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+ +--- +## ***"We* ♡ *your feedback!"*** +![DAP⇨flow](../images/DAPairflowFLOWleft.png) +:::tip UX +👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-access**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-access) +- Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. +- We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. +- We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. +☝ **Please use this link to help us understand your user experience!** +::: + +#### UX Criteria +:::info ABILITY +* Hackney **Google Workspace** user +* `[my service]` Data Analyst +* **Github** beginner +::: + +:::note BEHAVIOR +**Measures** the **DAP Platform Team** behavior: + +**Given** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space + +**When** I create my **GitHub** account at [github.com](https://github.com/) using my Hackney email address +**~and** I set up 2 factor authentication for my **GitHub** account +**~and** I request access to the `dap-airflow` private repository via the [☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7) + + +**Then** the **DAP Platform Team** will acknowledge my request via a reply-thread on the [☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7) +**~and** ensure I am granted membership of [London Borough of Hackney](https://github.com/LBHackney-IT) organization on GitHub +**~and** ensure I can subsequently access the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** confirm `[my service dags]` GitHub project folder with link to the `README.md` there +**~and** tell me my `dap-airflow` access is now configured while directing me back to the [**📚Onboarding** documentation](../introduction#github-branching). + +**Scale** of 5 **~and** flow features. +::: diff --git a/sidebars.js b/sidebars.js index 7d02f0e6..d8946ad8 100644 --- a/sidebars.js +++ b/sidebars.js @@ -136,6 +136,7 @@ module.exports = { "dap-airflow/onboarding/query-my-service-data", "dap-airflow/onboarding/prototype-simple-transforms", "dap-airflow/onboarding/prototype-legacy-transforms", + "dap-airflow/onboarding/github-access", ], }, ], From 92151a24e74dacde90ce55a5529639bf0ab61b64 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Thu, 22 Aug 2024 20:46:45 +0100 Subject: [PATCH 03/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20access?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/introduction.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index 1653b70b..171b118d 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -70,11 +70,11 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### [Prototype legacy transforms](../dap-airflow/onboarding/prototype-legacy-transforms) #### How do I use Amazon Athena to prototype a data transformation from a `[legacy SQL query]`? -## Topics arriving here soon... - ### [GitHub access](../dap-airflow/onboarding/github-access) #### How do I set up my GitHub access to **DAP⇨flow**? +## Topics arriving here soon... + ### Github branching #### How do I add a new development branch to **DAP⇨flow**'s `[dap-airflow]` repository? [DPF-185 DOCUMENTATION / 4.1 Add a new development branch to the DAP Airflow repository ](https://docs.google.com/document/d/1g6s14JK-9LBM8HT-F6-T-rGq7TxnWHD37FJi04Fh41Q/edit?usp=drive\_link) From 974dd41c21672420f37a75633cfcc44ec7dc130d Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 23 Aug 2024 17:34:07 +0100 Subject: [PATCH 04/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20branching?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/images/branch.png | Bin 0 -> 26180 bytes .../dap-airflow/images/github-branch-four.png | Bin 0 -> 16842 bytes .../images/github-branch-three.png | Bin 0 -> 50990 bytes docs/dap-airflow/introduction.md | 12 ++- docs/dap-airflow/onboarding/github-access.md | 22 ++--- docs/dap-airflow/onboarding/github-branch.md | 78 ++++++++++++++++++ sidebars.js | 1 + 7 files changed, 95 insertions(+), 18 deletions(-) create mode 100644 docs/dap-airflow/images/branch.png create mode 100644 docs/dap-airflow/images/github-branch-four.png create mode 100644 docs/dap-airflow/images/github-branch-three.png create mode 100644 docs/dap-airflow/onboarding/github-branch.md diff --git a/docs/dap-airflow/images/branch.png b/docs/dap-airflow/images/branch.png new file mode 100644 index 0000000000000000000000000000000000000000..05cfdd54f92353de0a54535b4f013c02691abc42 GIT binary patch literal 26180 zcmeFZc{G*Z`!IYT^KftsnUWk4GEbpQIVw^3Xd*+7Qlg9vrZ~kphBB0S9zK*JLn&mQ zB|-y2Byv;~9f^qdx{to^_w#+$^LyUsS?gKr{pV+`R_DI&y{~y+``XvF_l~eM-_OM% z%7GvV*8vk_D+FQYf`2Y-EbxZCcG(mDWAZUNaD)y10@+T7!!yRmYQGUu{6g##`tj_Z zLwgXUEQWKH$c*;!G_mnP5J745ALf9S)Et61KRaN&=ZLSv%)8*C3my)=SH5DkB^b{+ zrykpZ;}Del=zg$IAhL{QZ@x?L>EV7yE51H8vVfV}`Jr@;?h8YFHzMVZ;W(c3mN{Qi z_&b;F$9|@j5I)_3P(h}Mkn1lb-p?_!P*OYwo>FzjzS;l$THE8`rq}Z*b8E?Q?}z>R z!3}}mYyxI`f=bTL{sv0_|M@HWE_)vH(D#zSqWyGSB?-j_DFb?5M?;KfMY9>mSRAV-pwANm}{QQcwPh{CHlSM+%hE3r+@XA#!NnK zX?~(KDJh%{X`p#`jhwNRkd_giHvXI=y&rc|`jWLq4F)Nf-;cf79mr8M-hzoT)$DpL zz?x*biJ$8nf?T?%iY<0N#{9y|o7C1K>UknM#H=+kf<+A>JzRihDisX;G7K(;H;MbD zY8-BcyWkj+4ht!}o>h+D^Lb&W7q<8sH~BuWk$YZ9Yf{@nAqt_90EOOpzV zJTKyJ+!Xi(>p@XQNI$%dn?$Lf#k~5&IA`bcC>%vwfxhC#i;nS&b7jcRrMa#Wm%D=h?s^wEiI2m`w$De02Bjqk` zvKq?N3QfsWx158S$)$19&9RMl4a``S34%!Pb;YvY8oOvkOrIU6^L%J%SBp_1jt4_Z zWG7$X$K|+ZhQ=OAmRVHsg65Qt&p_T2|o6*+YgJ!$v`w7h_G_%1ZmSD_^T%zg5@P{*Ik1wFW4barppc zru`)fB~bUR#5K3D+}mL}4wB=VrVa_dv$4*V49KE{;KNYP2}?l>weW%|Ygs;rl9q5; zaRwwG$MLrFGeI^)M$p*ul!5^JgfL}X$iu_KKwEbt!4xg+`Z->6qx`KGCK+O}yeQUEEK-a;iZn=Twi`YA?yYHTEYyMDVj)^-b+55^?r@17 zMP(d^SbrIEv^G`HkZC{eYAnEw=duv?C0U!eqQZKZ>Xaj*lf}oF>&xclm)pS1!)4-x zS4|M+;W~o!mYi_PS@sRiX9oFym}9!8ZpulaD$FCviZ|`d z6rQ{8M#-~dyiE+ZBP4mUAqP#lDQ6~r#p7^ff^|b>5$6B z3NE+VEjW9ru#dWU30b_bXr!-6H1WA1Gjf%e^VtF2P=8;^-daA26oJRR}@aYvGSL{uEv+^E+$lQ(c48zd8eg|c4-{M7-qB>nUz=iU2iOJi&zdl=Fn$J5#rVUzrFGCJ(omZtQO40l}(*?h6vSd+;_?*{Kpg2?BG zS5!1OA00h6-&+;dNuZ|gnr2rE)FFigYDvt zz1V~2yjuw4v6)9324TGJ!D4*^+6n5)4?HDaVVn7iwgL3ot_IIkPqty5 z@N-5lh|jW(3!Qk5QDhMl>dV#LyjbG8r?%=(D|J@oH~d(JGL55_ulUHd$OIQue?1^{T7C)?dx{P`T;>-ZV@DcZycZSiH=HspQuvd{<9W!=h! 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+ +--- +## ***"We* ♡ *your feedback!"*** +![DAP⇨flow](../images/DAPairflowFLOWleft.png) +:::tip UX +👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-branch**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-branch) +- Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. +- We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. +- We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. +☝ **Please use this link to help us understand your user experience!** +::: + +#### UX Criteria +:::info ABILITY +* Hackney **Google Workspace** user +* `[my service]` Data Analyst +* ***GitHub*** beginner +::: + +:::note BEHAVIOR +**Measures** the ***GitHub*** behavior: + +**Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication +**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorperating the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space + +**When** I access the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) repository +**~and** I select the "**Code**" tab at the top of the repository page +**~and** below that, I click on the "**![][branch]`main`**" branch dropdown button menu +**~and** type a new branch name, eg. **`[my branch]`**, +**~and** click "Create branch **![][branch]`[my branch]`** from **`main`**" below that on the dropdown menu + +**Then** "**![][branch]`[my branch]`**” should replace "**![][branch]`main`**" as my working branch for development +**~and** ***GitHub*** will alert me via email if there are errors or warnings +**~and** I will have information that I can pass to the **DAP Platform Team** via the **[☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7)** if I encounter errors or need assistance. + +**Scale** of 6 to 8 **~and** flow features. +::: + +[branch]: diff --git a/sidebars.js b/sidebars.js index d8946ad8..67acb3ac 100644 --- a/sidebars.js +++ b/sidebars.js @@ -137,6 +137,7 @@ module.exports = { "dap-airflow/onboarding/prototype-simple-transforms", "dap-airflow/onboarding/prototype-legacy-transforms", "dap-airflow/onboarding/github-access", + "dap-airflow/onboarding/github-branch", ], }, ], From 43bbc93a99252825cfefcbb85d35e7f35c19a7b8 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 23 Aug 2024 17:39:06 +0100 Subject: [PATCH 05/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20branching?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/onboarding/github-branch.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index 21b22b78..a24419b8 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -9,7 +9,7 @@ tags: [onboarding] # How do I add a new development branch to **DAP⇨flow**'s `[dap-airflow]` repository? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Log into your GitHub account +### 1. Log into your ***GitHub*** account **`🖱`** Open your web browser and log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. 👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** From ca07b7732b0118a1934a6b8098e15c3c608a18aa Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 23 Aug 2024 17:43:26 +0100 Subject: [PATCH 06/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20branching?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/introduction.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index 3ac80b02..8b76beb7 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -73,11 +73,11 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### [GitHub access](../dap-airflow/onboarding/github-access) #### How do I set up my GitHub access to **DAP⇨flow**? -## Topics arriving here soon... - ### [GitHub branching](../dap-airflow/onboarding/github-branch) #### How do I add a new development branch to the **DAP⇨flow** repository? +## Topics arriving here soon... + ### Committing transforms #### How do I commit my working transform query to the **DAP⇨flow** repository? [DPF-185 DOCUMENTATION / 4.2 Commit a working transform query to the DAP Airflow repository](https://docs.google.com/document/d/18TL2ep1laWzHU9MW-XvC\_N1S-gJx9SmPh9M2DC9XNQ4/edit?usp=drive\_link) From e93d9f254453acd9c883b4f8fa65f3057f1ffb7c Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 23 Aug 2024 17:54:07 +0100 Subject: [PATCH 07/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20branching?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/onboarding/github-branch.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index a24419b8..2ff03209 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -25,11 +25,11 @@ tags: [onboarding] **`🖱`** Below that, click on the "**![][branch]`main`**" branch dropdown button menu. -**`🖮`** Type a new branch name, for example, **`[my branch]`**. +**`🖮`** Type your new branch name **`[my branch]`** as your working branch for development. **`🖱`** Below that on the dropdown menu, click on "Create branch **![][branch]`[my branch]`** from **`main`.**" -### 4. Verify the new branch +### 4. Verify your new branch **`👁`** After creating the branch, "![][branch]`[my branch]`” should replace "![][branch]`main`" as your working branch for development. **`Fig. 4`** ![Fig. 4](../images/github-branch-four.png) @@ -60,19 +60,20 @@ tags: [onboarding] **Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication **~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorperating the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** I have decided what to call **`[my branch]`** as my working branch for development **~and** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space **When** I access the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) repository **~and** I select the "**Code**" tab at the top of the repository page **~and** below that, I click on the "**![][branch]`main`**" branch dropdown button menu -**~and** type a new branch name, eg. **`[my branch]`**, +**~and** type my new branch name **`[my branch]`** **~and** click "Create branch **![][branch]`[my branch]`** from **`main`**" below that on the dropdown menu **Then** "**![][branch]`[my branch]`**” should replace "**![][branch]`main`**" as my working branch for development **~and** ***GitHub*** will alert me via email if there are errors or warnings **~and** I will have information that I can pass to the **DAP Platform Team** via the **[☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7)** if I encounter errors or need assistance. -**Scale** of 6 to 8 **~and** flow features. +**Scale** of 6 to 9 **~and** flow features. ::: [branch]: From e994c7508d85d68611f3afeab6b7877e76ca44e2 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Tue, 27 Aug 2024 22:19:07 +0100 Subject: [PATCH 08/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20Committing=20transforms?= MIME-Version: 1.0 Content-Type: text/plain; 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zqex=p+TYmVhyQktR^&4K?;AcN|8rd^ixM#2F4p0pefx_gxJ)(xxCo@L1Jy3oyz%gV E0dnFw)Bpeg literal 0 HcmV?d00001 diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index 8b76beb7..55440c7a 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -12,19 +12,22 @@ tags: [dap-airflow] **DAP⇨flow** is an integation of ***Apache Airflow*** with ***Amazon Athena*** built upon Hackney's ***Data Analytics Platform***. #### It allows Data Analysts, in the simplest way possible, to develop and run data pipelines using their own service's data and create data products for their service and service users. -Building data pipelines used to be harder and more complex and time consuming. Data Analysts after prototyping their SQL queries using ***Amazon Athena*** were required to migrate Athena's SQL code to Spark SQL, a different SQL dialect, then embed their code within an ***Amazon Glue*** job. They also had to negotiate querying across multiple generations of the same data stored in the ***Amazon S3*** Data lake. That meant they could not simply take a legacy SQL query and run it in ***Amazon Athena*** or create an ***Amazon Glue*** product directly from it. +Building data pipelines used to be harder and more complex and time consuming. Data Analysts after prototyping their SQL queries using ***Amazon Athena*** were required to convert Athena SQL code to Spark SQL, a different SQL dialect, then embed their code within an ***Amazon Glue*** job which they had be deployed using ***Terraform***. + +They also had to negotiate querying across multiple generations of the same data stored in the ***Amazon S3*** Data lake. That meant they could not simply take a legacy SQL query and run it in ***Amazon Athena*** or create an ***Amazon Glue*** product directly from it. #### How **DAP⇨flow** solves these problems -* Firstly, Data Analysts no longer need to use the more complex ***Amazon Glue*** because data pipelines built using ***Apache Airflow*** can use ***Amazon Athena*** to generate the data transformation products using the same prototype SQL code. +* Firstly, Data Analysts no longer need to convert and re-test their prototype SQL transforms to run in a seperate and more complex ***Amazon Glue*** run-time environment. Instead, ***Apache Airflow*** uses ***Amazon Athena*** to automate and generate data transform products using the original, already tested and working, prototype SQL code. - **This cuts development time by more than half while Data Analysts no longer need to context-switch between the two SQL dialects.** + **That cuts development time by more than half while Data Analysts no longer need to context-switch between the two SQL dialects.** -* Secondly, Data Analysts no longer need to adapt their SQL queries to ***Amazon S3***'s Data Lake partitioning architecture, because ***Apache Airflow*** is used to generate views of the underlying table data which presents Data Analysts with only current ingested service data, in readiness for prototyping and also later on when the automated transforms are run by Airflow. +* Secondly, Data Analysts no longer must adapt their SQL queries to ***Amazon S3***'s Data Lake partitioning architecture, because ***Apache Airflow*** is configured to generate views of the underlying table data to present Data Analysts with current-only ingested service data, both in readiness for prototyping and testing, and for when the working transforms are subsequently deployed, being automated and run by Airflow. - **This further cuts development time while Data Analysts can very easily take the legacy SQL code from their service database system and run it directly on *Amazon Athena* with few changes.** + **That further cuts development time while Data Analysts can very easily take the legacy SQL code from their service database system and run it directly on *Amazon Athena* with few changes.** - Data Analysts can also migrate their existing Athena SQL prototypes, previously adapted for the ***Amazon S3***'s Data Lake partitioning architecture, because the table history is still available to them, although the table names will now be suffixed "**_history**". + Data Analysts can also migrate their existing Athena SQL prototypes, previously adapted for the ***Amazon S3***'s Data Lake partitioning architecture, because the same table history is available to them, although the table names will now be suffixed "**_history**", which is more intuitive for new users. +* Lastly, Data Analysts no longer need to use ***Terraform*** for deploying their data pipeline jobs because ***Apache Airflow*** simply takes care of that as soon as they commit their transform queries to **DAP⇨flow**'s ***GitHub*** repository. ## 📚Onboarding @@ -76,11 +79,10 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### [GitHub branching](../dap-airflow/onboarding/github-branch) #### How do I add a new development branch to the **DAP⇨flow** repository? -## Topics arriving here soon... +### [Committing transforms](../dap-airflow/onboarding/github-commit-transform) +#### How do I commit my working transform to the **DAP⇨flow** repository? -### Committing transforms -#### How do I commit my working transform query to the **DAP⇨flow** repository? -[DPF-185 DOCUMENTATION / 4.2 Commit a working transform query to the DAP Airflow repository](https://docs.google.com/document/d/18TL2ep1laWzHU9MW-XvC\_N1S-gJx9SmPh9M2DC9XNQ4/edit?usp=drive\_link) +## Topics arriving here soon... ### Raising pull requests #### How do I raise a Pull Request to merge my development branch into the main trunk of the **DAP⇨flow** repository? diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index 2ff03209..d4c01444 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -59,7 +59,7 @@ tags: [onboarding] **Measures** the ***GitHub*** behavior: **Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication -**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorperating the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorporating the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) private repository **~and** I have decided what to call **`[my branch]`** as my working branch for development **~and** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space diff --git a/docs/dap-airflow/onboarding/github-commit-transform.md b/docs/dap-airflow/onboarding/github-commit-transform.md new file mode 100644 index 00000000..eaacf1b3 --- /dev/null +++ b/docs/dap-airflow/onboarding/github-commit-transform.md @@ -0,0 +1,139 @@ +--- +id: github-commit-transform +title: Committing transforms +description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Analytics Platform Airflow integration." +layout: playbook_js +tags: [onboarding] +--- + +# How do I commit my working transform query to **DAP⇨flow**'s `[dap-airflow]` repository? +![DAP⇨flow](../images/DAPairflowFLOWleft.png) + +### 1. Access ***Amazon Athena*** and workgroup + +**`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. + +**`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. + +### 2. Prepare and make ready your SQL query +**`🖱`** Ensure you have already