.py @@ -48,9 +48,6 @@ def assert_sample_files( assert len(all_file_items) >= 10 for item in all_file_items: - # skip pseudo files that look like folders - if item["file_url"].endswith("/"): - continue # only accept file items we know assert item["file_name"] in minimally_expected_file_items diff --git a/tests/load/databricks/__init__.py b/tests/load/databricks/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/load/databricks/test_databricks_configuration.py b/tests/load/databricks/test_databricks_configuration.py new file mode 100644 index 0000000000..9127e39be4 --- /dev/null +++ b/tests/load/databricks/test_databricks_configuration.py @@ -0,0 +1,32 @@ +import pytest +import os + +pytest.importorskip("databricks") + + +from dlt.destinations.impl.databricks.configuration import DatabricksClientConfiguration +from dlt.common.configuration import resolve_configuration +from tests.utils import preserve_environ + + +def test_databricks_credentials_to_connector_params(): + os.environ["CREDENTIALS__SERVER_HOSTNAME"] = "my-databricks.example.com" + os.environ["CREDENTIALS__HTTP_PATH"] = "/sql/1.0/warehouses/asdfe" + os.environ["CREDENTIALS__ACCESS_TOKEN"] = "my-token" + os.environ["CREDENTIALS__CATALOG"] = "my-catalog" + # JSON encoded dict of extra args + os.environ["CREDENTIALS__CONNECTION_PARAMETERS"] = '{"extra_a": "a", "extra_b": "b"}' + + config = resolve_configuration(DatabricksClientConfiguration(dataset_name="my-dataset")) + + credentials = config.credentials + + params = credentials.to_connector_params() + + assert params["server_hostname"] == "my-databricks.example.com" + assert params["http_path"] == "/sql/1.0/warehouses/asdfe" + assert params["access_token"] == "my-token" + assert params["catalog"] == "my-catalog" + assert params["extra_a"] == "a" + assert params["extra_b"] == "b" + assert params["_socket_timeout"] == credentials.socket_timeout diff --git a/tests/load/mssql/test_mssql_credentials.py b/tests/load/mssql/test_mssql_credentials.py index 0098d228f1..0e38791f22 100644 --- a/tests/load/mssql/test_mssql_credentials.py +++ b/tests/load/mssql/test_mssql_credentials.py @@ -1,18 +1,35 @@ import pyodbc import pytest -from dlt.common.configuration import resolve_configuration +from dlt.common.configuration import resolve_configuration, ConfigFieldMissingException from dlt.common.exceptions import SystemConfigurationException -from dlt.destinations.impl.mssql.configuration import MsSqlCredentials, SUPPORTED_DRIVERS +from dlt.destinations.impl.mssql.configuration import MsSqlCredentials -def test_parse_native_representation_unsupported_driver_specified() -> None: +def test_mssql_credentials_defaults() -> None: + creds = MsSqlCredentials() + assert creds.port == 1433 + assert creds.connect_timeout == 15 + assert MsSqlCredentials.__config_gen_annotations__ == ["port", "connect_timeout"] + # port should be optional + resolve_configuration(creds, explicit_value="mssql://loader:loader@localhost/dlt_data") + assert creds.port == 1433 + + +def test_parse_native_representation() -> None: # Case: unsupported driver specified. with pytest.raises(SystemConfigurationException): resolve_configuration( MsSqlCredentials( - "mssql://test_user:test_password@sql.example.com:12345/test_db?DRIVER=foo" + "mssql://test_user:test_pwd@sql.example.com/test_db?DRIVER=ODBC+Driver+13+for+SQL+Server" + ) + ) + # Case: password not specified. + with pytest.raises(ConfigFieldMissingException): + resolve_configuration( + MsSqlCredentials( + "mssql://test_user@sql.example.com/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server" ) ) @@ -21,33 +38,49 @@ def test_to_odbc_dsn_supported_driver_specified() -> None: # Case: supported driver specified — ODBC Driver 18 for SQL Server. creds = resolve_configuration( MsSqlCredentials( - "mssql://test_user:test_password@sql.example.com:12345/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server" + "mssql://test_user:test_pwd@sql.example.com/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server" ) ) dsn = creds.to_odbc_dsn() result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} assert result == { "DRIVER": "ODBC Driver 18 for SQL Server", - "SERVER": "sql.example.com,12345", + "SERVER": "sql.example.com,1433", "DATABASE": "test_db", "UID": "test_user", - "PWD": "test_password", + "PWD": "test_pwd", } # Case: supported driver specified — ODBC Driver 17 for SQL Server. creds = resolve_configuration( MsSqlCredentials( - "mssql://test_user:test_password@sql.example.com:12345/test_db?DRIVER=ODBC+Driver+17+for+SQL+Server" + "mssql://test_user:test_pwd@sql.example.com/test_db?DRIVER=ODBC+Driver+17+for+SQL+Server" ) ) dsn = creds.to_odbc_dsn() result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} assert result == { "DRIVER": "ODBC Driver 17 for SQL Server", + "SERVER": "sql.example.com,1433", + "DATABASE": "test_db", + "UID": "test_user", + "PWD": "test_pwd", + } + + # Case: port and supported driver specified. + creds = resolve_configuration( + MsSqlCredentials( + "mssql://test_user:test_pwd@sql.example.com:12345/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server" + ) + ) + dsn = creds.to_odbc_dsn() + result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} + assert result == { + "DRIVER": "ODBC Driver 18 for SQL Server", "SERVER": "sql.example.com,12345", "DATABASE": "test_db", "UID": "test_user", - "PWD": "test_password", + "PWD": "test_pwd", } @@ -55,7 +88,7 @@ def test_to_odbc_dsn_arbitrary_keys_specified() -> None: # Case: arbitrary query keys (and supported driver) specified. creds = resolve_configuration( MsSqlCredentials( - "mssql://test_user:test_password@sql.example.com:12345/test_db?FOO=a&BAR=b&DRIVER=ODBC+Driver+18+for+SQL+Server" + "mssql://test_user:test_pwd@sql.example.com:12345/test_db?FOO=a&BAR=b&DRIVER=ODBC+Driver+18+for+SQL+Server" ) ) dsn = creds.to_odbc_dsn() @@ -65,7 +98,7 @@ def test_to_odbc_dsn_arbitrary_keys_specified() -> None: "SERVER": "sql.example.com,12345", "DATABASE": "test_db", "UID": "test_user", - "PWD": "test_password", + "PWD": "test_pwd", "FOO": "a", "BAR": "b", } @@ -73,7 +106,7 @@ def test_to_odbc_dsn_arbitrary_keys_specified() -> None: # Case: arbitrary capitalization. creds = resolve_configuration( MsSqlCredentials( - "mssql://test_user:test_password@sql.example.com:12345/test_db?FOO=a&bar=b&Driver=ODBC+Driver+18+for+SQL+Server" + "mssql://test_user:test_pwd@sql.example.com:12345/test_db?FOO=a&bar=b&Driver=ODBC+Driver+18+for+SQL+Server" ) ) dsn = creds.to_odbc_dsn() @@ -83,30 +116,30 @@ def test_to_odbc_dsn_arbitrary_keys_specified() -> None: "SERVER": "sql.example.com,12345", "DATABASE": "test_db", "UID": "test_user", - "PWD": "test_password", + "PWD": "test_pwd", "FOO": "a", "BAR": "b", } -available_drivers = [d for d in pyodbc.drivers() if d in SUPPORTED_DRIVERS] +available_drivers = [d for d in pyodbc.drivers() if d in MsSqlCredentials.SUPPORTED_DRIVERS] @pytest.mark.skipif(not available_drivers, reason="no supported driver available") def test_to_odbc_dsn_driver_not_specified() -> None: # Case: driver not specified, but supported driver is available. creds = resolve_configuration( - MsSqlCredentials("mssql://test_user:test_password@sql.example.com:12345/test_db") + MsSqlCredentials("mssql://test_user:test_pwd@sql.example.com/test_db") ) dsn = creds.to_odbc_dsn() result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} assert result in [ { "DRIVER": d, - "SERVER": "sql.example.com,12345", + "SERVER": "sql.example.com,1433", "DATABASE": "test_db", "UID": "test_user", - "PWD": "test_password", + "PWD": "test_pwd", } - for d in SUPPORTED_DRIVERS + for d in MsSqlCredentials.SUPPORTED_DRIVERS ] diff --git a/tests/load/mssql/test_mssql_table_builder.py b/tests/load/mssql/test_mssql_table_builder.py index f7e0ce53ff..039ce99113 100644 --- a/tests/load/mssql/test_mssql_table_builder.py +++ b/tests/load/mssql/test_mssql_table_builder.py @@ -1,11 +1,10 @@ import pytest -from copy import deepcopy import sqlfluff from dlt.common.utils import uniq_id from dlt.common.schema import Schema -pytest.importorskip("dlt.destinations.mssql.mssql", reason="MSSQL ODBC driver not installed") +pytest.importorskip("dlt.destinations.impl.mssql.mssql", reason="MSSQL ODBC driver not installed") from dlt.destinations.impl.mssql.mssql import MsSqlClient from dlt.destinations.impl.mssql.configuration import MsSqlClientConfiguration, MsSqlCredentials diff --git a/tests/load/pipeline/test_arrow_loading.py b/tests/load/pipeline/test_arrow_loading.py index 4a3c209c32..7f159f57b7 100644 --- a/tests/load/pipeline/test_arrow_loading.py +++ b/tests/load/pipeline/test_arrow_loading.py @@ -35,6 +35,7 @@ def test_load_item( include_time = destination_config.destination not in ( "athena", "redshift", + "databricks", ) # athena/redshift can't load TIME columns from parquet item, records = arrow_table_all_data_types( item_type, include_json=False, include_time=include_time diff --git a/tests/load/pipeline/test_dbt_helper.py b/tests/load/pipeline/test_dbt_helper.py index 11f59d5276..91318d0f34 100644 --- a/tests/load/pipeline/test_dbt_helper.py +++ b/tests/load/pipeline/test_dbt_helper.py @@ -28,7 +28,9 @@ def dbt_venv() -> Iterator[Venv]: @pytest.mark.parametrize( - "destination_config", destinations_configs(default_sql_configs=True), ids=lambda x: x.name + "destination_config", + destinations_configs(default_sql_configs=True, supports_dbt=True), + ids=lambda x: x.name, ) def test_run_jaffle_package( destination_config: DestinationTestConfiguration, dbt_venv: Venv @@ -55,21 +57,21 @@ def test_run_jaffle_package( assert all(r.status == "pass" for r in tests) # get and display dataframe with customers - customers = select_data(pipeline, "SELECT * FROM customers") + qual_name = pipeline.sql_client().make_qualified_table_name + customers = select_data(pipeline, f"SELECT * FROM {qual_name('customers')}") assert len(customers) == 100 - orders = select_data(pipeline, "SELECT * FROM orders") + orders = select_data(pipeline, f"SELECT * FROM {qual_name('orders')}") assert len(orders) == 99 @pytest.mark.parametrize( - "destination_config", destinations_configs(default_sql_configs=True), ids=lambda x: x.name + "destination_config", + destinations_configs(default_sql_configs=True, supports_dbt=True), + ids=lambda x: x.name, ) def test_run_chess_dbt(destination_config: DestinationTestConfiguration, dbt_venv: Venv) -> None: from docs.examples.chess.chess import chess - if not destination_config.supports_dbt: - pytest.skip("dbt is not supported for this destination configuration") - # provide chess url via environ os.environ["CHESS_URL"] = "https://api.chess.com/pub/" @@ -114,16 +116,15 @@ def test_run_chess_dbt(destination_config: DestinationTestConfiguration, dbt_ven @pytest.mark.parametrize( - "destination_config", destinations_configs(default_sql_configs=True), ids=lambda