created, tested and saved your `[transform SQL]` as a working, fully functional Athena SQL query. + +👉 If you want reminding how to do any of that, see **here** or **here ►** +* **[DAP⇨flow📚Prototype simple transforms](../dap-airflow/onboarding/prototype-simple-transforms)** +* **[DAP⇨flow📚Prototype legacy transforms](../dap-airflow/onboarding/prototype-legacy-transforms)** + +**`🖱`** Open your `[transform SQL]` in the ***Amazon Athena*** query editor and keep it open in a web browser tab. + +### 3. Access the `dap-airflow` repository in ***GitHub*** + +**`🖱`** Use another tab in your web browser to log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. + +👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** + +**`🖱`** Open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. + +### 4. Open your `[service dags]/transformations` subfolder on a your `[transform branch]` + +**`🖱`** Ensure you have created your ![][branch]`[transform branch]` and have it selected. +**`Fig. 4`** ![Fig. 4a](../images/github-commit-transform-four-a.png) + +👉 For how to create a branch, **see here ►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** + +**`🖱`** In the DAP Airflow repository, navigate to your `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service sub-folder. You can use ***GitHub***’s left-hand navigation pane as follows: +* Click on the **`airflow`** folder +* Inside the `airflow` folder, click on the **`dags`** folder +* Inside the `dags` folder, click on your **`[service dags]`** folder +* Inside the `[service dags]` folder, click on the **`transformations`** subfolder + +**`Fig. 4b & 5a`** ![Fig. 4b & 5a](../images/github-commit-transform-four-b-five-a.png) + +### 5. Create your new `[transform].sql` file in ***GitHub*** + +**`🖱`** At the top right region of the page, click the "**Add file**" button and select "**Create new file**" + +**`🖮`** In the box following the **`transformations/`** subfolder, enter your `[transform].sql`. + +**`Fig. 5b`** ![Fig. 5b](../images/github-commit-transform-five-b.png) + +**`🖱`** Keep this ***Github*** code editor and it's web browser tab open for later on. + +### 6. Copy your `[transform SQL]` code from ***Amazon Athena*** +**`🖱`** Switch back to the ***Amazon Athena*** tab in your web browser, with your `[transform SQL]` still in the query editor. +**`🖱`** Select the entire code of `[transform SQL]` open in the Athena query editor. +**`Fig. 6`** ![Fig. 6](../images/github-commit-transform-six.png) +**`🖱`** Use the right-click menu to "*Copy*" the selected code to your computer’s clipboard. + +### 7. Paste your `[transform SQL]` code into ***GitHub*** +**`🖱`** Switch back to the ***GitHub*** tab in your web browser, with `[transform].sql` currently empty in the code editor. +**`🖱`** In the editor window beneath where it says “**Edit**”, use the right-click menu to "*Paste*" the entire `[transform SQL]` code from your computer’s clipboard. +**`Fig. 7 & 8`** ![Fig. 7 & 8](../images/github-commit-transform-seven-eight.png) + +### 8. Review and adjust your `[transform SQL]` code +**`🖱`** Scroll to the bottom of the editor window. +**`👁 🖱`** Check for and remove any `limit` clause (e.g., `limit 100`), leaving just the final **`;`** semi-colon at the very end. + +### 9. Commit your `[transform].sql` file +**`🖱`** Click the "**Commit changes**" button to open a dialogue box. +**`Fig. 9`** ![Fig. 9](../images/github-commit-transform-nine.png) +**`🖮`** Enter a short commit message, Eg. `Add ... [transform].sql`. +**`🖮`** Enter a longer description if wanted. +**`🖱`** Select the option “**Commit directly to the `[transform branch]`**”. +**`🖱`** Click the "**Commit changes**" button. + +### 10. Verify the Commit +**`👁`**You should see a message confirming your `[transform].sql` was successfully committed directly to your `[transform branch]`. + +
+
+ +--- +## ***"We* ♡ *your feedback!"*** +![DAP⇨flow](../images/DAPairflowFLOWleft.png) +:::tip UX +👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-commit-transform**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-commit-transform) +- Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. +- We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. +- We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. +☝ **Please use this link to help us understand your user experience!** +::: + +#### UX Criteria +:::info ABILITY +* Hackney **Google Workspace** user +* `[my service]` Data Analyst +* ***Amazon Athena*** user +* ***GitHub*** user +::: + +:::note BEHAVIOR +**Measures** the behavior of ***GitHub*** and ***Amazon Athena***. + +**Given** in my web browser, I have logged into my AWS account +**~and** I accessed ***Amazon Athena*** +**~and** I have selected my `[service workgroup]` +**~and** I have created and saved my `[transform SQL]` as a working fully functional Athena SQL query +**~and** I have my `[transform SQL]` kept open in the Athena query editor in a web browser tab +**~and** in another tab in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication +**~and** I am granted membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorporating the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** I have accessed the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) repository +**~and** I previously created my **`[transform branch]`** + +**When** I select my **`[transform branch]`** as my working branch +**~and** I navigate to my `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service subfolder +**~and** at the top right region of the page, click the "**Add file**" button and select "**Create new file**" +**~and** in the box following the **`transformations/`** subfolder, I enter my `[transform].sql` +**~and** back in the ***Amazon Athena*** web browser tab, I select the entire code of my `[transform SQL]` in the Athena query editor before *copying* it into my computer’s clipboard +**~and** back in the ***GitHub*** web browser tab, in the editor window, beneath where it says “**Edit**”, I *paste* the entire code of my `[transform SQL]` from my computer’s clipboard + **~and** I scroll to the bottom of the editor window to check and remove any `limit` clause (eg. `limit 100`), leaving just the `;` semi-colon at the very end +**~and** I click the "**Commit changes**" button to open up a dialogue box +**~and** I enter a short commit message, Eg. `Add ... [transform].sql` +**~and** I enter a longer description if I want to +**~and** I select the option “**Commit directly to my `[transform branch]`** +**~and** I click the "**Commit changes**" button + +**Then** I should see a message telling me, my `[transform].sql` was successfully committed directly to my `[transform branch]`. + +**Scale** of 11 to 19 **~and** flow features. +::: + +[branch]: diff --git a/sidebars.js b/sidebars.js index 67acb3ac..fd54ccff 100644 --- a/sidebars.js +++ b/sidebars.js @@ -138,6 +138,7 @@ module.exports = { "dap-airflow/onboarding/prototype-legacy-transforms", "dap-airflow/onboarding/github-access", "dap-airflow/onboarding/github-branch", + "dap-airflow/onboarding/github-commit-transform", ], }, ], From ab1b52dd347a805402aa127fa5424490ccc3b5a9 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Thu, 29 Aug 2024 01:45:03 +0100 Subject: [PATCH 09/16] =?UTF-8?q?Updated=20DAP=E2=87=A8flow=20onboarding?= =?UTF-8?q?=20/=20rationalized=20my/your=20[labels]?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../dap-airflow/images/github-access-five.png | Bin 117887 -> 117879 bytes .../prototype-simple-transforms-nine-b.png | Bin 107565 -> 60786 bytes .../prototype-simple-transforms-seven.png | Bin 107565 -> 31145 bytes .../prototype-simple-transforms-six-c.png | Bin 0 -> 81002 bytes .../prototype-simple-transforms-six-d.png | Bin 0 -> 14922 bytes docs/dap-airflow/introduction.md | 36 ++--- .../access-my-Amazon-Athena-database.md | 45 +++--- .../access-my-current-service-data.md | 44 +++--- .../access-my-service-data-history.md | 73 ++++----- .../access-the-AWS-Management-Console.md | 30 ++-- .../onboarding/access-the-AWS-region.md | 23 +-- docs/dap-airflow/onboarding/begin.md | 43 +++--- docs/dap-airflow/onboarding/github-access.md | 10 +- docs/dap-airflow/onboarding/github-branch.md | 28 ++-- .../onboarding/github-commit-transform.md | 30 ++-- 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ze6|I@XC6EC?Y1>MtmL4gb<~Hozk+r52!V&(*&IWkvIY}0KtB=UTr&xsyO-W_v>S7z zmDi zSAE43->k)BH?mI^uToybFwC2%GMtzx?}CtOP&LhyWa8>a`v51W5tfPcQ6<<(13RNq z*UtA1*&B!B@oYkQdWY&Nu6eEf8#vR{Fv diff --git a/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md b/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md index 44d9e263..cfeaf553 100644 --- a/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md +++ b/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md @@ -6,29 +6,32 @@ layout: playbook_js tags: [onboarding] --- -# How will I access my database from Amazon Athena? +# How will I use ***Amazon Athena*** to access my database? -### 1. Access the AWS Management Console -**`🖱`** In your web browser, log in to your AWS account to access the AWS Management Console. +### 1. Access the ***AWS Management Console*** +**`🖱`** In your web browser, log in to your AWS account to access the ***AWS Management Console***. 👉 First time AWS Users should **start here ►** **[DAP⇨flow📚AWS Console access](../onboarding/access-the-AWS-Management-Console)** -### 2. Familiarize Yourself with the console -**`🖱`** Take a moment to get comfortable with the layout and check out options available in the AWS console interface. +### 2. Familiarize yourself with the console +**`👁`** Take a moment to get comfortable with the layout and check out options available in the ***AWS Management Console*** interface. **`Fig. 2 & 3`** ![Fig. 2 & 3](../images/access-my-Amazon-Athena-database-two-three.png) -### 3. Open Amazon Athena -**`🖱`** Locate and open Amazon Athena from the services menu. +### 3. Open ***Amazon Athena*** +**`🖱`** Locate and open ***Amazon Athena*** from the services menu. -### 4. Select the Workgroup -**`🖱`** On the Athena interface, look to the top right corner next to "**Workgroup**". Then from the list box, select `[my service]`. +### 4. Select your `[service workgroup]` +**`👁`** Look to the top right corner of the ***Amazon Athena*** interface, next to "**Workgroup**". + +**`🖱`** From the list box there, click on **`▼`** to select your `[service workgroup]`. **`Fig. 4 & 5`** ![Fig. 4 & 5](../images/access-my-Amazon-Athena-database-four-five.png) -### 5. Select the Database -**`🖱`** On the left side of the Athena interface, under the "**Database**" section, find the list box and check you have `[my service raw zone]`. +### 5. Select your `[service raw zone]` database +**`👁`** On the left side of the ***Amazon Athena*** interface, below the "**Database**" section, find the list box and check you can already see your `[service raw zone]` database. +**`🖱`** If you don't see it there, then simply click on **`▼`** to select your `[service raw zone]` database from the list box. --- ## ***"We* ♡ *your feedback!"*** @@ -44,21 +47,23 @@ tags: [onboarding] #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user -* `[my service]` Data Analyst +* **AWS Management Console** user +* Hackney `[service]` Data Analyst ::: :::note BEHAVIOR -**Measures** the behavior of **Amazon Athena** when first run and configured by the user +**Measures** the behavior of **Amazon Athena** when first run and configured by the user: -**Given** in my web browser, I have access to the Data Platform AWS Management Console +**Given** in my web browser, I have access to the ***AWS Management Console*** **~and** I have familiarized myself with the console interface -**When** I open Amazon Athena via the console menu system, by clicking on “**Athena**” where it appears -**~and** I click through any splash screen that might appear, eg. “Explore the Query Editor” -**Then** I will be presented with the Amazon Athena interface -**~and** up at the right next to “**Workgroup**”, I should be offered `[my service]` from the list box -**~and** over on the left under “**Database**” I should be offered `[my service raw zone]` from the list box. + +**When** I open ***Amazon Athena*** via the console menu system, by clicking on “**Athena**” whereever it appears +**~and** I click through any splash screen that might appear, eg. “**Explore the Query Editor**” + +**Then** I will be presented with the **Amazon Athena** interface +**~and** up at the right next to “**Workgroup**”, I should be offered my `[service workgroup]` from the list box +**~and** over on the left under “**Database**” I should be offered my `[service raw zone]` from the list box. **Scale** of 3 to 4 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/access-my-current-service-data.md b/docs/dap-airflow/onboarding/access-my-current-service-data.md index c1438560..b7acede4 100644 --- a/docs/dap-airflow/onboarding/access-my-current-service-data.md +++ b/docs/dap-airflow/onboarding/access-my-current-service-data.md @@ -6,43 +6,43 @@ layout: playbook_js tags: [onboarding] --- -# How will I access my current service data from Amazon Athena? +# How will I access my current service data from ***Amazon Athena***? -### 1. Access Amazon Athena -**`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. +### 1. Access ***Amazon Athena*** +**`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. -👉 First time Amazon Athena users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** +👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your database -**`🖱`** Ensure that you have selected `[my service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. +### 2. Select your `[service raw zone]` database +**`🖱`** Ensure that you have selected your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. ### 3. Explore the views in your database -**`🖱`** Beneath the "**Database**" section on the left of the Athena interface and below the “**▼ Tables**” section (collapsed when clicking **▼**→“**► Tables**”), expand the “**► Views**" section (clicking **►**→“**▼ Views**”) to find a list of views based on tables available from `[my service raw zone]` database. +**`🖱`** Beneath the "**Database**" section on the left of the Athena interface and below the "**`▼` Tables**” section (collapsed when clicking **`▼`**→“**`►` Tables**”), expand the “**`►` Views**" section (clicking **`►`**→“**`▼` Views**”) to find a list of views based on tables available from your `[service raw zone]` database. -* **DAP⇨flow** implements Athena databases that present users with views that show only current-generation data, based upon their underlying history-table counterparts. So Data Analysts can ignore the history in the S3 data lake and instead write much simpler transformations resembling the queries of the original `[my service database]`. +* **DAP⇨flow** implements Athena databases that present users with views that show only current-generation data, based upon their underlying history-table counterparts. So Data Analysts can ignore the history in the S3 data lake and instead write much simpler transformations resembling the queries of your original `[service database]`. - 👉 The explanation of that underlying history is **documented here ►** **[DAP⇨flow📚My service data history](../onboarding/access-my-service-data-history)** + 👉 The explanation of the underlying history is **documented here ►** **[DAP⇨flow📚My service data history](../onboarding/access-my-service-data-history)** -* In the implementation of **DAP⇨flow**, the names of the views should exactly represent the original table names of `[my service database]`. +* In the implementation of **DAP⇨flow**, the names of the views should exactly represent the original table names of your `[service database]`. **`Fig. 2, 3, 4 & 5`** ![Fig. 2, 3, 4 & 5](../images/access-my-current-service-data-two-five.png) ### 4. Expand each view -**`🖱`** Navigating beneath “**▼ Views**”, click on each view name to expand it and observe the complete list of columns in that view. +**`🖱`** Navigating beneath “**`▼` Views**”, click on each view name to expand it and observe the complete list of columns in that view. ### 5. Verify the views and columns -**`👁`** Compare each view and its columns with the equivalent table and columns from `[my service database]` to observe how their names and data types match up with their counterparts. +**`👁`** Compare each view and its columns with the equivalent table and columns from your `[service database]` to observe how their names and data types match up with their counterparts. * Occasionally the automatic data type translation will yield unexpected results. Always check columns to ensure there will never be any data lost. For example, if integer precision is lost. -* Be specially aware of **date** translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially used in comparison, or when joined to date columns from tables elsewhere. +* Be specially aware of *date* translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially when used in comparison, or used to join *date* columns from tables elsewhere. ### 6. Observe the partition columns -**`🖱`** Scroll to the bottom of the column list to find the partition scheme derived from the underlying history table. This will comprise four or more columns shown with the partition data type alongside eg. ***string.*** But unlike its table counterpart in the section above, the view will actually not show “***(Partitioned)***”. +**`🖱`** Scroll to the bottom of the column list to find the partition scheme derived from the underlying history table. This will comprise four or more columns shown with the partition data type alongside eg. **`string`** But unlike its table counterpart in the section above, the view will actually not show **`(Partitioned)`**. **`Fig. 6`** ![Fig. 6](../images/access-my-current-service-data-six.png) -* Later on when we come to query these views we will observe data fetched from the single most current **generation** of data, as we study the output from those partition columns, in particular, “**import\_date**”. +* Later on when we come to query these views we will observe data fetched from the single most current **generation** of data, as we study the output from those partition columns, in particular, `import_date`. --- @@ -59,19 +59,21 @@ tags: [onboarding] #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user -* `[my service]` Data Analyst -* `[my service database]` user +* ***AWS Management Console*** user +* Hackney `[service]` Data Analyst +* Hackney `[service database]` user ::: :::note BEHAVIOR -**Measures** the behavior of **Amazon Athena** while the user explores `[my service raw zone]` database views and columns. +**Measures** the behavior of **Amazon Athena** as users explore their `[service raw zone]` database views and columns: + +**Given** I have selected my `[service raw zone]` database in the ***Amazon Athena*** interface -**Given** I have selected `[my service raw zone]` database in the Amazon Athena interface **When** I explore the list below “**Views**” **~and** expand each view name to list its columns -**Then** I should find view names exactly equivalent to tables from `[my service database]` + +**Then** I should find view names exactly equivalent to tables from my `[service database]` **~and** find equivalent column names with their respective equivalent data types **~and** I should observe every view has columns added, eg. “import_date”, based on the partition schema of each underlying table. diff --git a/docs/dap-airflow/onboarding/access-my-service-data-history.md b/docs/dap-airflow/onboarding/access-my-service-data-history.md index 7320000a..f95c8504 100644 --- a/docs/dap-airflow/onboarding/access-my-service-data-history.md +++ b/docs/dap-airflow/onboarding/access-my-service-data-history.md @@ -6,66 +6,67 @@ layout: playbook_js tags: [onboarding] --- -# How will I access my service data history from Amazon Athena? +# How will I access my `[service]`'s data history from ***Amazon Athena***? -### 1. Access Amazon Athena -**`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. +### 1. Access ***Amazon Athena*** +**`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. -👉 First time Amazon Athena users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** +👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Selecting and understanding your database -**`🖱`** Ensure that you have selected `[my service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. +### 2. Understanding your `[service raw zone]` database +**`🖱`** Ensure you have selected your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. **`Fig. 2 & 3`** ![Fig. 2 & 3](../images/access-my-service-data-history-two-three.png) -* Athena’s databases are actually catalogs of the data stored in the AWS S3 storage buckets and folders, which we collectively call a **data lake.** From the top level, data lakes are divided by zone, then by service, then by service database. +💡 Athena’s databases are actually catalogs of the data stored in the ***AWS S3*** storage buckets and folders, which we collectively call a **data lake.** From the top level, data lakes are divided by zone, then by service, then by service database. -* The service database folders are represented by **databases** in Athena which which are labeled in the reverse “***service*\-*database*\-*zone” format***. The zone suffix labeling has the following meaning: - * “-**raw-zone**" for databases where data tables arrive after they are ingested from a service database and whose specification depends upon the source of that data. - * “-**refined-zone**" for databases where data goes whenever it is transformed and whose specification is implemented by data analysts and engineers when developing their data pipelines. - * “-**trusted-zone**" for databases containing the product tables whose specification is developed and agreed upon by data analysts and engineers in collaboration with their data users. +💡 The service database folders are represented by **databases** in Athena that are labeled in the reverse *`service-database-zone`* format. The *zone suffix* labeling has the following meaning: +* **`...-raw-zone`** for databases where data tables arrive after they are ingested from a service database and whose specification depends upon the source of that data. +* **`...-refined-zone`** for databases where data goes whenever it is transformed and whose specification is implemented by data analysts and engineers when developing their data pipelines. +* **`...-trusted-zone`** for databases containing the product tables whose specification is developed and agreed upon by data analysts and engineers in collaboration with their data users. -👉 For more information on how Amazon S3 organizes data, go ►[**here**](https://docs.aws.amazon.com/AmazonS3/latest/userguide/organizing-objects.html) +👉 For more information on how Amazon S3 organizes data, see ►[**here**](https://docs.aws.amazon.com/AmazonS3/latest/userguide/organizing-objects.html) ### 3. Explore the tables in your database -**`🖱`** Beneath the "**Database**" section on the left of the Athena interface, expand the "**► Tables**" section to find the list of tables available from `[my service raw zone]` database. +**`🖱`** Beneath the "**Database**" section on the left of the Athena interface, expand the "**`►` Tables**" section to find the list of tables available from your `[service raw zone]` database. * This is how Athena presents tables from the S3 data lake. In S3’s folder structure, tables are represented by folders below the service database folder. -* In this implementation, the table names were all suffixed with “**\_history**” to remind us that each table contains several daily generations of data traveling back in time. +* In this implementation, the table names were all suffixed `..._history` to remind us that each table contains several daily generations of data stretching back in time. -### 4. Expand each table +### 4. Expanding each table **`🖱`** Click on each table name to expand it and observe the complete list of columns for that table. **`Fig. 4 & 5`** ![Fig. 4 & 5](../images/access-my-service-data-history-four-five.png) -### 5. Verify the views and columns -**`👁`** Compare each table and its columns with the equivalent table and columns from `[my service database]` to observe how their names and data types match up with their counterparts. +### 5. Verifying the views and columns +**`👁`** Compare each table and its columns with the equivalent table and columns from your `[service database]` to observe how their names and data types match up with their counterparts. * Occasionally the automatic data type translation will yield unexpected results. Always check columns to ensure there will never be any data lost. For example, if integer precision is lost. -* Be specially aware of **date** translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially used in comparison, or when joined to date columns from tables elsewhere. +* Be especially aware of *date* translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially when used in comparison, or used to join *date* columns from tables elsewhere. -### 6. Observe the partition columns -**`🖱`** Scroll to the bottom of the column list to find the partition scheme. This will comprise four or more partition columns shown with the partition data type alongside eg. ***string (Partitioned).*** +### 6. Observing the partition columns +**`🖱`** Scroll to the bottom of the column list to find the partition scheme. This will comprise three, or four, or more partition columns shown with the partition data type alongside eg. **`string (Partitioned)`**. -**`Fig. 6`** ![Fig. 6](../images/access-my-service-data-history-six.png) +**`Fig. 6`** ![Fig. 6](../images/access-my-service-data-history-six.png) +#### 💡 Traditional databases versus a data lake It helps to become familiar with the fundamental differences between a traditional database and a data lake that records the entire history of our data. * Because tables are ingested or otherwise transformed daily (the most common frequency), each table folder, in the S3 data lake, must be subdivided by it's **generation**, so the underlying technology of the data platform can quickly access either current data, or specified previous data, needed for transformations. * Generations are organized hierarchically using S3 folders represented by the following partition column strings: - * ***Year*** eg. “**import\_year**” eg. ‘2024’ (the current year) - * ***Month*** eg. “**import\_month**” eg. ‘06’ (the current month eg. June) - * ***Day*** eg. “**import\_day**” eg. ‘05’ (5th day of the current month) - * ***Date*** eg. “**import\_date**” eg. “20240605” (5th June 2024\) + * ***Year*** eg. `import_year` eg. ‘2024’ (the current year) + * ***Month*** eg. `import_month` eg. ‘06’ (the current month eg. June) + * ***Day*** eg. `import_day` eg. ‘05’ (5th day of the current month) + * ***Date*** eg. `import_date` eg. “20240605” (5th June 2024\) - We might see alternatives to "**import\_**…" column prefixes such as “**transform\_**…” or “**generation\_**…”, or observe combinations of generation the prefixes, to indicate data imported and transformed at different times. + We might see alternatives to `import_…` column prefixes such as `transform_…` or `generation_…`, or observe combinations of generation the prefixes, to indicate data imported and transformed at different times. -* We may observe other non-generational partition types, for example, we might want to subdivide the data after it is ingested in some other useful way, eg. by currency or historicity to facilitate data governance management and optimize our data pipelines even further. +* We may observe other non-generational partition types, for example, we might want to subdivide the data after it is ingested in some other useful way, eg. by *currency* or *historicity* to facilitate data governance management or optimize our data pipelines in some way. -👉 So that Data Analysts are not overwhelmed by data partitioning, and can avoid using generational sub-queries in their transformations, a solution was developed which is **documented here ►** **[DAP⇨flow📚My current service data](../onboarding/access-my-current-service-data)** +👉 So that Data Analysts are not overwhelmed by the data partitioning scheme, and can avoid using complex generational sub-queries in their transformations, a better solution was developed. The product of that development is **documented here ►** **[DAP⇨flow📚My current service data](../onboarding/access-my-current-service-data)** --- ## ***"We* ♡ *your feedback!"*** @@ -81,21 +82,23 @@ It helps to become familiar with the fundamental differences between a tradition #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user -* `[my service]` Data Analyst -* `[my service database]` user +* **AWS Management Console** user +* Hackney `[service]` Data Analyst +* Hackney `[service database]` user ::: :::note BEHAVIOR -**Measures** the behavior of **Amazon Athena** while the user explores `[my service raw zone]` database tables and columns. +**Measures** the behavior of **Amazon Athena** while users explore their `[service raw zone]` database tables and columns: + +**Given** I selected my `[service raw zone]` database in the ***Amazon Athena*** interface -**Given** I have selected `[my service raw zone]` database in the Amazon Athena interface **When** I explore the list below “**Tables**” **~and** expand each table name to list its columns -**Then** I should find table names equivalent to tables from `[my service database]` with the suffix “**_history**” added + +**Then** I should find table names equivalent to tables from my `[service database]` with the suffix `..._history` added **~and** find equivalent column names with their respective equivalent data types -**~and** I should observe every table has partition columns added, eg. “import_date”. +**~and** I should observe every table has partition columns added, eg. `import_date`. **Scale** of 3 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md b/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md index 2a9ac45a..6963f6ba 100644 --- a/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md +++ b/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md @@ -6,32 +6,34 @@ layout: playbook_js tags: [onboarding] --- -# How will I access the AWS Management Console? +# How will I access the ***AWS Management Console***? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Log into your Hackney Council Google Account -**`🖱`** Start by logging into your Hackney Council Google account. +### 1. Log into your **Hackney Council** Google Account +**`🖱`** Always start by logging into your **Hackney Council** Google account. ### 2. Open the AWS access portal **`🖱`** In your web browser, navigate to the **[AWS access portal](https://d-936715b9ec.awsapps.com/start\#/)**. ### 3. Expand the AWS accounts -**`🖱`** If you were granted access to the Hackney Council AWS Console then you should be able to locate and fully expand the "**DataPlatform-Pre-Production**" section under “**AWS accounts**”. +**`🖱`** If you were granted access to **Hackney Council's** ***AWS Management Console*** then you should be able to locate and fully expand the "**DataPlatform-Pre-Production**" section under “**AWS accounts**”. **`Fig. 3 & 4`** ![Fig. 3 & 4](../images/access-the-AWS-Management-Console-three-four.png) ### 4. Locate Your service role -**`🖱`** Below "**DataPlatform-Pre-Production**", find `[my service role]` listed. +**`🖱`** Below "**DataPlatform-Pre-Production**", find your `[service role]` listed. -### 5. Access the AWS Management Console -**`🖱`** Click on `[my service role]` to access the Data Platform AWS Management Console. - * You may need to accept cookies and respond to service messages. - * You may see errors caused by the AWS region not set correctly. +👉 If you do not know your `[service role]`, **please check here** to ensure you were properly set up to use the ***AWS Management Console*** ►** **[DAP⇨flow📚Before you begin](../onboarding/begin)** - 👉 To fix the AWS region, **check here ►** **[DAP⇨flow📚AWS region](../onboarding/access-the-AWS-region)** +### 5. Access the ***AWS Management Console*** +**`🖱`** Click on your `[service role]` to access the Data Platform AWS Management Console. +* You may need to accept cookies and respond to service messages. +* You may see errors caused by the AWS region not set correctly. **`Fig. 5`** ![Fig. 5](../images/access-the-AWS-Management-Console-five.png) +👉 To fix the AWS region, **check here ►** **[DAP⇨flow📚AWS region](../onboarding/access-the-AWS-region)** +

@@ -53,13 +55,15 @@ tags: [onboarding] ::: :::note BEHAVIOR -**Measures** the **AWS Management Console** behavior: +**Measures** the ***AWS Management Console*** behavior: **Given** in my web browser, I am logged into my **Hackney Council Google account** -**~and** I was granted access to the **Hackney Council AWS Console** +**~and** I was granted access to the **Hackney Council's** ***AWS Management Console*** + **When** I open the [**AWS access portal**](https://d-936715b9ec.awsapps.com/start\#/) **~and** fully expand the **DataPlatform-Pre-Production** under **AWS Accounts** -**Then** below **DataPlatform-Pre-Production**, I should see `[my service role]` listed + +**Then** below **DataPlatform-Pre-Production**, I should see my `[service role]` listed **~and** clicking on it should give me access to the **AWS Management Console**. **Scale** of 2 to 3 **~and** flow features. diff --git a/docs/dap-airflow/onboarding/access-the-AWS-region.md b/docs/dap-airflow/onboarding/access-the-AWS-region.md index 1ae2d0d4..664ebcae 100644 --- a/docs/dap-airflow/onboarding/access-the-AWS-region.md +++ b/docs/dap-airflow/onboarding/access-the-AWS-region.md @@ -11,23 +11,24 @@ tags: [onboarding] You will need to check the region you are in, usually the first time you access the AWS Management Console. Thereafter your web browser will remember the region you last used so you should not need to check this very often. -### 1. Access the AWS Management Console -**`🖱`** In your web browser, log in to your AWS account to access the AWS Management Console. +### 1. Access the ***AWS Management Console*** +**`🖱`** In your web browser, log in to your AWS account to access the ***AWS Management Console***. 👉 First time AWS Users should **start here ►** **[DAP⇨flow📚AWS Console access](../onboarding/access-the-AWS-Management-Console)** ### 2. Locate the Region Selector -**`🖱`** At the top of the console, find the region selector "**▼**". +**`👁`** At the top of the console, locate the region selector **`▼`**. **`Fig. 2`** ![Fig. 2](../images/access-the-AWS-region-two.png) ### 3. Select Your Region -**`🖱`** Click on the arrow to open the region menu. Then from the list, choose "**Europe (London) eu-west-2.**" +**`🖱`** Click on the **`▼`** arrow to open the region menu. +**`🖱`** From the list that appears, choose **`Europe (London) eu-west-2`** as your region. **`Fig. 3 & 4`** ![Fig. 3 & 4](../images/access-the-AWS-region-three-four.png) ### 4. Verify the Selected Region -**`🖱`** After selecting, you should see "**London ▼**" displayed at the top of the console, confirming that you have successfully changed the region. +**`👁 `** After selecting your region, you should see **`London ▼`** displayed at the top of the console, confirming that you have successfully changed the region.

@@ -50,12 +51,14 @@ You will need to check the region you are in, usually the first time you access ::: :::note BEHAVIOR -**Measures** the **AWS Management Console** behavior: +**Measures** the ***AWS Management Console*** behavior: -**Given** I have accessed the **AWS Management Console** -**When** I check my region by selecting the “**▼**” arrow second from the right at the top of the console -**~and** select “**Europe (London) eu-west-2**” from the menu -**Then** “**London ▼**” should appear at the top of the console as my region. +**Given** I have accessed the ***AWS Management Console*** + +**When** I check then select my region by clicking the **`▼`** arrow second from the right at the top of the console +**~and** select **`Europe (London) eu-west-2`** from the menu + +**Then** **`London ▼`** should appear at the top of the console as my region. **Scale** of 2 to 3 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/begin.md b/docs/dap-airflow/onboarding/begin.md index 1954e23b..14c8f602 100644 --- a/docs/dap-airflow/onboarding/begin.md +++ b/docs/dap-airflow/onboarding/begin.md @@ -9,14 +9,14 @@ tags: [onboarding] # What must happen before I can begin DAP⇨flow? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Is your service’s data now available on the Data Analytics Platform (DAP)? -Your manager or the **DAP Platform Team** will have told you about this. +### 1. Is your `[service]`’s data now available on the Data Analytics Platform (DAP)? +Your `[service]` manager or the **DAP Platform Team** will have told you about this. -### 2. Are you using your Hackney Council Google Account? -You’ll always need to be logged into your Hackney Council Google account via your web browser when following the **DAP⇨flow** onboarding tasks. +### 2. Are you using your **Hackney Council** Google Account? +You’ll always need to be logged into your **Hackney Council** Google account via your web browser when following the **DAP⇨flow** onboarding tasks. ### 3. Your manager must add you to the DAP Access Google Group -Ask your manager to add your name to the [DAP Access Google Group](https://support.google.com/groups/answer/2465464?hl=en) for `[my service]`. Your manager may need to contact the **DAP Platform Team** if this is their first time adding someone to the group. +Ask your `[service]` manager to add your name to the [DAP Access Google Group](https://support.google.com/groups/answer/2465464?hl=en), aka your `[service workgroup]`. Your manager may need to contact the **DAP Platform Team** if this is their first time adding someone to the group. ### 4. Access granted! Once your name is added, you will be granted @@ -24,11 +24,11 @@ Once your name is added, you will be granted - membership of the **☎️DAP⇨flow Hotline** Google Chat Space. ### 5. You’ll receive an email, welcoming you to **DAP⇨flow** -Check for an email from the **DAP Platform Team** welcoming you to the DAP. This email will present you with the following information needed while using the **DAP⇨flow** service and using the **📚Onboarding** documentation: -- `[my service]` name confirming my workgroup -- `[my service role]` needed to access the AWS Console -- `[my service raw zone]` is the database where you will find your data -- `[my service database]` confirms where your data came from +Check for an email from the **DAP Platform Team** welcoming you to the DAP. This email will present you with the following information needed to begin using the **DAP⇨flow** and while following the **📚Onboarding** documentation: +- Your `[service workgroup]` confirming your workgroup in ***Amazon Athena*** and other places +- Your `[service role]` needed to access the ***AWS Management Console*** +- Your `[service raw zone]` as the database where you will find your ingested data +- Your `[service database]` confirming where your data actually came from ### 6. Check out the links in your email You will be directed and encouraged to use the following **DAP⇨flow** resources linked in the email: @@ -65,20 +65,27 @@ You will be directed and encouraged to use the following **DAP⇨flow** resource #### UX Criteria :::info ABILITY * Hackney **Google Workspace** user -* `[my service]` Data Analyst +* Hackney `[service]` Data Analyst ::: :::note BEHAVIOR -**Measures** the **DAP Platform Team** behavior: +**Measures** the **DAP Platform Team** behavior and the agency of the `[service]` manager: + +**Given** my `[service]` was already set up as a [**DAP department**](https://playbook.hackney.gov.uk/Data-Platform-Playbook/playbook/getting-set-up/onboarding-new-departments-to-the-platform) +**~and** I have a **Hackney Council Google account** + +**When** my `[service]`manager puts my name in the [**DAP Access Google Group**](https://support.google.com/groups/answer/2465464?hl=en) for my `[service workgroup]` -**Given** `[my service]` was already set up as a [**DAP department**](https://playbook.hackney.gov.uk/Data-Platform-Playbook/playbook/getting-set-up/onboarding-new-departments-to-the-platform) -**~and** I have a **Hackney Council Google account** -**When** my manager puts my name in the [**DAP Access Google Group**](https://support.google.com/groups/answer/2465464?hl=en) for `[my service]` **Then** I will be granted appropriate access to the [**Hackney Council AWS Console**](https://d-936715b9ec.awsapps.com/start/\#/?tab=accounts) **~and** I will be granted membership of a community channel -**~and** I will receive an email from the **DAP Platform Team** welcoming me to the DAP -**~and** that email will give me a list of information that I will need to use the DAP service and documentation -**~and** that email will direct to the DAP resources I will need next and encourage me to use them. +**~and** I will receive an email from the **DAP Platform Team** welcoming me to **DAP⇨flow** +**~and** that email will give me the list of information I need to begin using **DAP⇨flow** while following the **📚Onboarding** documentation: +- `[service workgroup]` +- `[service role]` +- `[service raw zone]` +- `[service database]` + +**~and** that email will direct to the next **DAP⇨flow📚Onboarding** resource I will need. **Scale** of 4 to 5 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/github-access.md b/docs/dap-airflow/onboarding/github-access.md index e5b34a2c..a3d454e8 100644 --- a/docs/dap-airflow/onboarding/github-access.md +++ b/docs/dap-airflow/onboarding/github-access.md @@ -35,11 +35,11 @@ The **DAP Platform Team** will 👉 * Acknowledge your request and continue to update your status via a reply-thread on the [☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7). -* If you don't have membership already, [ensure you get invited](https://docs.github.com/en/enterprise-cloud@latest/organizations/managing-membership-in-your-organization/inviting-users-to-join-your-organization) to the [London Borough of Hackney](https://github.com/LBHackney-IT) organization on GitHub. +* If you don't have membership already, [ensure you get invited](https://docs.github.com/en/enterprise-cloud@latest/organizations/managing-membership-in-your-organization/inviting-users-to-join-your-organization) to the [**London Borough of Hackney**](https://github.com/LBHackney-IT) organization on GitHub. * Check your access to the [**`dap-airflow`** private repository](https://github.com/LBHackney-IT/dap-airflow). -* Inform you about your ***GitHub*** project folder `[my service dags]` and point you to the `README.md` there. +* Inform you about your `[service dags]` ***GitHub*** project folder and point you to the `README.md` there. * Tell you your `dap-airflow` access is now configured while directing you back to the **📚Onboarding** documentation to learn about [what you should do next](../introduction#github-branching). @@ -63,7 +63,7 @@ The **DAP Platform Team** will 👉 #### UX Criteria :::info ABILITY * Hackney **Google Workspace** user -* `[my service]` Data Analyst +* Hackney `[service]` Data Analyst * ***GitHub*** beginner ::: @@ -78,9 +78,9 @@ The **DAP Platform Team** will 👉 **Then** the **DAP Platform Team** will acknowledge my request via a reply-thread on the [☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7) -**~and** ensure I am granted membership of [London Borough of Hackney](https://github.com/LBHackney-IT) organization on ***GitHub*** +**~and** ensure I am granted membership of [**London Borough of Hackney**](https://github.com/LBHackney-IT) organization on ***GitHub*** **~and** ensure I can subsequently access the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) private repository -**~and** confirm `[my service dags]` ***GitHub*** project folder with link to the `README.md` there +**~and** confirm my `[service dags]` ***GitHub*** project folder with link to the `README.md` there **~and** tell me my `dap-airflow` access is now configured while directing me back to the [**📚Onboarding** documentation](../introduction#github-branching). **Scale** of 5 **~and** flow features. diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index d4c01444..8f6d7400 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -6,7 +6,7 @@ layout: playbook_js tags: [onboarding] --- -# How do I add a new development branch to **DAP⇨flow**'s `[dap-airflow]` repository? +# How do I create `[transform branch]` as my new working branch of **DAP⇨flow**'s `[dap-airflow]` repository? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) ### 1. Log into your ***GitHub*** account @@ -17,7 +17,7 @@ tags: [onboarding] ### 2. Access the repository **`🖱`** When you are ready to begin, open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. -### 3. Create a new branch +### 3. Create `[transform branch]` as your new working branch **`🖱`** Select the "**Code**" tab at the top of the repository page @@ -25,12 +25,12 @@ tags: [onboarding] **`🖱`** Below that, click on the "**![][branch]`main`**" branch dropdown button menu. -**`🖮`** Type your new branch name **`[my branch]`** as your working branch for development. +**`🖮`** Type **`[transform branch]`** as the name as your new working branch. -**`🖱`** Below that on the dropdown menu, click on "Create branch **![][branch]`[my branch]`** from **`main`.**" +**`🖱`** Below that on the dropdown menu, click on "Create branch **![][branch]`[transform branch]`** from **`main`.**" -### 4. Verify your new branch -**`👁`** After creating the branch, "![][branch]`[my branch]`” should replace "![][branch]`main`" as your working branch for development. +### 4. Verify `[transform branch]` is now your working branch +**`👁`** Check your "![][branch]`[trannsform branch]`” has replaced "![][branch]`main`" as your working branch. **`Fig. 4`** ![Fig. 4](../images/github-branch-four.png) @@ -51,25 +51,25 @@ tags: [onboarding] #### UX Criteria :::info ABILITY * Hackney **Google Workspace** user -* `[my service]` Data Analyst +* Hackney `[service]` Data Analyst * ***GitHub*** beginner ::: :::note BEHAVIOR -**Measures** the ***GitHub*** behavior: +**Measures** the ***GitHub*** and `dap-airflow` repository behavior: **Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication -**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorporating the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) private repository -**~and** I have decided what to call **`[my branch]`** as my working branch for development +**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorporating the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** **`[transform branch]`** will be the name of my new working branch **~and** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space -**When** I access the [dap-airflow](https://github.com/LBHackney-IT/dap-airflow) repository +**When** I access the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) repository **~and** I select the "**Code**" tab at the top of the repository page **~and** below that, I click on the "**![][branch]`main`**" branch dropdown button menu -**~and** type my new branch name **`[my branch]`** -**~and** click "Create branch **![][branch]`[my branch]`** from **`main`**" below that on the dropdown menu +**~and** I type **`[transform branch]`** +**~and** click "Create branch **![][branch]`[transform branch]`** from **`main`**" below that on the dropdown menu -**Then** "**![][branch]`[my branch]`**” should replace "**![][branch]`main`**" as my working branch for development +**Then** "**![][branch]`[transform branch]`**” should replace "**![][branch]`main`**" as my working branch **~and** ***GitHub*** will alert me via email if there are errors or warnings **~and** I will have information that I can pass to the **DAP Platform Team** via the **[☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7)** if I encounter errors or need assistance. diff --git a/docs/dap-airflow/onboarding/github-commit-transform.md b/docs/dap-airflow/onboarding/github-commit-transform.md index eaacf1b3..cc922a2d 100644 --- a/docs/dap-airflow/onboarding/github-commit-transform.md +++ b/docs/dap-airflow/onboarding/github-commit-transform.md @@ -6,19 +6,19 @@ layout: playbook_js tags: [onboarding] --- -# How do I commit my working transform query to **DAP⇨flow**'s `[dap-airflow]` repository? +# How do I commit my working `[transform SQL]` query to **DAP⇨flow**'s `[dap-airflow]` repository? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access ***Amazon Athena*** and workgroup +### 1. Access ***Amazon Athena*** with your `[service workgroup]` -**`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. +**`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. **`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 2. Prepare and make ready your SQL query +### 2. Prepare and make ready your `[transform SQL]` query **`🖱`** Ensure you have already created, tested and saved your `[transform SQL]` as a working, fully functional Athena SQL query. -👉 If you want reminding how to do any of that, see **here** or **here ►** +👉 If you want reminding of how to do any of that, see **here** or **here ►** * **[DAP⇨flow📚Prototype simple transforms](../dap-airflow/onboarding/prototype-simple-transforms)** * **[DAP⇨flow📚Prototype legacy transforms](../dap-airflow/onboarding/prototype-legacy-transforms)** @@ -26,9 +26,9 @@ tags: [onboarding] ### 3. Access the `dap-airflow` repository in ***GitHub*** -**`🖱`** Use another tab in your web browser to log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. +**`🖱`** Use another tab in your web browser to log into your ***GitHub*** account using your *Hackney email address* with two-factor authentication. -👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** +👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should check back at **the start ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** **`🖱`** Open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. @@ -37,9 +37,9 @@ tags: [onboarding] **`🖱`** Ensure you have created your ![][branch]`[transform branch]` and have it selected. **`Fig. 4`** ![Fig. 4a](../images/github-commit-transform-four-a.png) -👉 For how to create a branch, **see here ►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** +👉 For how to create your `[transform branch]`, **see here ►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** -**`🖱`** In the DAP Airflow repository, navigate to your `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service sub-folder. You can use ***GitHub***’s left-hand navigation pane as follows: +**`🖱`** In the `[dap-airflow]` repository, navigate to your `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service sub-folder. You can use ***GitHub***’s left-hand navigation pane as follows: * Click on the **`airflow`** folder * Inside the `airflow` folder, click on the **`dags`** folder * Inside the `dags` folder, click on your **`[service dags]`** folder @@ -59,17 +59,17 @@ tags: [onboarding] ### 6. Copy your `[transform SQL]` code from ***Amazon Athena*** **`🖱`** Switch back to the ***Amazon Athena*** tab in your web browser, with your `[transform SQL]` still in the query editor. -**`🖱`** Select the entire code of `[transform SQL]` open in the Athena query editor. +**`🖱`** Select your entire `[transform SQL]` code in the Athena query editor. **`Fig. 6`** ![Fig. 6](../images/github-commit-transform-six.png) **`🖱`** Use the right-click menu to "*Copy*" the selected code to your computer’s clipboard. ### 7. Paste your `[transform SQL]` code into ***GitHub*** **`🖱`** Switch back to the ***GitHub*** tab in your web browser, with `[transform].sql` currently empty in the code editor. -**`🖱`** In the editor window beneath where it says “**Edit**”, use the right-click menu to "*Paste*" the entire `[transform SQL]` code from your computer’s clipboard. +**`🖱`** In the ***GitHub*** editor window beneath where it says “**Edit**”, use the right-click menu to "*Paste*" your entire `[transform SQL]` code, from the computer’s clipboard, into your `[transform].sql` file. **`Fig. 7 & 8`** ![Fig. 7 & 8](../images/github-commit-transform-seven-eight.png) ### 8. Review and adjust your `[transform SQL]` code -**`🖱`** Scroll to the bottom of the editor window. +**`🖱`** Scroll to the bottom of the ***GitHub*** editor window. **`👁 🖱`** Check for and remove any `limit` clause (e.g., `limit 100`), leaving just the final **`;`** semi-colon at the very end. ### 9. Commit your `[transform].sql` file @@ -100,7 +100,7 @@ tags: [onboarding] #### UX Criteria :::info ABILITY * Hackney **Google Workspace** user -* `[my service]` Data Analyst +* Hackney `[service]` Data Analyst * ***Amazon Athena*** user * ***GitHub*** user ::: @@ -122,8 +122,8 @@ tags: [onboarding] **~and** I navigate to my `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service subfolder **~and** at the top right region of the page, click the "**Add file**" button and select "**Create new file**" **~and** in the box following the **`transformations/`** subfolder, I enter my `[transform].sql` -**~and** back in the ***Amazon Athena*** web browser tab, I select the entire code of my `[transform SQL]` in the Athena query editor before *copying* it into my computer’s clipboard -**~and** back in the ***GitHub*** web browser tab, in the editor window, beneath where it says “**Edit**”, I *paste* the entire code of my `[transform SQL]` from my computer’s clipboard +**~and** back in the ***Amazon Athena*** web browser tab, I select my entire `[transform SQL]` code in the Athena query editor before *copying* it into the computer’s clipboard +**~and** back in the ***GitHub*** web browser tab, in the editor window, beneath where it says “**Edit**”, I *paste* my `[transform SQL]` code, from the computer’s clipboard, into my `[transform].sql` file **~and** I scroll to the bottom of the editor window to check and remove any `limit` clause (eg. `limit 100`), leaving just the `;` semi-colon at the very end **~and** I click the "**Commit changes**" button to open up a dialogue box **~and** I enter a short commit message, Eg. `Add ... [transform].sql` diff --git a/docs/dap-airflow/onboarding/prototype-legacy-transforms.md b/docs/dap-airflow/onboarding/prototype-legacy-transforms.md index f70cc3ee..e2e9dbf3 100644 --- a/docs/dap-airflow/onboarding/prototype-legacy-transforms.md +++ b/docs/dap-airflow/onboarding/prototype-legacy-transforms.md @@ -5,60 +5,68 @@ description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Ana layout: playbook_js tags: [onboarding] --- -# How do I use *Amazon Athena* to prototype a data transformation from a `[legacy SQL query]`? +# How do I use ***Amazon Athena*** to prototype a data transformation from my `[legacy SQL query]`? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access *Amazon Athena* -**`🖱`** In your web browser, log in to your AWS account, navigate to the **AWS Management Console**, and open ***Amazon Athena***. +### 1. Access ***Amazon Athena*** +**`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. 👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your workgroup -**`🖱`** Ensure you have selected `[my service]` from the list box next to “**Workgroup**”. +### 2. Select your `[service workgroup]` +**`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 3. Select your database -**`🖱`** Ensure you select `[my service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. +### 3. Select your `[service raw zone]` database +**`🖱`** Ensure you select your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. -**`👁`** You should observe `[my service database]` equivalent tables and columns with their respective data types listed below "**▼ Views**". +**`👁`** You should observe your `[service database]` equivalent tables and columns with their respective data types listed below "**`▼` Views**". -### 4.Prepare your SQL query -**`🖱`** Copy and paste your `[legacy SQL query]` lifted from `[my service database]` into the query editor. - -You should take the opportunity to tidy up and format your code, making it easier to read, maintain, and spot errors. +### 4.Prepare your `[transform SQL]` query +**`🖱`** *Copy-and-paste* your `[legacy SQL query]` lifted from your `[service database]` into ***Amazon Athena***'s query editor to become your new `[transform SQL]` code. + +You should take this opportunity to tidy up and format your SQL code, making it easier to read, maintain, and spot errors. -👉 For an example, see [DPF-185 EXAMPLE 2.2 CFS Allocations query](https://docs.google.com/document/d/1EOBUOT6rZUk4tasub6Mqv\_ywHaXwQscTmFod9HQZQpU/edit?usp=sharing) +👉 You'll find considerations for SQL development discussed **►[💡here](../onboarding/prototype-simple-transforms#considerations-when-adopting-amazon-athena-for-your-future-sql-development)**. + +### 5. Verify table and column availability +**`🖱`** Over on the left of the Athena interface, expand the list under “**`▼` Views**” to verify your `[service raw zone]` includes your `[service database]` equivalent tables and columns matching those in your `[transform SQL]`. -### 5. Verify Table and Column Availability -**`🖱`** Over on the left of the Athena interface, expand the list under “**▼ Views**” to verify it includes your `[my service database]` equivalent tables and columns matching those in your `[legacy SQL query]`. **`Fig. 5a`** ![Fig. 5a](../images/prototype-legacy-transforms-five-a.png) -**`Fig. 5b`** ![Fig. 5b](../images/prototype-legacy-transforms-five-b.png) -### 6. Ensure your SQL query is compatible with *Amazon Athena* -**`👁`** Review your SQL code to ensure all column functions and expressions are compatible with ***Amazon Athena***, aiming to produce the same column output as the original. +**`Fig. 5b`** ![Fig. 5b](../images/prototype-legacy-transforms-five-b.png) + +### 6. Ensure your `[transform SQL]` is compatible with ***Amazon Athena*** +**`👁`** Review your `[transform SQL]` code to ensure all column functions and expressions are compatible with ***Amazon Athena***, aiming to produce the same column output as the original `[legacy SQL query]`. -Often the easy way to test your SQL code compatibility is simply to try running it (as per **Step 7**). It might succeed, or fail with errors that will inform you about what you need to change. +Often the easy way to test your SQL code compatibility is to simply try running it (as per **Step 7**). It might succeed, or fail with errors that should inform you about what you need to change. -👉 If your original column functions need replacing with equivalent ***Amazon Athena*** functions then you can check the ***Amazon Athena* documentation ►[here](https://docs.aws.amazon.com/athena/latest/ug/functions.html)**. +👉 If your original column functions need replacing with equivalent ***Amazon Athena*** functions then you can check the ***Amazon Athena* documentation ► [here](https://docs.aws.amazon.com/athena/latest/ug/functions.html)**. -**`🖱`** The first thing you will do when editing your SQL code, is make sure your tables names are fully qualified. +**`🖱`** Ensure your table names from your `[transform SQL]` are fully qualified, as follows: -- Table names should be prefixed by their correct database names, eg. `“[my service raw zone]”.“”`. +- Table names should be prefixed by their correct database names, eg. `[service raw zone].