x: x.name + "destination_config", + destinations_configs(default_sql_configs=True, supports_dbt=True), + ids=lambda x: x.name, ) def test_run_chess_dbt_to_other_dataset( destination_config: DestinationTestConfiguration, dbt_venv: Venv ) -> None: from docs.examples.chess.chess import chess - if not destination_config.supports_dbt: - pytest.skip("dbt is not supported for this destination configuration") - # provide chess url via environ os.environ["CHESS_URL"] = "https://api.chess.com/pub/" diff --git a/tests/load/pipeline/test_pipelines.py b/tests/load/pipeline/test_pipelines.py index d170fd553b..af61dc5d3d 100644 --- a/tests/load/pipeline/test_pipelines.py +++ b/tests/load/pipeline/test_pipelines.py @@ -788,7 +788,7 @@ def other_data(): column_schemas["col11_precision"]["precision"] = 0 # drop TIME from databases not supporting it via parquet - if destination_config.destination in ["redshift", "athena"]: + if destination_config.destination in ["redshift", "athena", "synapse", "databricks"]: data_types.pop("col11") data_types.pop("col11_null") data_types.pop("col11_precision") @@ -827,15 +827,16 @@ def some_source(): assert len(package_info.jobs["completed_jobs"]) == expected_completed_jobs with pipeline.sql_client() as sql_client: + qual_name = sql_client.make_qualified_table_name assert [ - row[0] for row in sql_client.execute_sql("SELECT * FROM other_data ORDER BY 1") + row[0] + for row in sql_client.execute_sql(f"SELECT * FROM {qual_name('other_data')} ORDER BY 1") ] == [1, 2, 3, 4, 5] - assert [row[0] for row in sql_client.execute_sql("SELECT * FROM some_data ORDER BY 1")] == [ - 1, - 2, - 3, - ] - db_rows = sql_client.execute_sql("SELECT * FROM data_types") + assert [ + row[0] + for row in sql_client.execute_sql(f"SELECT * FROM {qual_name('some_data')} ORDER BY 1") + ] == [1, 2, 3] + db_rows = sql_client.execute_sql(f"SELECT * FROM {qual_name('data_types')}") assert len(db_rows) == 10 db_row = list(db_rows[0]) # "snowflake" and "bigquery" do not parse JSON form parquet string so double parse diff --git a/tests/load/pipeline/test_stage_loading.py b/tests/load/pipeline/test_stage_loading.py index de4a7f4c3b..222171ca61 100644 --- a/tests/load/pipeline/test_stage_loading.py +++ b/tests/load/pipeline/test_stage_loading.py @@ -94,7 +94,13 @@ def test_staging_load(destination_config: DestinationTestConfiguration) -> None: # check item of first row in db with pipeline.sql_client() as sql_client: - rows = sql_client.execute_sql("SELECT url FROM issues WHERE id = 388089021 LIMIT 1") + if destination_config.destination in ["mssql", "synapse"]: + qual_name = sql_client.make_qualified_table_name + rows = sql_client.execute_sql( + f"SELECT TOP 1 url FROM {qual_name('issues')} WHERE id = 388089021" + ) + else: + rows = sql_client.execute_sql("SELECT url FROM issues WHERE id = 388089021 LIMIT 1") assert rows[0][0] == "https://api.github.com/repos/duckdb/duckdb/issues/71" if destination_config.supports_merge: @@ -109,10 +115,23 @@ def test_staging_load(destination_config: DestinationTestConfiguration) -> None: # check changes where merged in with pipeline.sql_client() as sql_client: - rows = sql_client.execute_sql("SELECT number FROM issues WHERE id = 1232152492 LIMIT 1") - assert rows[0][0] == 105 - rows = sql_client.execute_sql("SELECT number FROM issues WHERE id = 1142699354 LIMIT 1") - assert rows[0][0] == 300 + if destination_config.destination in ["mssql", "synapse"]: + qual_name = sql_client.make_qualified_table_name + rows_1 = sql_client.execute_sql( + f"SELECT TOP 1 number FROM {qual_name('issues')} WHERE id = 1232152492" + ) + rows_2 = sql_client.execute_sql( + f"SELECT TOP 1 number FROM {qual_name('issues')} WHERE id = 1142699354" + ) + else: + rows_1 = sql_client.execute_sql( + "SELECT number FROM issues WHERE id = 1232152492 LIMIT 1" + ) + rows_2 = sql_client.execute_sql( + "SELECT number FROM issues WHERE id = 1142699354 LIMIT 1" + ) + assert rows_1[0][0] == 105 + assert rows_2[0][0] == 300 # test append info = pipeline.run( @@ -158,15 +177,22 @@ def test_all_data_types(destination_config: DestinationTestConfiguration) -> Non if destination_config.destination in ( "redshift", "athena", + "databricks", ) and destination_config.file_format in ("parquet", "jsonl"): # Redshift copy doesn't support TIME column exclude_types.append("time") + if destination_config.destination == "synapse" and destination_config.file_format == "parquet": + # TIME columns are not supported for staged parquet loads into Synapse + exclude_types.append("time") if destination_config.destination == "redshift" and destination_config.file_format in ( "parquet", "jsonl", ): # Redshift can't load fixed width binary columns from parquet exclude_columns.append("col7_precision") + if destination_config.destination == "databricks" and destination_config.file_format == "jsonl": + exclude_types.extend(["decimal", "binary", "wei", "complex", "date"]) + exclude_columns.append("col1_precision") column_schemas, data_types = table_update_and_row( exclude_types=exclude_types, exclude_columns=exclude_columns @@ -199,7 +225,8 @@ def my_source(): assert_load_info(info) with pipeline.sql_client() as sql_client: - db_rows = sql_client.execute_sql("SELECT * FROM data_types") + qual_name = sql_client.make_qualified_table_name + db_rows = sql_client.execute_sql(f"SELECT * FROM {qual_name('data_types')}") assert