`. -- The original `[my service database]` database name, where used in your `[legacy SQL query]`, will be different here in **DAP⇨flow**, so you will need to swap it out with `[my service raw zone]`. +- ***Amazon Athena***, by default, renders editor-inserted names encapsulated in `"` double-quotes, eg. `“[service raw zone]”.“
”`. You don't need to do this! But FYI, the quotes are a safeguard in case of column names containing spaces, even though we never allow that. + +- Your original `[service database]` database name will not be used by **DAP⇨flow**, so you will need to swap it out with your `[service raw zone]`. + +### 7. Run your `[transform SQL]` query +**`🖱`** After customizing the SQL code, click “**Run**” or “**Run again**” located underneath the code window on the left side in the ***Amazon Athena*** interface. -### 7. Run your query -**`🖱`** After customizing the SQL code, click “**Run**” located underneath the code window on the left side in the ***Amazon Athena*** interface. **`Fig. 7`** ![Fig. 7](../images/prototype-legacy-transforms-seven.png) ### 8. Review the results -**`👁`** ***Amazon Athena*** should fetch the same results as your `[legacy SQL query]` would have when executed upon your original `[my service database]`. If you are able at his point, to make such a direct comparison with the legacy system then it will help you have confidence in the results of your prototype. +**`👁`** ***Amazon Athena*** should fetch the same results as your `[legacy SQL query]` would have, when run by your original `[service database]`. If it is possible to make a direct comparison with the legacy system output then that should help you have confidence in the results of your prototype SQL. + **`Fig. 8`** ![Fig. 8](../images/prototype-legacy-transforms-eight.png) -### 9. Save your query -**`🖱`** Check you are in the correct `[my service]` workgroup before clicking on the three dots **⋮** to the right of your Query tab, then select “**Save as**”. +### 9. Save your query as `[transform].sql` +**`🖱`** Check you are in your correct `[service workgroup]` before clicking on the three dots **⋮** to the right of your Query tab, and clicking “**Save as**”. + **`Fig. 9a`** ![Fig. 9a](../images/prototype-legacy-transforms-nine-a.png) -**`🖱`** When the dialogue pops up, enter the name of your transform query eg. `[my transform].sql` and write a description before clicking the “**Save query**” button. +**`🖮`** When the dialogue pops up, enter a name for your `[transform SQL]` eg. `[transform].sql` and write a description before clicking the “**Save query**” button. + **`Fig. 9b`** ![Fig. 9b](../images/prototype-legacy-transforms-nine-b.png)
@@ -78,28 +86,28 @@ Often the easy way to test your SQL code compatibility is simply to try running #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user +* **AWS Management Console** user * **Amazon Athena** beginner -* `[my service]` Data Analyst -* `[my service database]` user +* Hackney `[service]` Data Analyst +* Hackney `[service database]` user ::: :::note BEHAVIOR -**Measures** the behavior of ***Amazon Athena*** when the user prototypes a transform from a `[legacy SQL query]`. +**Measures** the behavior of ***Amazon Athena*** while users convert there `[legacy SQL query]` into transforms: **Given** in my web browser, I have accessed ***Amazon Athena*** -**~and** I have selected `[my service]` workgroup -**~and** ***Amazon Athena*** shows `[my service raw zone]` with `[my service database]` equivalent tables and columns -**~and** data was previously ingested from `[my service database]` into`[my service raw zone]` -**~and** I have my `[legacy SQL query]` from [my service database] that I want to migrate to **DAP⇨flow** +**~and** I have selected my `[service workgroup]` +**~and** ***Amazon Athena*** shows my `[service raw zone]` with my `[service database]` equivalent tables and columns +**~and** data was previously ingested from my `[service database]` into my `[service raw zone]` +**~and** I have my `[legacy SQL query]` used by my `[service database]` that I now want to migrate to **DAP⇨flow** **When** I copy-and-paste my `[legacy SQL query]` into the query editor **~and** I ensure all the column functions and expressions are made input-and-output-compatible with ***Amazon Athena*** -**~and** I ensure the table names are fully qualified, being prefixed with `[my service raw zone]` instead of `[my service database]` +**~and** I ensure the table names are fully qualified, being prefixed with my `[service raw zone]` instead of my `[service database]` **~and** I click “**Run**” underneath the code window on the left-hand side -**Then** ***Amazon Athena*** should fetch results as would my `[legacy SQL query]` have done when executed upon `[my service database]` -**~and** I can save `[my transform]` with a name `[my transform].sql` and a description in `[my service]` workgroup. +**Then** ***Amazon Athena*** should fetch results as would my `[legacy SQL query]` have done when run by my `[service database]` +**~and** I can save my new `[transform SQL]` with a name `[transform].sql` and a description in my `[service workgroup]`. **Scale** of 4 to 8 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/prototype-simple-transforms.md b/docs/dap-airflow/onboarding/prototype-simple-transforms.md index 96326ff4..5c8448f4 100644 --- a/docs/dap-airflow/onboarding/prototype-simple-transforms.md +++ b/docs/dap-airflow/onboarding/prototype-simple-transforms.md @@ -5,45 +5,49 @@ description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Ana layout: playbook_js tags: [onboarding] --- -# How can I use Amazon Athena to prototype a simple table-join data transformation? +# How can I use ***Amazon Athena*** to prototype a simple table-join data transformation? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access Amazon Athena -**`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. +### 1. Access ***Amazon Athena*** +**`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. -👉 First time Amazon Athena users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** +👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your workgroup -**`🖱`** Ensure you have selected `[my service]` from the list box next to “Workgroup”. +### 2. Select your `[service workgroup]` +**`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 3. Explore your database -**`🖱`** Ensure you have selected `[my service raw zone]` from the list box under "**Database**" on the left side of the Athena interface, before expanding the lists of names under "**► Tables**" or "**► Views**". Expanding those names further should reveal column names with data types, as follows: +### 3. Exploring your `[service raw zone]` database +**`🖱`** Ensure you have selected your `[service raw zone]` from the list box under "**Database**" on the left side of the Athena interface. -* "**▼ Tables**" +**`🖱`** You can then expand the lists under "**`►` Tables**" or "**`►` Views**", then expand each name further to reveal column names and data types, as follows: + +* "**`▼` Tables**" 👉 Documented here ► **[📚My service data history](../onboarding/access-my-service-data-history)** -* "**▼ Views**" +* "**`▼` Views**" 👉 Documented here ► **[📚My current service data](../onboarding/access-my-current-service-data)** -### 4. Understand the data model -**`👁`** Identify which tables and columns you need to use for your data transformation. +### 4. Understanding the data model +**`👁`** Identify which tables and columns you need to use for your data transformation: + +- Wherever you want a `
` originally from your `[service database]` you should be able to find it's name listed under "**`▼` Views**" below your `[service raw zone]` database. -To be clear, where we want a `
` originally from `[my service database]` we will refer to it's equivalent name listed under "**▼ Views**" under the `[my service raw zone]`, in all that follows: +- For a simple simple table-join data transformation you will need: -* You will need a `` with a unique ``. + * The **``** with a unique ``. -* You will need a `` with a unique `` and a foreign key pointing to the `` of the ``. + * The **``** with a unique `` and a foreign key pointing to the `` of the ``. -### 5. Prepare your SQL query +### 5. Prepare your `[transform SQL]` query **`🖱`** You can either: * Start completely from scratch and building up your query in the editor as you go along; -* Or, begin with `[my SQL template]`, eg. **`Fig. 5`**, by copying and pasting it into the query editor. +* Or, begin with a SQL template design, eg. **`Fig. 5`** `[SQL template]`, by *copy-and-pasting* it into the query editor. -**`Fig. 5 [my SQL template]`** +**`Fig. 5`** `[SQL template]` ```sql --- Query will use table names from [my service database]... +-- Query will use table names from my [service database]... SELECT p.import_date AS original_import_date, -- added to my query p., @@ -70,79 +74,85 @@ ORDER BY limit 100; ``` -#### Considerations when using *Amazon Athena* for the first time +#### 💡Considerations when adopting ***Amazon Athena*** for your future SQL development -Migrating to a new technology or platform offers an ideal opportunity to raise standards and shed old coding habits of the past. But you are welcome to skip right to the next section and think about this later... +Migrating to a new technology or platform offers an ideal opportunity to raise coding standards and shed common old habits of the past. * You have complete freedom over the SQL code formatting however we recommend always putting each element, table or column, on its own line. This helps debugging and readability. You should endeavour to be consistent in your style and agree a particular style among your service colleagues. In our examples, we will use 4-space tabulation and use "hard left" nesting, which you are welcome to adopt. -* Nesting has no syntactic significance to SQL interpreters. So a JOIN-clause joins everything previous, not just the previous table, with the table following, and nesting the JOIN-clauses makes no difference to the forward-order of execution. Execution order can only be affected by the use of bracketed sub-queries. The hard-left nesting style, on the other hand, is designed to help the reader be conscious of the execution order above all else. +* Nesting has no syntactic significance to SQL interpreters so its only impact is aesthetic alone. JOIN-clauses join everything previously to the table following, and not just the previous table, so nesting them does change order of execution. Execution order can only be affected by the use of bracketed sub-queries. The hard-left nesting style, on the other hand, is designed to help the reader be conscious of the execution order above all else. * Avoid using lazy cartesian table products without JOIN-clauses in between the tables (or subqueries or CTEs). Likewise avoid using WHERE-clauses to perform cartesian filters and use JOIN-clauses instead. Conversely, Athena does not mind non-cartesian filters within JOIN-clauses and is even recommended where partition-columns are involved because it reduces the quantity of data scanned before any subsequent joins are executed. * Always consider using CTEs in place of subqueries to help debugging and readability. ***Amazon Athena*** permits VALUES table constructors in CTEs allowing replacement of very lengthy WHERE-CASE filters with the more efficient JOIN-CTE filters. ### 6. Customizing a template query -When, for example, using the **`Fig. 5`** template: +When, for example, using the **`Fig. 5`** `[SQL template]`: -**`🖱`** You will need to replace `` and `` placeholders with actual names listed under “**▼ Views**” on the left-hand side of the interface. The Athena editor allows you to insert names directly into the text by simply clicking on the three dots **⋮** to the right of the name, over on the left-hand side, then selecting “insert into editor”. +**`🖱`** You will need to replace the `` and `` template placeholders with actual names listed under “**`▼` Views**” over from the left-hand side of the interface. The Athena editor allows you to insert names directly into the code by simply clicking on the three dots **`⋮`** right of the name, then selecting “***insert into editor***”. **`Fig. 6a`** ![Fig. 6a](../images/prototype-simple-transforms-six-a.png) -**`🖱`** You will need to replace the `` and `` placeholders with corresponding key column names from `[my example]` +**`🖱`** You will need to replace the `` and `` template placeholders with corresponding key column names. **`Fig. 6b`** ![Fig. 6b](../images/prototype-simple-transforms-six-b.png) -**`🖱`** Include all the columns you need. So replace ``, ``, etc. as per the example, with actual column names. - -#### General considerations +**`🖱`** Include all the columns you need. So replace the , placeholders ``, ``, etc., with actual column names. And so on. 👉 If your column expressions require functions, you can check the ***Amazon Athena* documentation ►[here](https://docs.aws.amazon.com/athena/latest/ug/functions.html)**. **`🖱`** Edit your table names to ensure they are fully qualified, as follows: -- Table names should be prefixed by their correct database names, eg. `[my service zone].
`. +- Table names should be prefixed by their correct database names, eg. `[service raw zone].
`. -- ***Amazon Athena***, by default, renders editor-inserted names encapsulated in `"` double-quotes, eg. `“[my service zone]”.“
”`. You don't need to do this! But FYI, the quotes are a safeguard in case of column names containing spaces, even though we never allow that. +- ***Amazon Athena***, by default, renders editor-inserted names encapsulated in `"` double-quotes, eg. `“[service raw zone]”.“
”`. You don't need to do this! But FYI, the quotes are a safeguard in case of column names containing spaces, even though we never allow that. -- The original `[my service database]` database name will not be used by **DAP⇨flow**, so you will need to swap it out with `[my service raw zone]`. +- Your original `[service database]` database name will not be used by **DAP⇨flow**, so you will need to swap it out with your `[service raw zone]`. -- The use of fully-qualified table names means you can use tables from databases elsewhere in the Data Platform. For example, you might want to join your table from your raw-zone database with a table or view from a refined-zone elsewhere. +- Use of fully-qualified table names means you can use tables from databases elsewhere in the Data Platform. For example, you might want to join your table from your `[service raw zone]` database with a table or view from your `[service refined zone]`. -- You must avoid using the following column names in your transform query output because they are reserved by the **DAP⇨flow** implementation when writing your transform output to the S3 data lake partition folders: +- You must avoid using the following column names in your transform query output because they are reserved by the **DAP⇨flow** implementation for writing your transform output to the S3 data lake partition folders: * `import_date` * `import_year` * `import_month` * `import_day` - The **`Fig. 5`** template example shows the column `import_date` renamed as `original_import_date` to avoid that ever being a problem. + The **`Fig. 5`** template example shows the column `import_date` renamed as `original_import_date` which avoids that ever being a problem. - It isn't necessary to output this column in your query but it is good practice to add `original_import_date` to inform users of your transform products about which generation the data came from. + It isn't necessary to output a `original_import_date` column in your query but it is good practice to inform users of your transform products about which generation the data came from. - Because **DAP⇨flow**'s Airflow ingestion can trigger transforms immediately afterward, it natually follows that, the transform output dates will be equal to the import dates of the raw-zone views feeding those transforms. For that reason, you might not want to use `original_import_date` in your transform in production. But if the pipeline trigger logic might cause these dates to diverge in some future use case, then you should consider leaving it in. + Because **DAP⇨flow**'s Airflow ingestion can trigger transforms immediately afterward, it naturally follows that, the transform output dates will be the same as the original import dates. For that reason, you might not want to use `original_import_date` in your transform in production. But if the pipeline trigger logic might cause those dates to diverge in some future use case, then you should consider leaving it in. -* It is recommended to order the output by `` then ``. + **`Fig. 6c`** ![Fig. 6c](../images/prototype-simple-transforms-six-c.png) + +* Here, it is recommended to order the output by `` then ``. + + 💡 Transformed data is written back to S3 in blocks of records organized into separate files collated into folders representing the the S3 partition scheme. Having records written out in a coherent order makes for more efficient scanning or crawling later on. + + **`Fig. 6d`** ![Fig. 6d](../images/prototype-simple-transforms-six-d.png) * Adding a `limit` clause at the end of your query when testing SQL queries in the Athena console normally prevents long-running queries when testing. You will routinely remove the `limit` clause later when your transform goes into production. -**`Fig. 7`** ![Fig. 7](../images/prototype-simple-transforms-seven.png) +### 7. Run your `[transform SQL]` query +**`🖱`** After customizing the SQL code, click “**Run**” or “**Run again**” located underneath the code window on the left side in the Athena interface. -### 7. Run your query -**`🖱`** After customizing the SQL code, click “Run” located underneath the code window on the left side in the Athena interface. +**`Fig. 7`** ![Fig. 7](../images/prototype-simple-transforms-seven.png) ### 8. Review the results -**`👁`** ***Amazon Athena*** should fetch however many rows your SQL `[limit]` clause is set to (eg. `limit 100;` in **`Fig. 5`**). +**`👁`** ***Amazon Athena*** should fetch a number of rows based on your set `[limit]` (eg. `limit 100;` as in the **`Fig. 5`** `[SQL template]`). -* If you included it, the first column `original_import_data` will inform us when the underlying data was ingested from `[my service database]`. If you do not see today’s date then you’ll immediately know that the data ingestion had failed sometime after the date shown, and you should contact the DAP Team to find out what the problem is. But so long as you have data of any given generation you can still test your transform query. +* If you included it, the first column `original_import_data` will inform us when the underlying data was ingested from your `[service database]`. If you do not see today’s date then you’ll immediately know that the data ingestion had failed sometime after the date shown, and you should contact the DAP Team to find out what the problem is. But so long as you have data of any given generation you can still test your transform query. -* The data will be sorted, eg., in the `` + `` order if that is what your `order by` clause says. +* The data should be sorted, eg., in the `` + `` order if that is what your `order by` clause says. -* If your query is based on a `` left-joined to the `` it is possible for the `` and its associated child columns to output NULLs in the place of values, alongside the `` and parent column values. It is worth paying attention to ensure such behavior is the same way as when querying `[my service database]` previously. +* If your query is based on a `` left-joined to the `` it is possible for the `` and its associated child columns to output NULLs in the place of values, alongside the `` and parent column values. It is worth paying attention to ensure such behavior is the same way as when querying your `[service database]` previously. **`Fig. 8`** ![Fig. 8](../images/prototype-simple-transforms-eight.png) -### 9. Save your query -Check you are in the correct `[my service]` workgroup before clicking on the three dots **⋮** to the right of your Query tab, then select “**Save as**”. When the dialogue pops up, enter the name of your transform query eg. `[my transform].sql` and write a description before clicking the “**Save query**” button. +### 9. Save your query as `[transform SQL]` +**`🖱`** Check you are in your correct `[service workgroup]` before clicking on the three dots **⋮** to the right of your Query tab, and clicking “**Save as**”. + +**`🖮`** When the dialogue pops up, enter a name for your `[transform SQL]` eg. `[transform].sql` and write a description before clicking the “**Save query**” button. **`Fig. 9a`** ![Fig. 9a](../images/prototype-simple-transforms-nine-a.png) @@ -165,32 +175,34 @@ Check you are in the correct `[my service]` workgroup before clicking on the thr #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user +* **AWS Management Console** user * ***Amazon Athena*** beginner -* `[my service]` Data Analyst -* `[my service database]` user +* Hackney `[service]` Data Analyst +* Hackney `[service database]` user ::: :::note BEHAVIOR -**Measures** the behavior of ***Amazon Athena*** showing `[my service raw zone]` when the user prototypes a simple transform. +**Measures** the behavior of ***Amazon Athena*** while users prototype simple transforms: **Given** in my web browser, I have accessed ***Amazon Athena*** -**~and** I have selected `[my service]` workgroup -**~and** I have `[my example]` data transformation I want to implement using `[my SQL template]` involving two related tables from `[my service database]` that I want joined to produce a combined output -**~and** `[my example]` has a `` containing a unique `` which is a foreign key in a `` which also with its own unique `` -**~and** ***Amazon Athena*** shows `[my service raw zone]` with `[my service database]` equivalent tables and columns which includes the `` and `` +**~and** I have selected my `[service workgroup]` +**~and** I have my `[example]` data transformation I want to implement using my `[SQL template]` involving two related tables ingested from my`[service database]` that I want joined to produce a combined output +**~and** my `[example]` has a `` containing a unique `` which is a foreign key in a `` which also with its own unique `` +**~and** ***Amazon Athena*** shows my `[service raw zone]` with my `[service database]` equivalent tables and columns which includes the `` and `` +**~and** the *optional* first column output from my `[SQL template]` named `original_import_date` is based on the `import_date` of the `` +**~and** my `[SQL template]` was designed to fetch the first `` rows of data in the order ``+`` **~and** I am familiar with the concepts and basic requirements of writing an ***Amazon Athena*** SQL query -**When** I copy-and-paste `[my SQL template]` into the query editor -**~and** replace the `` and `` placeholders with corresponding table names from `[my example]` -**~and** replace the `` and `` placeholders with corresponding key column names from `[my example]` -**~and** include `, ,..` for each table and column I want to fetch -**~and** click “Run” underneath the code window on the left-hand side +**When** I copy-and-paste my `[SQL template]` into the query editor +**~and** I replace the `` and `` placeholders with corresponding table names from my `[example]` +**~and** replace the `` and `` placeholders with corresponding key column names from my `[example]` +**~and** include `, ,..` using column names from my `[example]` together with *optional* `[SQL template]` columns that I want fetched +**~and** I click “**Run**” underneath the code window on the left-hand side -**Then** ***Amazon Athena*** should fetch the first `` rows of data -**~and** the first column named `original_import_date` will show when the data was ingested from `[my service database]` -**~and** the output data should be sorted in ``+`` order -**~and** I can save my SQL as a working and fully functional transform query with the name `[my transform].sql` and description in `[my service]` workgroup. +**Then** ***Amazon Athena*** should fetch the first `` rows of data sorted in ``+`` order +**~and** the output should comprise the columns I selected +**~and** an *optional* column `original_import_date` would show when the data was ingested from my `[service database]` +**~and** I can save my SQL as a working and fully functional transform query with my name `[transform].sql` and description in my `[service workgroup]`. -**Scale** of 7 to 12 **~and** flow features. +**Scale** of 7 to 14 **~and** flow features. ::: diff --git a/docs/dap-airflow/onboarding/query-my-service-data.md b/docs/dap-airflow/onboarding/query-my-service-data.md index cb5e50b6..9e327a47 100644 --- a/docs/dap-airflow/onboarding/query-my-service-data.md +++ b/docs/dap-airflow/onboarding/query-my-service-data.md @@ -5,24 +5,24 @@ description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Ana layout: playbook_js tags: [onboarding] --- -# How will I query and analyze my service data with Amazon Athena? +# How will I query and analyze my `[service]` data with ***Amazon Athena***? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access Amazon Athena +### 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. 👉 First time Amazon Athena users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your workgroup -**`🖱`** Ensure you have selected `[my service]` from the list box next to “Workgroup”. +### 2. Select your `[service workgroup]` +**`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. ### 3. Explore your database -**`🖱`** Ensure you have selected `[my service raw zone]` from the list box under "**Database**" on the left side of the Athena interface, before expanding the lists under "**► Tables**" and/or "**► Views**. Expandanding further should reveal column names and data types, as follows: +**`🖱`** Ensure you have selected your `[service raw zone]` database from the list box under "**Database**" on the left side of the Athena interface, before expanding the lists under "**`►` Tables**" and/or "**`►` Views**. Expanding further should reveal column names and data types, as follows: - - "**▼ Tables**" + - "**`▼` Tables**" 👉 Documented here ► **[📚My service data history](../onboarding/access-my-service-data-history)** - - "**▼ Views**" + - "**`▼` Views**" 👉 Documented here ► **[📚My current service data](../onboarding/access-my-current-service-data)** ### 4. Familiarize yourself with SQL queries @@ -31,18 +31,18 @@ tags: [onboarding] 👉 You can learn more about using Amazon Athena **►** [**here**](https://docs.aws.amazon.com/athena/latest/ug/using-athena-sql.html) ### 5. Run SQL queries -**`🖱`** Use the SQL query editor in Amazon Athena to write and run queries involving tables and columns equivalent to the original `[my service database]`. +**`🖱`** Use the SQL query editor in ***Amazon Athena*** to write and run queries involving tables and columns equivalent to the your original `[service database]`. **`Fig. 5`** ![Fig. 5](../images/query-my-service-data-five.png) ### 6. Analyze your data -**`👁`** Review the results of your queries to find answers to your questions about `[my service]` data. +**`👁`** Review the results of your SQL queries to find answers to your questions about your `[service database]`. **`Fig. 6`** ![Fig. 6](../images/query-my-service-data-six.png) **`🖱`** You can copy results to the clipboard. -**`🖱`** You can download the results into a CSV file. +**`🖱`** You can download the results into a CSV file.

@@ -60,23 +60,25 @@ tags: [onboarding] #### UX Criteria :::info ABILITY -* Hackney **AWS Management Console** user +* **AWS Management Console** user * **Amazon Athena** user -* `[my service]` Data Analyst -* `[my service database]` user +* Hackney `[service]` Data Analyst +* Hackney `[service database]` user ::: :::note BEHAVIOR -**Measures** the behavior of **Amazon Athena** showing `[my service raw zone]` when the user runs a working SQL query. +**Measures** the behavior of **Amazon Athena** when users' run working SQL queries: + +**Given** in my web browser, I have accessed ***Amazon Athena*** +**~and** I have selected my `[service workgroup]` +**~and** Amazon Athena shows my `[service raw zone]` with my `[service database]` equivalent tables and columns +**~and** I am familiar with the concepts and basic requirements of writing an ***Amazon Athena*** SQL query -**Given** in my web browser, I have accessed **Amazon Athena** -**~and** I have selected `[my service]` workgroup -**~and** Amazon Athena shows `[my service raw zone]` with `[my service database]` equivalent tables and columns -**~and** I am familiar with the concepts and basic requirements of writing an Amazon Athena SQL query **When** I run my SQL query containing given those tables and columns -**Then** I should be able to find answers to my questions about `[my service]` data + +**Then** I should be able to find answers to my questions about my `[service database]` **~and** I can copy results to the clipboard -**~and** I can download the results into a CSV file +**~and** I can download the results into a CSV file **Scale** of 2 to 5 **~and** flow features. ::: From af1be85487ed115ae83d034de27daf6c862e2fbf Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 30 Aug 2024 19:01:00 +0100 Subject: [PATCH 10/16] =?UTF-8?q?Updated=20DAP=E2=87=A8flow=20onboarding?= =?UTF-8?q?=20/=20Committing=20transforms?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/onboarding/github-branch.md | 2 +- .../onboarding/github-commit-transform.md | 29 ++++++++++++++----- 2 files changed, 23 insertions(+), 8 deletions(-) diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index 8f6d7400..5facafc8 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -14,7 +14,7 @@ tags: [onboarding] 👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** -### 2. Access the repository +### 2. Access the `dap-airflow` repository **`🖱`** When you are ready to begin, open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. ### 3. Create `[transform branch]` as your new working branch diff --git a/docs/dap-airflow/onboarding/github-commit-transform.md b/docs/dap-airflow/onboarding/github-commit-transform.md index cc922a2d..8a60c340 100644 --- a/docs/dap-airflow/onboarding/github-commit-transform.md +++ b/docs/dap-airflow/onboarding/github-commit-transform.md @@ -35,9 +35,9 @@ tags: [onboarding] ### 4. Open your `[service dags]/transformations` subfolder on a your `[transform branch]` **`🖱`** Ensure you have created your ![][branch]`[transform branch]` and have it selected. -**`Fig. 4`** ![Fig. 4a](../images/github-commit-transform-four-a.png) +**`Fig. 4a`** ![Fig. 4a](../images/github-commit-transform-four-a.png) -👉 For how to create your `[transform branch]`, **see here ►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** +👉 For how to create your `[transform branch]`, **see here ►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** **`🖱`** In the `[dap-airflow]` repository, navigate to your `dap-airflow/airflow/dags/` **`[service dags]/transformations`** service sub-folder. You can use ***GitHub***’s left-hand navigation pane as follows: * Click on the **`airflow`** folder @@ -68,9 +68,10 @@ tags: [onboarding] **`🖱`** In the ***GitHub*** editor window beneath where it says “**Edit**”, use the right-click menu to "*Paste*" your entire `[transform SQL]` code, from the computer’s clipboard, into your `[transform].sql` file. **`Fig. 7 & 8`** ![Fig. 7 & 8](../images/github-commit-transform-seven-eight.png) -### 8. Review and adjust your `[transform SQL]` code -**`🖱`** Scroll to the bottom of the ***GitHub*** editor window. -**`👁 🖱`** Check for and remove any `limit` clause (e.g., `limit 100`), leaving just the final **`;`** semi-colon at the very end. +### 8. Review and adjust your `[transform SQL]` code +**`🖱`** Scroll to the bottom of the ***GitHub*** editor window to remove any `limit` clause (e.g., `limit 100`), leaving just the final **`;`** semi-colon at the very end. + +**`👁`** If you spot problems in your code you have an opportunity to fix them now, or fix them later. ### 9. Commit your `[transform].sql` file **`🖱`** Click the "**Commit changes**" button to open a dialogue box. @@ -83,6 +84,19 @@ tags: [onboarding] ### 10. Verify the Commit **`👁`**You should see a message confirming your `[transform].sql` was successfully committed directly to your `[transform branch]`. +### 11. Making subsequent changes to `[transform].sql` +Whether you are just fault-fixing or you want to add new SQL code features to your `[transform SQL]`: + +**`🖱`** In the ***GitHub*** editor window beneath where it says “**Edit**”, you can edit your `[transform].sql` file directly. + +**`🖱`** Alternatively, you can use the right-click menu to "*Paste*" a new version of your `[transform SQL]` code, from the computer’s clipboard, into your `[transform].sql` file. + +💡 But unlike regular code editors, ***GitHub*** will not allow you to simply *"Save"* consecutive changes to your code then come back later to finally *commit* your `[transform].sql` with the rest of your `[transform branch]`. Using ***GitHub***'s *web console* in this way absolutely requires you to re-*commit* your `[transform branch]` each and every time you edit or change your files. If you closed your web browser before *committing*, you would lose the edits you did using ***GitHub***'s editor since the previous *commit*. + +👉 After editing `[transform].sql` each time, simply **repeat from ► [step 9](#9-commit-your-transformsql-file)**. + +👉 You may *commit* as often as you need to, until finally, you raise a *pull request*, **here ►** **[DAP⇨flow📚GitHub pull request](../onboarding/github-pull-request)** +

@@ -131,9 +145,10 @@ tags: [onboarding] **~and** I select the option “**Commit directly to my `[transform branch]`** **~and** I click the "**Commit changes**" button -**Then** I should see a message telling me, my `[transform].sql` was successfully committed directly to my `[transform branch]`. +**Then** I should see a message telling me, my `[transform].sql` was successfully *committed* directly to my `[transform branch]` +**~and** I will be permitted to make further edits to my `[transform].sql` followed by *commits* to my to my `[transform branch]`, as often as I need to, until I raise a *pull request* for my `[transform branch]`. -**Scale** of 11 to 19 **~and** flow features. +**Scale** of 12 to 20 **~and** flow features. ::: [branch]: From bbc2b1d2a7acff894a6818315bf3e47e7ca497de Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Fri, 30 Aug 2024 23:31:12 +0100 Subject: [PATCH 11/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20pull=20requests?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../images/github-pull-request-five-six.png | Bin 0 -> 54939 bytes .../images/github-pull-request-four-a.png | Bin 0 -> 122904 bytes .../images/github-pull-request-four-b.png | Bin 0 -> 37201 bytes .../images/github-pull-request-four-c.png | Bin 0 -> 84277 bytes .../images/github-pull-request-three-a.png | Bin 0 -> 72775 bytes .../images/github-pull-request-three-b.png | Bin 0 -> 16842 bytes .../github-pull-request-three-tip-a.png | Bin 0 -> 61150 bytes .../github-pull-request-three-tip-b.png | Bin 0 -> 77025 bytes .../github-pull-request-three-tip-c.png | Bin 0 -> 84054 bytes docs/dap-airflow/introduction.md | 2 +- .../onboarding/github-pull-request.md | 143 ++++++++++++++++++ sidebars.js | 1 + 12 files changed, 145 insertions(+), 1 deletion(-) create mode 100644 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[**Jump to the end**](#to ## Topics arriving here soon... ### Raising pull requests -#### How do I raise a Pull Request to merge my `[transform branch]` into the main trunk of the **DAP⇨flow** repository? +#### How do I *"pull request"* my `[transform branch]` back into the `main` trunk of the **DAP⇨flow** repository? [DPF-146 DOCUMENTATION 4.3 Raise a Pull Request to merge the development branch into the main trunk of the DAP Airflow repository](https://docs.google.com/document/d/1LJjJobb2FVLoadUNCl3R7w9FedTFo8IJWHne-Zw9l-M/edit?usp=drive\_link) ### Merging branches diff --git a/docs/dap-airflow/onboarding/github-pull-request.md b/docs/dap-airflow/onboarding/github-pull-request.md new file mode 100644 index 00000000..739975c8 --- /dev/null +++ b/docs/dap-airflow/onboarding/github-pull-request.md @@ -0,0 +1,143 @@ +--- +id: github-pull-request +title: GitHub pull requests +description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Analytics Platform Airflow integration." +layout: playbook_js +tags: [onboarding] +--- + +# How do I raise a *"pull request"* to merge my `[transform branch]` back into the `main` trunk of **DAP⇨flow**'s `[dap-airflow]` repository? + +![DAP⇨flow](../images/DAPairflowFLOWleft.png) + +### 1. Log into your ***GitHub*** account +**`🖱`** Open your web browser and log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. + +👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** + +### 2. Access the `dap-airflow` repository +**`🖱`** When you are ready, open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. + +### 3. Switch to your working `[transform branch]` + +👉 If you haven't yet created your `[transform branch]` then **see here** how to do that **►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** + +**`🖱`** Select the "**Code**" tab at the top of the repository page. +**`Fig. 3a`** ![Fig. 3a](../images/github-pull-request-three-a.png) +**`🖱`** Click the `▼`dropdown button next to ![][branch]`main`. +**`🖮`** Start typing your `[transform branch]` name. +**`🖱`** Find and select your `[transform branch]` from the menu below. + +**`Fig. 3b`** ![Fig. 3b](../images/github-pull-request-three-b.png) +**`👁`** Your **![][branch]`[transform branch]`** should reappear next to the `▼`dropdown button. + +👉 If you've yet to commit your `[transform SQL]` to your `[transform branch]` then check back **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** + +:::tip But how will I know? + +Let's assume you set up your `[transform branch]` earlier but then you got distracted so, now, you are not certain if you actually *committed* your `[transform SQL]` to a `[transform].sql` file. + +#### So, how will you know if you did or you didn't? + +Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio Code*** can quickly pull up a *Git Graph* to simply find out. But what if you only have ***GitHub***'s web interface available, because you are on a Chromebook or you don't have a local copy of the repository? + +**Then here's a neat trick for you!** +(You must be [logged into your ***GitHub*** account](#1-log-into-your-github-account) for this) + +**`🖱`** Use the following link to open a separate new tab in your web browser: +**[`https://github.com/LBHackney-IT/dap-airflow/activity?ref=[transform branch]`](https://github.com/LBHackney-IT/dap-airflow/activity?ref=transform%20branch)** + +**`🖮`** Then replace all the text immediately after `ref=` with the name of your `[transform branch]` before hitting *Enter*. +![Fig. 3-tip-a](../images/github-pull-request-three-tip-a.png) + +**`👁`** Then below, ***GitHub*** should appear with your **![][branch]`[transform branch]`** showing. +![Fig. 3-tip-b](../images/github-pull-request-three-tip-b.png) +**`👁`** If, below that, you get the message "**No activity matched your search**" then you can be certain you never actually *committed* a `[transform].sql` file. + +👉 If you did not *commit* your `[transform SQL]` to your `[transform branch]` then check back **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** + +**`👁`** Otherwise, you should see a list of one-or-more *commits* to your `[transform branch]`. + +**`🖱`** But if you are not sure about those, then you can click on `…` after each *commit message* and select "**Compare changes**" +![Fig. 3-tip-c](../images/github-pull-request-three-tip-c.png) +**`👁`** Then, on the next screen you will be presented with a list of changes that should remind you what you actually did! + +👉 If you are not sure you have properly *committed* your `[transform SQL]` to your `[transform branch]` then you should retrace your steps **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** + +::: + +### 4. Create your *pull request* +**`🖱`** Select the "**Pull requests**" tab at the top of the repository page. +**`Fig. 4a`** ![Fig. 4a](../images/github-pull-request-four-a.png) +**`🖱`** Click the "**New pull request**" button on the right. + +**`🖱`** Set the `base:` branch to the **`main`** trunk. +**`Fig. 4b`** ![Fig. 4b](../images/github-pull-request-four-b.png) +**`🖱`** Set the `compare:` branch to your **`[transform branch]`**. + +**`🖱`** Click the "**Create pull request**" button. +**`Fig. 4c`** ![Fig. 4c](../images/github-pull-request-four-c.png) + +### 5. Add the details to your *pull request* +**`🖮`** Enter a title for your *pull request*. +**`🖮`** Add a description explaining the changes you have made. + +**`Fig. 5 & 6`** ![Fig. 5 & 6](../images/github-pull-request-five-six.png) + +### 6. Submit your *pull request* +**`🖱`** Click the "**Create pull request**" button below the description on the right. + +***GitHub*** should begin the process of pulling your **`[transform branch]`** into the `main` trunk or the `dap-airflow` repository: +**`✉`** You will be sent an email to confirm that. +**`✉`** A *pull request* email will be sent to the **DAP Platform Team** to notify them of your request. + +
+
+ +--- +## ***"We* ♡ *your feedback!"*** +![DAP⇨flow](../images/DAPairflowFLOWleft.png) +:::tip UX +👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-pull-request**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-pull-request) +- Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. +- We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. +- We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. +☝ **Please use this link to help us understand your user experience!** +::: + +#### UX Criteria +:::info ABILITY +* Hackney **Google Workspace** user +* Hackney `[service]` Data Analyst +* ***GitHub*** beginner +::: + +:::note BEHAVIOR +**Measures** the ***GitHub*** and `dap-airflow` repository behavior: + +**Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication +**~and** I am granted membership of **[London Borough of Hackney](https://github.com/LBHackney-IT) organization** on ***GitHub*** incorporating the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) private repository +**~and** I previously *committed* my `[transform].sql` file, containing my `[transform SQL]`, to my current **`[transform branch]`** +**~and** I have not previously raised a *pull request* on my **`[transform branch]`** + +**When** I access the [`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow) repository +**~and** I select the "**Code**" tab at the top of the repository page +**~and** below that, I click on the "**![][branch]`main`**" `▼`dropdown button +**~and** I begin typing my **`[transform branch]`** +**~and** below that, I select my **`[transform branch]`** so that my **![][branch]`[transform branch]`** reappears above next to the `▼`dropdown button +**~and** I select the "**Pull requests**" tab at the top of the repository page +**~and** I click the "**New pull request**" button over on the right +**~and** I set the `base:` branch to the **`main`** trunk +**~and** I set the `compare:` branch my **`[transform branch]`** +**~and** I click on the "Create pull request" button +**~and** I add a *title* for my pull request and a *description* explaining the changes I have made +**~and** below on the right, I click the "**Create pull request**" button + +**Then** ***GitHub*** should begin the process of pulling my **`[transform branch]`** into the `main` trunk or the `dap-airflow` repository +**~and** I will be sent an email confirming that +**~and** a *pull request* email will be sent to the **DAP Platform Team**. + +**Scale** of 13 to 16 **~and** flow features. +::: + +[branch]: diff --git a/sidebars.js b/sidebars.js index fd54ccff..8d4ccc0d 100644 --- a/sidebars.js +++ b/sidebars.js @@ -139,6 +139,7 @@ module.exports = { "dap-airflow/onboarding/github-access", "dap-airflow/onboarding/github-branch", "dap-airflow/onboarding/github-commit-transform", + "dap-airflow/onboarding/github-pull-request", ], }, ], From 0c2ebcf54b9800a33d02db7b388f410740617eb1 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Sat, 31 Aug 2024 00:32:58 +0100 Subject: [PATCH 12/16] =?UTF-8?q?Added=20DAP=E2=87=A8flow=20onboarding=20/?= =?UTF-8?q?=20GitHub=20pull=20requests?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/introduction.md | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index bffd8356..bccda720 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -82,11 +82,10 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### [Committing transforms](../dap-airflow/onboarding/github-commit-transform) #### How do I commit my working `[transform SQL]` to **DAP⇨flow**'s repository? -## Topics arriving here soon... +### [GitHub pull requests](../dap-airflow/onboarding/github-pull-request) +#### How do I raise a *"pull request"* to merge my `[transform branch]` into the `main` trunk of the **DAP⇨flow** repository? -### Raising pull requests -#### How do I *"pull request"* my `[transform branch]` back into the `main` trunk of the **DAP⇨flow** repository? -[DPF-146 DOCUMENTATION 4.3 Raise a Pull Request to merge the development branch into the main trunk of the DAP Airflow repository](https://docs.google.com/document/d/1LJjJobb2FVLoadUNCl3R7w9FedTFo8IJWHne-Zw9l-M/edit?usp=drive\_link) +## Topics arriving here soon... ### Merging branches #### How do i complete the merge of `[transform branch]` into the main trunk of **DAP⇨flow**'s repository? 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zn!g&<5V<)NfCn}Ia&7zv0=XwJv*;uY{a*&h>!hzfye6GBC*M4(Jv&EE-s}%gvvGeW cXIi Date: Sun, 1 Sep 2024 00:48:38 +0100 Subject: [PATCH 14/16] =?UTF-8?q?Updated=20DAP=E2=87=A8flow=20onboarding?= =?UTF-8?q?=20/=20UX?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/introduction.md | 37 ++++--- .../access-my-Amazon-Athena-database.md | 19 ++-- .../access-my-current-service-data.md | 23 ++-- .../access-my-service-data-history.md | 21 ++-- .../access-the-AWS-Management-Console.md | 19 ++-- .../onboarding/access-the-AWS-region.md | 19 ++-- docs/dap-airflow/onboarding/begin.md | 21 ++-- docs/dap-airflow/onboarding/github-access.md | 27 ++--- docs/dap-airflow/onboarding/github-branch.md | 17 +-- .../onboarding/github-commit-transform.md | 29 ++--- .../onboarding/github-pull-request.md | 100 ++++++++++-------- .../onboarding/prototype-legacy-transforms.md | 27 ++--- .../onboarding/prototype-simple-transforms.md | 60 ++++++----- .../onboarding/query-my-service-data.md | 23 ++-- docs/dap-airflow/ux.md | 68 ++++++++++++ sidebars.js | 1 + 16 files changed, 324 insertions(+), 187 deletions(-) create mode 100644 docs/dap-airflow/ux.md diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index bccda720..b3b638c6 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -1,27 +1,33 @@ --- id: introduction -title: Introduction +title: 📚Introduction description: "The DAP⇨flow guide for data analysts and engineers, for developing and deploying Airflow DAGs, running data pipelines in the Data Analytics Platform (DAP)." layout: playbook_js tags: [dap-airflow] --- -# Introduction +# 📚Introduction ![DAP⇨flow](../dap-airflow/images/DAPairflowFLOWwide.png) ## What is **DAP⇨flow**? **DAP⇨flow** is an integation of ***Apache Airflow*** with ***Amazon Athena*** built upon Hackney's ***Data Analytics Platform***. #### It allows Data Analysts, in the simplest way possible, to develop and run data pipelines using their own service's data and create data products for their service and service users. -Building data pipelines used to be harder and more complex and time consuming. Data Analysts after prototyping their SQL queries using ***Amazon Athena*** were required to convert Athena SQL code to Spark SQL, a different SQL dialect, then embed their code within an ***Amazon Glue*** job which they had be deployed using ***Terraform***. +Building data pipelines used to be harder and more complex and time consuming. -They also had to negotiate querying across multiple generations of the same data stored in the ***Amazon S3*** Data lake. That meant they could not simply take a legacy SQL query and run it in ***Amazon Athena*** or create an ***Amazon Glue*** product directly from it. +Data Analysts, after prototyping their SQL queries using ***Amazon Athena*** were required to convert *Athena SQL* code to *Spark SQL*, a different SQL dialect, then embed their code within an ***Amazon Glue*** job which they had to deploy using ***Terraform***. + +Data Analysts were forced to query across multiple generations of the same data stored in the ***Amazon S3*** Data lake when al they actually wanted was their current data. That meant they could not simply take a legacy SQL query and run it in ***Amazon Athena*** or create an ***Amazon Glue*** product directly from it. #### How **DAP⇨flow** solves these problems -* Firstly, Data Analysts no longer need to convert and re-test their prototype SQL transforms to run in a seperate and more complex ***Amazon Glue*** run-time environment. Instead, ***Apache Airflow*** uses ***Amazon Athena*** to automate and generate data transform products using the original, already tested and working, prototype SQL code. +* Firstly, Data Analysts no longer need to convert and re-test their prototype SQL transforms to run in the separate and more complex ***Amazon Glue*** run-time environment. + + Instead, ***Apache Airflow*** can use exactly the same ***Amazon Athena*** to transform data in production with the outputs going directly into data products. So that Data Analysts' prototype SQL transform queries, that they spent time on testing until they were working, can simply be reused instead of being discarded. **That cuts development time by more than half while Data Analysts no longer need to context-switch between the two SQL dialects.