len(db_rows) == 10 db_row = list(db_rows[0]) # parquet is not really good at inserting json, best we get are strings in JSON columns diff --git a/tests/load/synapse/__init__.py b/tests/load/synapse/__init__.py new file mode 100644 index 0000000000..34119d38cb --- /dev/null +++ b/tests/load/synapse/__init__.py @@ -0,0 +1,3 @@ +from tests.utils import skip_if_not_active + +skip_if_not_active("synapse") diff --git a/tests/load/synapse/test_synapse_configuration.py b/tests/load/synapse/test_synapse_configuration.py new file mode 100644 index 0000000000..4055cbab38 --- /dev/null +++ b/tests/load/synapse/test_synapse_configuration.py @@ -0,0 +1,46 @@ +import pytest + +from dlt.common.configuration import resolve_configuration +from dlt.common.exceptions import SystemConfigurationException + +from dlt.destinations.impl.synapse.configuration import ( + SynapseClientConfiguration, + SynapseCredentials, +) + + +def test_synapse_configuration() -> None: + # By default, unique indexes should not be created. + assert SynapseClientConfiguration().create_indexes is False + + +def test_parse_native_representation() -> None: + # Case: unsupported driver specified. + with pytest.raises(SystemConfigurationException): + resolve_configuration( + SynapseCredentials( + "synapse://test_user:test_pwd@test.sql.azuresynapse.net/test_db?DRIVER=ODBC+Driver+17+for+SQL+Server" + ) + ) + + +def test_to_odbc_dsn_longasmax() -> None: + # Case: LONGASMAX not specified in query (this is the expected scenario). + creds = resolve_configuration( + SynapseCredentials( + "synapse://test_user:test_pwd@test.sql.azuresynapse.net/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server" + ) + ) + dsn = creds.to_odbc_dsn() + result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} + assert result["LONGASMAX"] == "yes" + + # Case: LONGASMAX specified in query; specified value should be overridden. + creds = resolve_configuration( + SynapseCredentials( + "synapse://test_user:test_pwd@test.sql.azuresynapse.net/test_db?DRIVER=ODBC+Driver+18+for+SQL+Server&LONGASMAX=no" + ) + ) + dsn = creds.to_odbc_dsn() + result = {k: v for k, v in (param.split("=") for param in dsn.split(";"))} + assert result["LONGASMAX"] == "yes" diff --git a/tests/load/synapse/test_synapse_table_builder.py b/tests/load/synapse/test_synapse_table_builder.py new file mode 100644 index 0000000000..4719a8d003 --- /dev/null +++ b/tests/load/synapse/test_synapse_table_builder.py @@ -0,0 +1,137 @@ +import os +import pytest +import sqlfluff +from copy import deepcopy +from sqlfluff.api.simple import APIParsingError + +from dlt.common.utils import uniq_id +from dlt.common.schema import Schema, TColumnHint + +from dlt.destinations.impl.synapse.synapse import SynapseClient +from dlt.destinations.impl.synapse.configuration import ( + SynapseClientConfiguration, + SynapseCredentials, +) + +from tests.load.utils import TABLE_UPDATE +from dlt.destinations.impl.synapse.synapse import ( + HINT_TO_SYNAPSE_ATTR, + TABLE_INDEX_TYPE_TO_SYNAPSE_ATTR, +) + + +@pytest.fixture +def schema() -> Schema: + return Schema("event") + + +@pytest.fixture +def client(schema: Schema) -> SynapseClient: + # return client without opening connection + client = SynapseClient( + schema, + SynapseClientConfiguration( + dataset_name="test_" + uniq_id(), credentials=SynapseCredentials() + ), + ) + assert client.config.create_indexes is False + return client + + +@pytest.fixture +def client_with_indexes_enabled(schema: Schema) -> SynapseClient: + # return client without opening connection + client = SynapseClient( + schema, + SynapseClientConfiguration( + dataset_name="test_" + uniq_id(), credentials=SynapseCredentials(), create_indexes=True + ), + ) + assert client.config.create_indexes is True + return client + + +def test_create_table(client: SynapseClient) -> None: + # non existing table + sql = client._get_table_update_sql("event_test_table", TABLE_UPDATE, False)[0] + sqlfluff.parse(sql, dialect="tsql") + assert "event_test_table" in sql + assert '"col1" bigint NOT NULL' in sql + assert '"col2" float NOT NULL' in sql + assert '"col3" bit NOT NULL' in sql + assert '"col4" datetimeoffset NOT NULL' in sql + assert '"col5" nvarchar(max) NOT NULL' in sql + assert '"col6" decimal(38,9) NOT NULL' in sql + assert '"col7" varbinary(max) NOT NULL' in sql + assert '"col8" decimal(38,0)' in sql + assert '"col9" nvarchar(max) NOT NULL' in sql + assert '"col10" date NOT NULL' in sql + assert '"col11" time NOT NULL' in sql + assert '"col1_precision" smallint NOT NULL' in sql + assert '"col4_precision" datetimeoffset(3) NOT NULL' in sql + assert '"col5_precision" nvarchar(25)' in sql + assert '"col6_precision" decimal(6,2) NOT NULL' in sql + assert '"col7_precision" varbinary(19)' in sql + assert '"col11_precision" time(3) NOT NULL' in sql + table_index_type = client.config.default_table_index_type + table_index_type_attr = TABLE_INDEX_TYPE_TO_SYNAPSE_ATTR[table_index_type] + assert f"WITH ( {table_index_type_attr} )" in sql + + +def test_alter_table(client: SynapseClient) -> None: + # existing table has no columns + sql = client._get_table_update_sql("event_test_table", TABLE_UPDATE, True)[0] + sqlfluff.parse(sql, dialect="tsql") + canonical_name = client.sql_client.make_qualified_table_name("event_test_table") + assert sql.count(f"ALTER TABLE {canonical_name}\nADD") == 1 + assert "event_test_table" in sql + assert '"col1" bigint NOT NULL' in sql + assert '"col2" float NOT NULL' in sql + assert '"col3" bit NOT NULL' in sql + assert '"col4" datetimeoffset NOT NULL' in sql + assert '"col5" nvarchar(max) NOT NULL' in sql + assert '"col6" decimal(38,9) NOT NULL' in sql + assert '"col7" varbinary(max) NOT NULL' in sql + assert '"col8" decimal(38,0)' in sql + assert '"col9" nvarchar(max) NOT NULL' in sql + assert '"col10" date NOT NULL' in sql + assert '"col11" time NOT NULL' in sql + assert '"col1_precision" smallint NOT NULL' in sql + assert '"col4_precision" datetimeoffset(3) NOT NULL' in sql + assert '"col5_precision" nvarchar(25)' in sql + assert '"col6_precision" decimal(6,2) NOT NULL' in sql + assert '"col7_precision" varbinary(19)' in sql + assert '"col11_precision" time(3) NOT NULL' in sql + table_index_type = client.config.default_table_index_type + table_index_type_attr = TABLE_INDEX_TYPE_TO_SYNAPSE_ATTR[table_index_type] + assert f"WITH ( {table_index_type_attr} )" not in sql + + +@pytest.mark.parametrize("hint", ["primary_key", "unique"]) +def test_create_table_with_column_hint( + client: SynapseClient, client_with_indexes_enabled: SynapseClient, hint: TColumnHint +) -> None: + attr = HINT_TO_SYNAPSE_ATTR[hint] + + # Case: table without hint. + sql = client._get_table_update_sql("event_test_table", TABLE_UPDATE, False)[0] + sqlfluff.parse(sql, dialect="tsql") + assert f" {attr} " not in sql + + # Case: table with hint, but client does not have indexes enabled. + mod_update = deepcopy(TABLE_UPDATE) + mod_update[0][hint] = True # type: ignore[typeddict-unknown-key] + sql = client._get_table_update_sql("event_test_table", mod_update, False)[0] + sqlfluff.parse(sql, dialect="tsql") + assert f" {attr} " not in sql + + # Case: table with hint, client has indexes enabled. + sql = client_with_indexes_enabled._get_table_update_sql("event_test_table", mod_update, False)[ + 0 + ] + # We expect an error because "PRIMARY KEY NONCLUSTERED NOT ENFORCED" and + # "UNIQUE NOT ENFORCED" are invalid in the generic "tsql" dialect. + # They are however valid in the Synapse variant of the dialect. + with pytest.raises(APIParsingError): + sqlfluff.parse(sql, dialect="tsql") + assert f'"col1" bigint {attr} NOT NULL' in sql diff --git a/tests/load/synapse/test_synapse_table_indexing.py b/tests/load/synapse/test_synapse_table_indexing.py new file mode 100644 index 0000000000..df90933de4 --- /dev/null +++ b/tests/load/synapse/test_synapse_table_indexing.py @@ -0,0 +1,148 @@ +import os +import pytest +from typing import Iterator, List, Any, Union +from textwrap import dedent + +import dlt +from dlt.common.schema import TColumnSchema + +from dlt.destinations.sql_client import SqlClientBase + +from dlt.destinations.impl.synapse import synapse_adapter +from dlt.destinations.impl.synapse.synapse_adapter import TTableIndexType + +from tests.load.utils import TABLE_UPDATE, TABLE_ROW_ALL_DATA_TYPES +from tests.load.pipeline.utils import ( + drop_pipeline, +) # this import ensures all test data gets removed +from tests.load.synapse.utils import get_storage_table_index_type + + +TABLE_INDEX_TYPE_COLUMN_SCHEMA_PARAM_GRID = [ + ("heap", None), + # For "clustered_columnstore_index" tables, different code paths exist + # when no column schema is specified versus when a column schema is + # specified, so we test both. + ("clustered_columnstore_index", None), + ("clustered_columnstore_index", TABLE_UPDATE), +] + + +@pytest.mark.parametrize( + "table_index_type,column_schema", TABLE_INDEX_TYPE_COLUMN_SCHEMA_PARAM_GRID +) +def test_default_table_index_type_configuration( + table_index_type: TTableIndexType, + column_schema: Union[List[TColumnSchema], None], +) -> None: + # Configure default_table_index_type. + os.environ["DESTINATION__SYNAPSE__DEFAULT_TABLE_INDEX_TYPE"] = table_index_type + + @dlt.resource( + name="items_without_table_index_type_specified", + write_disposition="append", + columns=column_schema, + ) + def items_without_table_index_type_specified() -> Iterator[Any]: + yield TABLE_ROW_ALL_DATA_TYPES + + pipeline = dlt.pipeline( + pipeline_name=f"test_default_table_index_type_{table_index_type}", + destination="synapse", + dataset_name=f"test_default_table_index_type_{table_index_type}", + full_refresh=True, + ) + + job_client = pipeline.destination_client() + # Assert configuration value gets properly propagated to job client configuration. + assert job_client.config.default_table_index_type == table_index_type # type: ignore[attr-defined] + + # Run the pipeline and create the tables. + pipeline.run(items_without_table_index_type_specified) + + # For all tables, assert the applied index type equals the expected index type. + # Child tables, if any, inherit the index type of their parent. + tables = pipeline.default_schema.tables + for table_name in tables: + applied_table_index_type = get_storage_table_index_type(job_client.sql_client, table_name) # type: ignore[attr-defined] + if table_name in pipeline.default_schema.data_table_names(): + # For data tables, the applied table index type should be the default value. + assert applied_table_index_type == job_client.config.default_table_index_type # type: ignore[attr-defined] + elif table_name in pipeline.default_schema.dlt_table_names(): + # For dlt tables, the applied table index type should always be "heap". + assert applied_table_index_type == "heap" + + # Test overriding the