** -* Secondly, Data Analysts no longer must adapt their SQL queries to ***Amazon S3***'s Data Lake partitioning architecture, because ***Apache Airflow*** is configured to generate views of the underlying table data to present Data Analysts with current-only ingested service data, both in readiness for prototyping and testing, and for when the working transforms are subsequently deployed, being automated and run by Airflow. +* Secondly, Data Analysts no longer must adapt their legacy SQL queries to ***Amazon S3***'s Data Lake partitioning architecture. + + Instead, ***Apache Airflow*** is configured to generate views of the underlying table data to present Data Analysts with current-only ingested service data, both in readiness for prototyping and testing, and for when the working transforms are subsequently deployed, being automated and run by Airflow. **That further cuts development time while Data Analysts can very easily take the legacy SQL code from their service database system and run it directly on *Amazon Athena* with few changes.** @@ -42,9 +48,8 @@ Data Analysts are encouraged to think about what they need to do before deciding #### ***"We* ♡ *your feedback!"*** Your continuous feedback enables us to improve **DAP⇨flow** and our ***Data Analytics Platform*** service. Survey links are provided at the end of each onboarding document. -#### Here below, is the full list of topics currently on offer... - -Further documents will be added as they are developed. [**Jump to the end**](#topics-arriving-here-soon) to discover what is coming next! +#### **Below here, is the full list of topics currently on offer...** +And more topics will be added as they are ready. [**Skip to the end**](#coming-soon) to discover what's coming next! ### [Before you begin](../dap-airflow/onboarding/begin) #### What must happen before I can begin **DAP⇨flow**? @@ -59,13 +64,13 @@ Further documents will be added as they are developed. [**Jump to the end**](#to #### How will I use ***Amazon Athena*** to access my database? ### [My current service data](../dap-airflow/onboarding/access-my-current-service-data) -#### How will I access my current service data from ***Amazon Athena***? +#### How will I access my `[service]`'s current data from ***Amazon Athena***? ### [My service data history](../dap-airflow/onboarding/access-my-service-data-history) -#### How will I access my service data history from ***Amazon Athena***? +#### How will I access my `[service]`'s data history from ***Amazon Athena***? ### [Query my service data](../dap-airflow/onboarding/query-my-service-data) -#### How will I query and analyze my service data with ***Amazon Athena***? +#### How will I query and analyze my `[service]`'s data with ***Amazon Athena***? ### [Prototype simple transforms](../dap-airflow/onboarding/prototype-simple-transforms) #### How can I use ***Amazon Athena*** to prototype a simple table-join data transformation? @@ -74,7 +79,7 @@ Further documents will be added as they are developed. [**Jump to the end**](#to #### How do I use ***Amazon Athena*** to prototype a data transformation from my `[legacy SQL query]`? ### [GitHub access](../dap-airflow/onboarding/github-access) -#### How do I set up my ***GitHub*** access to **DAP⇨flow**? +#### How do I set up my ***GitHub*** access for **DAP⇨flow**? ### [GitHub branching](../dap-airflow/onboarding/github-branch) #### How do I create `[transform branch]` as my new working branch of **DAP⇨flow**'s repository? @@ -85,7 +90,8 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### [GitHub pull requests](../dap-airflow/onboarding/github-pull-request) #### How do I raise a *"pull request"* to merge my `[transform branch]` into the `main` trunk of the **DAP⇨flow** repository? -## Topics arriving here soon... +## 📚Coming soon... +The following guides are due for completion. ### Merging branches #### How do i complete the merge of `[transform branch]` into the main trunk of **DAP⇨flow**'s repository? @@ -96,7 +102,8 @@ Further documents will be added as they are developed. [**Jump to the end**](#to ### Adding tables to the raw-zone #### How do i add a new table ingestion to my `[service raw-zone]` database? -## Topics suggested for the later... +## 📚Suggested for later... +The following guides are on our backlog. #### Migrating old Athena prototype SQL to the new **DAP⇨flow** diff --git a/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md b/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md index cfeaf553..40c9329e 100644 --- a/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md +++ b/docs/dap-airflow/onboarding/access-my-Amazon-Athena-database.md @@ -8,27 +8,27 @@ tags: [onboarding] # How will I use ***Amazon Athena*** to access my database? -### 1. Access the ***AWS Management Console*** +## 1. Access the ***AWS Management Console*** **`🖱`** In your web browser, log in to your AWS account to access the ***AWS Management Console***. 👉 First time AWS Users should **start here ►** **[DAP⇨flow📚AWS Console access](../onboarding/access-the-AWS-Management-Console)** -### 2. Familiarize yourself with the console +## 2. Familiarize yourself with the console **`👁`** Take a moment to get comfortable with the layout and check out options available in the ***AWS Management Console*** interface. **`Fig. 2 & 3`** ![Fig. 2 & 3](../images/access-my-Amazon-Athena-database-two-three.png) -### 3. Open ***Amazon Athena*** +## 3. Open ***Amazon Athena*** **`🖱`** Locate and open ***Amazon Athena*** from the services menu. -### 4. Select your `[service workgroup]` +## 4. Select your `[service workgroup]` **`👁`** Look to the top right corner of the ***Amazon Athena*** interface, next to "**Workgroup**". **`🖱`** From the list box there, click on **`▼`** to select your `[service workgroup]`. **`Fig. 4 & 5`** ![Fig. 4 & 5](../images/access-my-Amazon-Athena-database-four-five.png) -### 5. Select your `[service raw zone]` database +## 5. Select your `[service raw zone]` database **`👁`** On the left side of the ***Amazon Athena*** interface, below the "**Database**" section, find the list box and check you can already see your `[service raw zone]` database. **`🖱`** If you don't see it there, then simply click on **`▼`** to select your `[service raw zone]` database from the list box. @@ -37,15 +37,17 @@ tags: [onboarding] ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-Amazon-Athena-database**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-Amazon-Athena-database) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-Amazon-Athena-database**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-Amazon-Athena-database) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * **AWS Management Console** user * Hackney `[service]` Data Analyst @@ -53,6 +55,7 @@ tags: [onboarding] ::: :::note BEHAVIOR +### How will I use ***Amazon Athena*** to access my database? **Measures** the behavior of **Amazon Athena** when first run and configured by the user: **Given** in my web browser, I have access to the ***AWS Management Console*** diff --git a/docs/dap-airflow/onboarding/access-my-current-service-data.md b/docs/dap-airflow/onboarding/access-my-current-service-data.md index b7acede4..3abd46eb 100644 --- a/docs/dap-airflow/onboarding/access-my-current-service-data.md +++ b/docs/dap-airflow/onboarding/access-my-current-service-data.md @@ -6,17 +6,17 @@ layout: playbook_js tags: [onboarding] --- -# How will I access my current service data from ***Amazon Athena***? +# How will I access my `[service]`'s current data from ***Amazon Athena***? -### 1. Access ***Amazon Athena*** +## 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. 👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your `[service raw zone]` database +## 2. Select your `[service raw zone]` database **`🖱`** Ensure that you have selected your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. -### 3. Explore the views in your database +## 3. Explore the views in your database **`🖱`** Beneath the "**Database**" section on the left of the Athena interface and below the "**`▼` Tables**” section (collapsed when clicking **`▼`**→“**`►` Tables**”), expand the “**`►` Views**" section (clicking **`►`**→“**`▼` Views**”) to find a list of views based on tables available from your `[service raw zone]` database. * **DAP⇨flow** implements Athena databases that present users with views that show only current-generation data, based upon their underlying history-table counterparts. So Data Analysts can ignore the history in the S3 data lake and instead write much simpler transformations resembling the queries of your original `[service database]`. @@ -27,17 +27,17 @@ tags: [onboarding] **`Fig. 2, 3, 4 & 5`** ![Fig. 2, 3, 4 & 5](../images/access-my-current-service-data-two-five.png) -### 4. Expand each view +## 4. Expand each view **`🖱`** Navigating beneath “**`▼` Views**”, click on each view name to expand it and observe the complete list of columns in that view. -### 5. Verify the views and columns +## 5. Verify the views and columns **`👁`** Compare each view and its columns with the equivalent table and columns from your `[service database]` to observe how their names and data types match up with their counterparts. * Occasionally the automatic data type translation will yield unexpected results. Always check columns to ensure there will never be any data lost. For example, if integer precision is lost. * Be specially aware of *date* translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially when used in comparison, or used to join *date* columns from tables elsewhere. -### 6. Observe the partition columns +## 6. Observe the partition columns **`🖱`** Scroll to the bottom of the column list to find the partition scheme derived from the underlying history table. This will comprise four or more columns shown with the partition data type alongside eg. **`string`** But unlike its table counterpart in the section above, the view will actually not show **`(Partitioned)`**. **`Fig. 6`** ![Fig. 6](../images/access-my-current-service-data-six.png) @@ -49,15 +49,17 @@ tags: [onboarding] ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-current-service-data**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-current-service-data) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-current-service-data**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-current-service-data) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * ***AWS Management Console*** user * Hackney `[service]` Data Analyst @@ -66,6 +68,7 @@ tags: [onboarding] ::: :::note BEHAVIOR +### How will I access my `[service]`'s current data from ***Amazon Athena***? **Measures** the behavior of **Amazon Athena** as users explore their `[service raw zone]` database views and columns: **Given** I have selected my `[service raw zone]` database in the ***Amazon Athena*** interface diff --git a/docs/dap-airflow/onboarding/access-my-service-data-history.md b/docs/dap-airflow/onboarding/access-my-service-data-history.md index f95c8504..e076e98c 100644 --- a/docs/dap-airflow/onboarding/access-my-service-data-history.md +++ b/docs/dap-airflow/onboarding/access-my-service-data-history.md @@ -8,12 +8,12 @@ tags: [onboarding] # How will I access my `[service]`'s data history from ***Amazon Athena***? -### 1. Access ***Amazon Athena*** +## 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. 👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Understanding your `[service raw zone]` database +## 2. Understanding your `[service raw zone]` database **`🖱`** Ensure you have selected your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. **`Fig. 2 & 3`** ![Fig. 2 & 3](../images/access-my-service-data-history-two-three.png) @@ -27,26 +27,26 @@ tags: [onboarding] 👉 For more information on how Amazon S3 organizes data, see ►[**here**](https://docs.aws.amazon.com/AmazonS3/latest/userguide/organizing-objects.html) -### 3. Explore the tables in your database +## 3. Explore the tables in your database **`🖱`** Beneath the "**Database**" section on the left of the Athena interface, expand the "**`►` Tables**" section to find the list of tables available from your `[service raw zone]` database. * This is how Athena presents tables from the S3 data lake. In S3’s folder structure, tables are represented by folders below the service database folder. * In this implementation, the table names were all suffixed `..._history` to remind us that each table contains several daily generations of data stretching back in time. -### 4. Expanding each table +## 4. Expanding each table **`🖱`** Click on each table name to expand it and observe the complete list of columns for that table. **`Fig. 4 & 5`** ![Fig. 4 & 5](../images/access-my-service-data-history-four-five.png) -### 5. Verifying the views and columns +## 5. Verifying the views and columns **`👁`** Compare each table and its columns with the equivalent table and columns from your `[service database]` to observe how their names and data types match up with their counterparts. * Occasionally the automatic data type translation will yield unexpected results. Always check columns to ensure there will never be any data lost. For example, if integer precision is lost. * Be especially aware of *date* translations. Dates are sometimes transmitted in specialized formats, possibly numerical or possibly textual. If we’re unlucky these might need some coded reconciliation afterwards to make them both readable and useful in computations, especially when used in comparison, or used to join *date* columns from tables elsewhere. -### 6. Observing the partition columns +## 6. Observing the partition columns **`🖱`** Scroll to the bottom of the column list to find the partition scheme. This will comprise three, or four, or more partition columns shown with the partition data type alongside eg. **`string (Partitioned)`**. **`Fig. 6`** ![Fig. 6](../images/access-my-service-data-history-six.png) @@ -72,15 +72,17 @@ It helps to become familiar with the fundamental differences between a tradition ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-service-data-history**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-service-data-history) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-my-service-data-history**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-my-service-data-history) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * **AWS Management Console** user * Hackney `[service]` Data Analyst @@ -89,6 +91,7 @@ It helps to become familiar with the fundamental differences between a tradition ::: :::note BEHAVIOR +### How will I access my `[service]`'s data history from ***Amazon Athena***? **Measures** the behavior of **Amazon Athena** while users explore their `[service raw zone]` database tables and columns: **Given** I selected my `[service raw zone]` database in the ***Amazon Athena*** interface diff --git a/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md b/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md index 6963f6ba..7e33274e 100644 --- a/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md +++ b/docs/dap-airflow/onboarding/access-the-AWS-Management-Console.md @@ -9,23 +9,23 @@ tags: [onboarding] # How will I access the ***AWS Management Console***? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Log into your **Hackney Council** Google Account +## 1. Log into your **Hackney Council** Google Account **`🖱`** Always start by logging into your **Hackney Council** Google account. -### 2. Open the AWS access portal +## 2. Open the AWS access portal **`🖱`** In your web browser, navigate to the **[AWS access portal](https://d-936715b9ec.awsapps.com/start\#/)**. -### 3. Expand the AWS accounts +## 3. Expand the AWS accounts **`🖱`** If you were granted access to **Hackney Council's** ***AWS Management Console*** then you should be able to locate and fully expand the "**DataPlatform-Pre-Production**" section under “**AWS accounts**”. **`Fig. 3 & 4`** ![Fig. 3 & 4](../images/access-the-AWS-Management-Console-three-four.png) -### 4. Locate Your service role +## 4. Locate Your service role **`🖱`** Below "**DataPlatform-Pre-Production**", find your `[service role]` listed. 👉 If you do not know your `[service role]`, **please check here** to ensure you were properly set up to use the ***AWS Management Console*** ►** **[DAP⇨flow📚Before you begin](../onboarding/begin)** -### 5. Access the ***AWS Management Console*** +## 5. Access the ***AWS Management Console*** **`🖱`** Click on your `[service role]` to access the Data Platform AWS Management Console. * You may need to accept cookies and respond to service messages. * You may see errors caused by the AWS region not set correctly. @@ -42,19 +42,22 @@ tags: [onboarding] ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-the-AWS-Management-Console**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-the-AWS-Management-Console) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-the-AWS-Management-Console**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-the-AWS-Management-Console) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user ::: :::note BEHAVIOR +### How will I access the ***AWS Management Console***? **Measures** the ***AWS Management Console*** behavior: **Given** in my web browser, I am logged into my **Hackney Council Google account** diff --git a/docs/dap-airflow/onboarding/access-the-AWS-region.md b/docs/dap-airflow/onboarding/access-the-AWS-region.md index 664ebcae..484a6ff9 100644 --- a/docs/dap-airflow/onboarding/access-the-AWS-region.md +++ b/docs/dap-airflow/onboarding/access-the-AWS-region.md @@ -6,28 +6,28 @@ layout: playbook_js tags: [onboarding] --- -# How will I ensure I am in the correct AWS region? +# How will I ensure I am in the correct AWS region? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) You will need to check the region you are in, usually the first time you access the AWS Management Console. Thereafter your web browser will remember the region you last used so you should not need to check this very often. -### 1. Access the ***AWS Management Console*** +## 1. Access the ***AWS Management Console*** **`🖱`** In your web browser, log in to your AWS account to access the ***AWS Management Console***. 👉 First time AWS Users should **start here ►** **[DAP⇨flow📚AWS Console access](../onboarding/access-the-AWS-Management-Console)** -### 2. Locate the Region Selector +## 2. Locate the Region Selector **`👁`** At the top of the console, locate the region selector **`▼`**. **`Fig. 2`** ![Fig. 2](../images/access-the-AWS-region-two.png) -### 3. Select Your Region +## 3. Select Your Region **`🖱`** Click on the **`▼`** arrow to open the region menu. **`🖱`** From the list that appears, choose **`Europe (London) eu-west-2`** as your region. **`Fig. 3 & 4`** ![Fig. 3 & 4](../images/access-the-AWS-region-three-four.png) -### 4. Verify the Selected Region +## 4. Verify the Selected Region **`👁 `** After selecting your region, you should see **`London ▼`** displayed at the top of the console, confirming that you have successfully changed the region.