default_table_index_type from a resource configuration. + if job_client.config.default_table_index_type == "heap": # type: ignore[attr-defined] + + @dlt.resource( + name="items_with_table_index_type_specified", + write_disposition="append", + columns=column_schema, + ) + def items_with_table_index_type_specified() -> Iterator[Any]: + yield TABLE_ROW_ALL_DATA_TYPES + + pipeline.run( + synapse_adapter(items_with_table_index_type_specified, "clustered_columnstore_index") + ) + applied_table_index_type = get_storage_table_index_type( + job_client.sql_client, # type: ignore[attr-defined] + "items_with_table_index_type_specified", + ) + # While the default is "heap", the applied index type should be "clustered_columnstore_index" + # because it was provided as argument to the resource. + assert applied_table_index_type == "clustered_columnstore_index" + + +@pytest.mark.parametrize( + "table_index_type,column_schema", TABLE_INDEX_TYPE_COLUMN_SCHEMA_PARAM_GRID +) +@pytest.mark.parametrize( + # Also test staging replace strategies, to make sure the final table index + # type is not affected by staging table index type adjustments. + "replace_strategy", + ["insert-from-staging", "staging-optimized"], +) +def test_resource_table_index_type_configuration( + table_index_type: TTableIndexType, + column_schema: Union[List[TColumnSchema], None], + replace_strategy: str, +) -> None: + os.environ["DESTINATION__REPLACE_STRATEGY"] = replace_strategy + + @dlt.resource( + name="items_with_table_index_type_specified", + write_disposition="replace", + columns=column_schema, + ) + def items_with_table_index_type_specified() -> Iterator[Any]: + yield TABLE_ROW_ALL_DATA_TYPES + + pipeline = dlt.pipeline( + pipeline_name=f"test_table_index_type_{table_index_type}", + destination="synapse", + dataset_name=f"test_table_index_type_{table_index_type}", + full_refresh=True, + ) + + # An invalid value for `table_index_type` should raise a ValueError. + with pytest.raises(ValueError): + pipeline.run(synapse_adapter(items_with_table_index_type_specified, "foo")) # type: ignore[arg-type] + + # Run the pipeline and create the tables. + pipeline.run(synapse_adapter(items_with_table_index_type_specified, table_index_type)) + + # For all tables, assert the applied index type equals the expected index type. + # Child tables, if any, inherit the index type of their parent. + job_client = pipeline.destination_client() + tables = pipeline.default_schema.tables + for table_name in tables: + applied_table_index_type = get_storage_table_index_type(job_client.sql_client, table_name) # type: ignore[attr-defined] + if table_name in pipeline.default_schema.data_table_names(): + # For data tables, the applied table index type should be the type + # configured in the resource. + assert applied_table_index_type == table_index_type + elif table_name in pipeline.default_schema.dlt_table_names(): + # For dlt tables, the applied table index type should always be "heap". + assert applied_table_index_type == "heap" diff --git a/tests/load/synapse/utils.py b/tests/load/synapse/utils.py new file mode 100644 index 0000000000..cd53716878 --- /dev/null +++ b/tests/load/synapse/utils.py @@ -0,0 +1,24 @@ +from typing import cast +from textwrap import dedent + +from dlt.destinations.impl.synapse.sql_client import SynapseSqlClient +from dlt.destinations.impl.synapse.synapse_adapter import TTableIndexType + + +def get_storage_table_index_type(sql_client: SynapseSqlClient, table_name: str) -> TTableIndexType: + """Returns table index type of table in storage destination.""" + with sql_client: + schema_name = sql_client.fully_qualified_dataset_name(escape=False) + sql = dedent(f""" + SELECT + CASE i.type_desc + WHEN 'HEAP' THEN 'heap' + WHEN 'CLUSTERED COLUMNSTORE' THEN 'clustered_columnstore_index' + END AS table_index_type + FROM sys.indexes i + INNER JOIN sys.tables t ON t.object_id = i.object_id + INNER JOIN sys.schemas s ON s.schema_id = t.schema_id + WHERE s.name = '{schema_name}' AND t.name = '{table_name}' + """) + table_index_type = sql_client.execute_sql(sql)[0][0] + return cast(TTableIndexType, table_index_type) diff --git a/tests/load/test_job_client.py b/tests/load/test_job_client.py index 153504bf4a..63f9d3c28d 100644 --- a/tests/load/test_job_client.py +++ b/tests/load/test_job_client.py @@ -28,13 +28,13 @@ from dlt.destinations.job_client_impl import SqlJobClientBase from dlt.common.destination.reference import WithStagingDataset +from tests.cases import table_update_and_row, assert_all_data_types_row from tests.utils import TEST_STORAGE_ROOT, autouse_test_storage from tests.common.utils import load_json_case from tests.load.utils import ( TABLE_UPDATE, TABLE_UPDATE_COLUMNS_SCHEMA, TABLE_ROW_ALL_DATA_TYPES, - assert_all_data_types_row, expect_load_file, load_table, yield_client_with_storage, @@ -387,7 +387,10 @@ def test_get_storage_table_with_all_types(client: SqlJobClientBase) -> None: "time", ): continue - if client.config.destination_type == "mssql" and c["data_type"] in ("complex"): + # mssql and synapse have no native data type for the complex type. + if client.config.destination_type in ("mssql", "synapse") and c["data_type"] in ("complex"): + continue + if client.config.destination_type == "databricks" and c["data_type"] in ("complex", "time"): continue assert c["data_type"] == expected_c["data_type"] @@ -502,9 +505,14 @@ def test_load_with_all_types( if not client.capabilities.preferred_loader_file_format: pytest.skip("preferred loader file format not set, destination will only work with staging") table_name = "event_test_table" + uniq_id() + column_schemas, data_types = table_update_and_row( + exclude_types=["time"] if client.config.destination_type == "databricks" else None, + ) # we should have identical content with all disposition types client.schema.update_table( - new_table(table_name, write_disposition=write_disposition, columns=TABLE_UPDATE) + new_table( + table_name, write_disposition=write_disposition, columns=list(column_schemas.values()) + ) ) client.schema.bump_version() client.update_stored_schema() @@ -521,12 +529,12 @@ def test_load_with_all_types( canonical_name = client.sql_client.make_qualified_table_name(table_name) # write row with io.BytesIO() as f: - write_dataset(client, f, [TABLE_ROW_ALL_DATA_TYPES], TABLE_UPDATE_COLUMNS_SCHEMA) + write_dataset(client, f, [data_types], column_schemas) query = f.getvalue().decode() expect_load_file(client, file_storage, query, table_name) db_row = list(client.sql_client.execute_sql(f"SELECT * FROM {canonical_name}")[0]) # content must equal - assert_all_data_types_row(db_row) + assert_all_data_types_row(db_row, schema=column_schemas) @pytest.mark.parametrize( diff --git a/tests/load/test_sql_client.py b/tests/load/test_sql_client.py index 96f0db09bb..026e481ede 100644 --- a/tests/load/test_sql_client.py +++ b/tests/load/test_sql_client.py @@ -38,7 +38,7 @@ def client(request) -> Iterator[SqlJobClientBase]: @pytest.mark.parametrize( "client", - destinations_configs(default_sql_configs=True, exclude=["mssql"]), + destinations_configs(default_sql_configs=True, exclude=["mssql", "synapse"]), indirect=True, ids=lambda x: x.name, ) @@ -263,9 +263,15 @@ def test_execute_df(client: SqlJobClientBase) -> None: client.update_stored_schema() table_name = prepare_temp_table(client) f_q_table_name = client.sql_client.make_qualified_table_name(table_name) - insert_query = ",".join([f"({idx})" for idx in range(0, total_records)]) - client.sql_client.execute_sql(f"INSERT INTO {f_q_table_name} VALUES {insert_query};") + if client.capabilities.insert_values_writer_type == "default": + insert_query = ",".join([f"({idx})" for idx in range(0, total_records)]) + sql_stmt = f"INSERT INTO {f_q_table_name} VALUES {insert_query};" + elif client.capabilities.insert_values_writer_type == "select_union": + insert_query = " UNION ALL ".join([f"SELECT {idx}" for idx in range(0, total_records)]) + sql_stmt = f"INSERT INTO {f_q_table_name} {insert_query};" + + client.sql_client.execute_sql(sql_stmt) with client.sql_client.execute_query( f"SELECT * FROM {f_q_table_name} ORDER BY col ASC" ) as curr: @@ -311,16 +317,17 @@ def test_database_exceptions(client: SqlJobClientBase) -> None: pass assert client.sql_client.is_dbapi_exception(term_ex.value.dbapi_exception) with pytest.raises(DatabaseUndefinedRelation) as term_ex: - with client.sql_client.execute_query( - "DELETE FROM TABLE_XXX WHERE 1=1;DELETE FROM ticket_forms__ticket_field_ids WHERE 1=1;" - ): - pass + client.sql_client.execute_many( + [ + "DELETE FROM TABLE_XXX WHERE 1=1;", + "DELETE FROM ticket_forms__ticket_field_ids WHERE 1=1;", + ] + ) assert client.sql_client.is_dbapi_exception(term_ex.value.dbapi_exception) with pytest.raises(DatabaseUndefinedRelation) as term_ex: - with client.sql_client.execute_query( - "DROP TABLE TABLE_XXX;DROP TABLE ticket_forms__ticket_field_ids;" - ): - pass + client.sql_client.execute_many( + ["DROP TABLE TABLE_XXX;", "DROP TABLE ticket_forms__ticket_field_ids;"] + ) # invalid syntax with pytest.raises(DatabaseTransientException) as term_ex: @@ -360,7 +367,10 @@ def test_database_exceptions(client: SqlJobClientBase) -> None: @pytest.mark.parametrize( - "client", destinations_configs(default_sql_configs=True), indirect=True, ids=lambda x: x.name + "client", + destinations_configs(default_sql_configs=True, exclude=["databricks"]), + indirect=True, + ids=lambda x: x.name, ) def test_commit_transaction(client: SqlJobClientBase) -> None: table_name = prepare_temp_table(client) @@ -391,7 +401,10 @@ def test_commit_transaction(client: SqlJobClientBase) -> None: @pytest.mark.parametrize( - "client", destinations_configs(default_sql_configs=True), indirect=True, ids=lambda x: x.name + "client", + destinations_configs(default_sql_configs=True, exclude=["databricks"]), + indirect=True, + ids=lambda x: x.name, ) def test_rollback_transaction(client: SqlJobClientBase) -> None: if client.capabilities.supports_transactions is False: @@ -449,7 +462,10 @@ def test_rollback_transaction(client: SqlJobClientBase) -> None: @pytest.mark.parametrize( - "client", destinations_configs(default_sql_configs=True), indirect=True, ids=lambda x: x.name + "client", + destinations_configs(default_sql_configs=True, exclude=["databricks"]), + indirect=True, + ids=lambda x: x.name, ) def test_transaction_isolation(client: SqlJobClientBase) -> None: if client.capabilities.supports_transactions is False: @@ -546,7 +562,10 @@ def test_max_column_identifier_length(client: SqlJobClientBase) -> None: @pytest.mark.parametrize( - "client", destinations_configs(default_sql_configs=True), indirect=True, ids=lambda x: x.name + "client", + destinations_configs(default_sql_configs=True, exclude=["databricks"]), + indirect=True, + ids=lambda x: x.name, ) def test_recover_on_explicit_tx(client: SqlJobClientBase) -> None: if client.capabilities.supports_transactions is False: @@ -567,7 +586,7 @@ def test_recover_on_explicit_tx(client: SqlJobClientBase) -> None: # syntax error within tx statements = ["BEGIN TRANSACTION;", f"INVERT INTO {version_table} VALUES(1);", "COMMIT;"] with pytest.raises(DatabaseTransientException): - client.sql_client.execute_fragments(statements) + client.sql_client.execute_many(statements) # assert derives_from_class_of_name(term_ex.value.dbapi_exception, "ProgrammingError") assert client.get_stored_schema() is not None client.complete_load("EFG") @@ -581,7 +600,7 @@ def test_recover_on_explicit_tx(client: SqlJobClientBase) -> None: ] # cannot insert NULL value with pytest.raises(DatabaseTerminalException): - client.sql_client.execute_fragments(statements) + client.sql_client.execute_many(statements) # assert derives_from_class_of_name(term_ex.value.dbapi_exception, "IntegrityError") # assert isinstance(term_ex.value.dbapi_exception, (psycopg2.InternalError, psycopg2.)) assert client.get_stored_schema() is not None diff --git a/tests/load/utils.py b/tests/load/utils.py index 30b866521d..c14387b024 100644 --- a/tests/load/utils.py +++ b/tests/load/utils.py @@ -97,10 +97,12 @@ class DestinationTestConfiguration: bucket_url: Optional[str] = None stage_name: Optional[str] = None staging_iam_role: Optional[str] = None + staging_use_msi: bool = False extra_info: Optional[str] = None supports_merge: bool = True # TODO: take it from client base class force_iceberg: bool = False supports_dbt: bool = True + disable_compression: bool = False @property def name(self) -> str: @@ -120,10 +122,11 @@ def setup(self) -> None: os.environ["DESTINATION__FILESYSTEM__BUCKET_URL"] = self.bucket_url or "" os.environ["DESTINATION__STAGE_NAME"] = self.stage_name or "" os.environ["DESTINATION__STAGING_IAM_ROLE"] = self.staging_iam_role or "" + os.environ["DESTINATION__STAGING_USE_MSI"] = str(self.staging_use_msi) or "" os.environ["DESTINATION__FORCE_ICEBERG"] = str(self.force_iceberg) or "" """For the filesystem destinations we disable compression to make analyzing the result easier""" - if self.destination == "filesystem": + if self.destination == "filesystem" or self.disable_compression: os.environ["DATA_WRITER__DISABLE_COMPRESSION"] = "True" def setup_pipeline( @@ -152,6 +155,7 @@ def destinations_configs( subset: Sequence[str] = (), exclude: Sequence[str] = (), file_format: Optional[TLoaderFileFormat] = None, + supports_dbt: Optional[bool] = None, ) -> List[DestinationTestConfiguration]: # sanity check for item in subset: @@ -165,7 +169,7 @@ def destinations_configs( destination_configs += [ DestinationTestConfiguration(destination=destination) for destination in SQL_DESTINATIONS - if destination != "athena" + if destination not in ("athena", "mssql", "synapse") ] destination_configs += [ DestinationTestConfiguration(destination="duckdb", file_format="parquet") @@ -192,6 +196,10 @@ def destinations_configs( extra_info="iceberg", ) ] + destination_configs += [ + DestinationTestConfiguration(destination="mssql", supports_dbt=False), + DestinationTestConfiguration(destination="synapse", supports_dbt=False), + ] if default_vector_configs: # for now only weaviate @@ -252,6 +260,36 @@ def destinations_configs( bucket_url=AZ_BUCKET, extra_info="az-authorization", ), + DestinationTestConfiguration( + destination="databricks", + staging="filesystem", + file_format="jsonl", + bucket_url=AWS_BUCKET, + extra_info="s3-authorization", + disable_compression=True, + ), + DestinationTestConfiguration( + destination="databricks", + staging="filesystem", + file_format="jsonl", + bucket_url=AZ_BUCKET, + extra_info="s3-authorization", + disable_compression=True, + ), + DestinationTestConfiguration( + destination="databricks", + staging="filesystem", + file_format="parquet", + bucket_url=AWS_BUCKET, + extra_info="s3-authorization", + ), + DestinationTestConfiguration( + destination="synapse", + staging="filesystem", + file_format="parquet", + bucket_url=AZ_BUCKET, + extra_info="az-authorization", + ), ] if all_staging_configs: @@ -284,6 +322,14 @@ def destinations_configs( bucket_url=GCS_BUCKET, extra_info="gcs-authorization", ), + DestinationTestConfiguration( + destination="synapse", + staging="filesystem", + file_format="parquet", + bucket_url=AZ_BUCKET, + staging_use_msi=True, + extra_info="az-managed-identity", + ), ] # add local filesystem destinations if requested @@ -328,6 +374,10 @@ def destinations_configs( destination_configs = [ conf for conf in destination_configs if conf.file_format == file_format ] + if supports_dbt is not None: + destination_configs = [ + conf for conf in destination_configs if conf.supports_dbt == supports_dbt + ] # filter out excluded configs destination_configs = [ @@ -467,7 +517,6 @@ def yield_client_with_storage( ) as client: client.initialize_storage() yield client - # print(dataset_name) client.sql_client.drop_dataset() if isinstance(client, WithStagingDataset): with client.with_staging_dataset(): diff --git a/tests/utils.py b/tests/utils.py index cf172f9733..1d2ace2533 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -45,6 +45,8 @@ "motherduck", "mssql", "qdrant", + "synapse", + "databricks", } NON_SQL_DESTINATIONS = {"filesystem", "weaviate", "dummy", "motherduck", "qdrant"} SQL_DESTINATIONS = IMPLEMENTED_DESTINATIONS - NON_SQL_DESTINATIONS