@@ -38,19 +38,22 @@ You will need to check the region you are in, usually the first time you access ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-the-AWS-region**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-the-AWS-region) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / access-the-AWS-region**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=access-the-AWS-region) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user ::: :::note BEHAVIOR +### How will I ensure I am in the correct AWS region? **Measures** the ***AWS Management Console*** behavior: **Given** I have accessed the ***AWS Management Console*** diff --git a/docs/dap-airflow/onboarding/begin.md b/docs/dap-airflow/onboarding/begin.md index 14c8f602..ed7084de 100644 --- a/docs/dap-airflow/onboarding/begin.md +++ b/docs/dap-airflow/onboarding/begin.md @@ -9,28 +9,28 @@ tags: [onboarding] # What must happen before I can begin DAP⇨flow? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Is your `[service]`’s data now available on the Data Analytics Platform (DAP)? +## 1. Is your `[service]`’s data now available on the Data Analytics Platform (DAP)? Your `[service]` manager or the **DAP Platform Team** will have told you about this. -### 2. Are you using your **Hackney Council** Google Account? +## 2. Are you using your **Hackney Council** Google Account? You’ll always need to be logged into your **Hackney Council** Google account via your web browser when following the **DAP⇨flow** onboarding tasks. -### 3. Your manager must add you to the DAP Access Google Group +## 3. Your manager must add you to the DAP Access Google Group Ask your `[service]` manager to add your name to the [DAP Access Google Group](https://support.google.com/groups/answer/2465464?hl=en), aka your `[service workgroup]`. Your manager may need to contact the **DAP Platform Team** if this is their first time adding someone to the group. -### 4. Access granted! +## 4. Access granted! Once your name is added, you will be granted - appropriate access to the [Hackney Council AWS Console](https://d-936715b9ec.awsapps.com/start/#/?tab=accounts). - membership of the **☎️DAP⇨flow Hotline** Google Chat Space. -### 5. You’ll receive an email, welcoming you to **DAP⇨flow** +## 5. You’ll receive an email, welcoming you to **DAP⇨flow** Check for an email from the **DAP Platform Team** welcoming you to the DAP. This email will present you with the following information needed to begin using the **DAP⇨flow** and while following the **📚Onboarding** documentation: - Your `[service workgroup]` confirming your workgroup in ***Amazon Athena*** and other places - Your `[service role]` needed to access the ***AWS Management Console*** - Your `[service raw zone]` as the database where you will find your ingested data - Your `[service database]` confirming where your data actually came from -### 6. Check out the links in your email +## 6. Check out the links in your email You will be directed and encouraged to use the following **DAP⇨flow** resources linked in the email: 👉 [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE/w4EMQuK-9QA/w4EMQuK-9QA?cls=10) @@ -55,20 +55,23 @@ You will be directed and encouraged to use the following **DAP⇨flow** resource ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / begin**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=begin) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / begin**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=begin) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user * Hackney `[service]` Data Analyst ::: :::note BEHAVIOR +### What must happen before I can begin DAP⇨flow? **Measures** the **DAP Platform Team** behavior and the agency of the `[service]` manager: **Given** my `[service]` was already set up as a [**DAP department**](https://playbook.hackney.gov.uk/Data-Platform-Playbook/playbook/getting-set-up/onboarding-new-departments-to-the-platform) diff --git a/docs/dap-airflow/onboarding/github-access.md b/docs/dap-airflow/onboarding/github-access.md index a3d454e8..79011037 100644 --- a/docs/dap-airflow/onboarding/github-access.md +++ b/docs/dap-airflow/onboarding/github-access.md @@ -6,31 +6,30 @@ layout: playbook_js tags: [onboarding] --- -# How do I set up my ***GitHub*** to access DAP⇨flow's repository? +# How do I set up my ***GitHub*** access for **DAP⇨flow**? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. So you're a DAP⇨flow user, and you're ready to go? +## 1. So you're a DAP⇨flow user, and you're ready to go? 👉 Check you did everything **here ►** **[DAP⇨flow📚Before you begin](../onboarding/begin)** 👉 Have you introduced yourself? **Here ►** [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE/w4EMQuK-9QA/w4EMQuK-9QA?cls=10) - - -### 2. You'll need a ***GitHub*** Account + +## 2. You'll need a ***GitHub*** Account 👉 When creating your ***GitHub*** account you must use your ***Hackney email address***. **Go here ►** [**github.com**](https://github.com/) -### 3. Set Up Two-Factor Authentication +## 3. Set Up Two-Factor Authentication 👉 Follow the steps to configure two-factor authentication for your ***GitHub*** account **here ►** [**GitHub 2-factor authentication for added security**](https://docs.github.com/en/authentication/securing-your-account-with-two-factor-authentication-2fa/configuring-two-factor-authentication) -### 4. Request Access to the `dap-airflow` repo +## 4. Request Access to the `dap-airflow` repo 👉 Use the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space to request collaborator access to **DAP⇨flow**'s private repository called `dap-airflow`. **`Fig. 4`** ![Fig. 4](../images/github-access-four.png) -### 5. Access request granted +## 5. Access request granted The **DAP Platform Team** will 👉 * Acknowledge your request and continue to update your status via a reply-thread on the [☎️DAP⇨flow Hotline](https://chat.google.com/room/AAAAZYTZYPE?cls=7). @@ -50,17 +49,20 @@ The **DAP Platform Team** will 👉
--- -## ***"We* ♡ *your feedback!"*** +## ***"We* ♡ *your feedback!"*** + ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-access**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-access) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-access**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-access) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user * Hackney `[service]` Data Analyst @@ -68,6 +70,7 @@ The **DAP Platform Team** will 👉 ::: :::note BEHAVIOR +### How do I set up my ***GitHub*** access for **DAP⇨flow**? **Measures** the **DAP Platform Team** behavior: **Given** I am member of the [**☎️DAP⇨flow Hotline**](https://chat.google.com/room/AAAAZYTZYPE?cls=7) Google Chat Space diff --git a/docs/dap-airflow/onboarding/github-branch.md b/docs/dap-airflow/onboarding/github-branch.md index 5facafc8..2d70562f 100644 --- a/docs/dap-airflow/onboarding/github-branch.md +++ b/docs/dap-airflow/onboarding/github-branch.md @@ -9,15 +9,15 @@ tags: [onboarding] # How do I create `[transform branch]` as my new working branch of **DAP⇨flow**'s `[dap-airflow]` repository? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Log into your ***GitHub*** account +## 1. Log into your ***GitHub*** account **`🖱`** Open your web browser and log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. 👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** -### 2. Access the `dap-airflow` repository +## 2. Access the `dap-airflow` repository **`🖱`** When you are ready to begin, open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. -### 3. Create `[transform branch]` as your new working branch +## 3. Create `[transform branch]` as your new working branch **`🖱`** Select the "**Code**" tab at the top of the repository page @@ -29,7 +29,7 @@ tags: [onboarding] **`🖱`** Below that on the dropdown menu, click on "Create branch **![][branch]`[transform branch]`** from **`main`.**" -### 4. Verify `[transform branch]` is now your working branch +## 4. Verify `[transform branch]` is now your working branch **`👁`** Check your "![][branch]`[trannsform branch]`” has replaced "![][branch]`main`" as your working branch. **`Fig. 4`** ![Fig. 4](../images/github-branch-four.png) @@ -41,14 +41,16 @@ tags: [onboarding] ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-branch**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-branch) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-branch**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-branch) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user * Hackney `[service]` Data Analyst @@ -56,6 +58,7 @@ tags: [onboarding] ::: :::note BEHAVIOR +### How do I create `[transform branch]` as my new working branch of **DAP⇨flow**'s `[dap-airflow]` repository? **Measures** the ***GitHub*** and `dap-airflow` repository behavior: **Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication diff --git a/docs/dap-airflow/onboarding/github-commit-transform.md b/docs/dap-airflow/onboarding/github-commit-transform.md index 21711ff9..d2b2406f 100644 --- a/docs/dap-airflow/onboarding/github-commit-transform.md +++ b/docs/dap-airflow/onboarding/github-commit-transform.md @@ -9,13 +9,13 @@ tags: [onboarding] # How do I commit my working `[transform SQL]` query to **DAP⇨flow**'s `[dap-airflow]` repository? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access ***Amazon Athena*** with your `[service workgroup]` +## 1. Access ***Amazon Athena*** with your `[service workgroup]` **`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. **`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 2. Prepare and make ready your `[transform SQL]` query +## 2. Prepare and make ready your `[transform SQL]` query **`🖱`** Ensure you have already created, tested and saved your `[transform SQL]` as a working, fully functional Athena SQL query. 👉 If you want reminding of how to do any of that, see **here** or **here ►** @@ -24,7 +24,7 @@ tags: [onboarding] **`🖱`** Open your `[transform SQL]` in the ***Amazon Athena*** query editor and keep it open in a web browser tab. -### 3. Access the `dap-airflow` repository in ***GitHub*** +## 3. Access the `dap-airflow` repository in ***GitHub*** **`🖱`** Use another tab in your web browser to log into your ***GitHub*** account using your *Hackney email address* with two-factor authentication. @@ -32,7 +32,7 @@ tags: [onboarding] **`🖱`** Open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. -### 4. Open your `[service dags]/transformations` subfolder on a your `[transform branch]` +## 4. Open your `[service dags]/transformations` subfolder on a your `[transform branch]` **`🖱`** Ensure you have created your ![][branch]`[transform branch]` and have it selected. **`Fig. 4a`** ![Fig. 4a](../images/github-commit-transform-four-a.png) @@ -47,7 +47,7 @@ tags: [onboarding] **`Fig. 4b & 5a`** ![Fig. 4b & 5a](../images/github-commit-transform-four-b-five-a.png) -### 5. Create your new `[transform].sql` file in ***GitHub*** +## 5. Create your new `[transform].sql` file in ***GitHub*** **`🖱`** At the top right region of the page, click the "**Add file**" button and select "**Create new file**" @@ -57,23 +57,23 @@ tags: [onboarding] **`🖱`** Keep this ***Github*** code editor and it's web browser tab open for later on. -### 6. Copy your `[transform SQL]` code from ***Amazon Athena*** +## 6. Copy your `[transform SQL]` code from ***Amazon Athena*** **`🖱`** Switch back to the ***Amazon Athena*** tab in your web browser, with your `[transform SQL]` still in the query editor. **`🖱`** Select your entire `[transform SQL]` code in the Athena query editor. **`Fig. 6`** ![Fig. 6](../images/github-commit-transform-six.png) **`🖱`** Use the right-click menu to "*Copy*" the selected code to your computer’s clipboard. -### 7. Paste your `[transform SQL]` code into ***GitHub*** +## 7. Paste your `[transform SQL]` code into ***GitHub*** **`🖱`** Switch back to the ***GitHub*** tab in your web browser, with `[transform].sql` currently empty in the code editor. **`🖱`** In the ***GitHub*** editor window beneath where it says “**Edit**”, use the right-click menu to "*Paste*" your entire `[transform SQL]` code, from the computer’s clipboard, into your `[transform].sql` file. **`Fig. 7 & 8`** ![Fig. 7 & 8](../images/github-commit-transform-seven-eight.png) -### 8. Review and adjust your `[transform SQL]` code +## 8. Review and adjust your `[transform SQL]` code **`🖱`** Scroll to the bottom of the ***GitHub*** editor window to remove any `limit` clause (e.g., `limit 100`), leaving just the final **`;`** semi-colon at the very end. **`👁`** If you spot problems in your code you have an opportunity to fix them now, or fix them later. -### 9. Commit your `[transform].sql` file +## 9. Commit your `[transform].sql` file **`🖱`** Click the "**Commit changes**" button to open a dialogue box. **`Fig. 9`** ![Fig. 9](../images/github-commit-transform-nine.png) **`🖮`** Enter a short commit message, Eg. `Add ... [transform].sql`. @@ -83,7 +83,7 @@ tags: [onboarding] **`👁`** You should see a message confirming your `[transform].sql` was successfully committed directly to your `[transform branch]`. -### 10. Making subsequent changes to `[transform].sql` +## 10. Making subsequent changes to `[transform].sql` Whether you are just fault-fixing or you want to add new SQL code features to your `[transform SQL]`: **`🖱`** In the ***GitHub*** editor window beneath where it says “**Edit**”, you can edit your `[transform].sql` file directly. @@ -103,14 +103,16 @@ Whether you are just fault-fixing or you want to add new SQL code features to yo ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-commit-transform**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-commit-transform) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-commit-transform**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-commit-transform) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * Hackney **Google Workspace** user * Hackney `[service]` Data Analyst @@ -119,6 +121,7 @@ Whether you are just fault-fixing or you want to add new SQL code features to yo ::: :::note BEHAVIOR +### How do I commit my working `[transform SQL]` query to **DAP⇨flow**'s `[dap-airflow]` repository? **Measures** the behavior of ***GitHub*** and ***Amazon Athena***. **Given** in my web browser, I have logged into my AWS account diff --git a/docs/dap-airflow/onboarding/github-pull-request.md b/docs/dap-airflow/onboarding/github-pull-request.md index 739975c8..f3a03a13 100644 --- a/docs/dap-airflow/onboarding/github-pull-request.md +++ b/docs/dap-airflow/onboarding/github-pull-request.md @@ -10,15 +10,15 @@ tags: [onboarding] ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Log into your ***GitHub*** account +## 1. Log into your ***GitHub*** account **`🖱`** Open your web browser and log into your ***GitHub*** account using your ***Hackney email address*** with two-factor authentication. 👉 Users without a ***GitHub*** account or existing ***GitHub*** users without membership of the **[London Borough of Hackney](https://github.com/LBHackney-IT) organization,** should **start here ►** **[DAP⇨flow📚GitHub access](../onboarding/github-access)** -### 2. Access the `dap-airflow` repository +## 2. Access the `dap-airflow` repository **`🖱`** When you are ready, open the **[`dap-airflow`](https://github.com/LBHackney-IT/dap-airflow)** repository in your web browser. -### 3. Switch to your working `[transform branch]` +## 3. Switch to your working `[transform branch]` 👉 If you haven't yet created your `[transform branch]` then **see here** how to do that **►** **[DAP⇨flow📚GitHub branching](../onboarding/github-branch)** @@ -31,42 +31,11 @@ tags: [onboarding] **`Fig. 3b`** ![Fig. 3b](../images/github-pull-request-three-b.png) **`👁`** Your **![][branch]`[transform branch]`** should reappear next to the `▼`dropdown button. -👉 If you've yet to commit your `[transform SQL]` to your `[transform branch]` then check back **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** +👉 If you've yet to *commit* your `[transform SQL]` to your `[transform branch]` then check back **here ► [DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** -:::tip But how will I know? +👉 If you don't remember if you *committed* your `[transform SQL]` to your `[transform branch]` then check **here ► [📚Appendix](#so-how-will-you-know-if-you-did-or-you-didnt)** -Let's assume you set up your `[transform branch]` earlier but then you got distracted so, now, you are not certain if you actually *committed* your `[transform SQL]` to a `[transform].sql` file. - -#### So, how will you know if you did or you didn't? - -Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio Code*** can quickly pull up a *Git Graph* to simply find out. But what if you only have ***GitHub***'s web interface available, because you are on a Chromebook or you don't have a local copy of the repository? - -**Then here's a neat trick for you!** -(You must be [logged into your ***GitHub*** account](#1-log-into-your-github-account) for this) - -**`🖱`** Use the following link to open a separate new tab in your web browser: -**[`https://github.com/LBHackney-IT/dap-airflow/activity?ref=[transform branch]`](https://github.com/LBHackney-IT/dap-airflow/activity?ref=transform%20branch)** - -**`🖮`** Then replace all the text immediately after `ref=` with the name of your `[transform branch]` before hitting *Enter*. -![Fig. 3-tip-a](../images/github-pull-request-three-tip-a.png) - -**`👁`** Then below, ***GitHub*** should appear with your **![][branch]`[transform branch]`** showing. -![Fig. 3-tip-b](../images/github-pull-request-three-tip-b.png) -**`👁`** If, below that, you get the message "**No activity matched your search**" then you can be certain you never actually *committed* a `[transform].sql` file. - -👉 If you did not *commit* your `[transform SQL]` to your `[transform branch]` then check back **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** - -**`👁`** Otherwise, you should see a list of one-or-more *commits* to your `[transform branch]`. - -**`🖱`** But if you are not sure about those, then you can click on `…` after each *commit message* and select "**Compare changes**" -![Fig. 3-tip-c](../images/github-pull-request-three-tip-c.png) -**`👁`** Then, on the next screen you will be presented with a list of changes that should remind you what you actually did! - -👉 If you are not sure you have properly *committed* your `[transform SQL]` to your `[transform branch]` then you should retrace your steps **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** - -::: - -### 4. Create your *pull request* +## 4. Create your *pull request* **`🖱`** Select the "**Pull requests**" tab at the top of the repository page. **`Fig. 4a`** ![Fig. 4a](../images/github-pull-request-four-a.png) **`🖱`** Click the "**New pull request**" button on the right. @@ -78,13 +47,21 @@ Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio **`🖱`** Click the "**Create pull request**" button. **`Fig. 4c`** ![Fig. 4c](../images/github-pull-request-four-c.png) -### 5. Add the details to your *pull request* +## 5. Add the details to your *pull request* **`🖮`** Enter a title for your *pull request*. **`🖮`** Add a description explaining the changes you have made. **`Fig. 5 & 6`** ![Fig. 5 & 6](../images/github-pull-request-five-six.png) -### 6. Submit your *pull request* +/** + * Submits a pull request to merge the user's `[transform branch]` into the `main` trunk of the `dap-airflow` repository. + * + * This step completes the pull request process by: + * - Clicking the "Create pull request" button to submit the pull request + * - Sending the user an email to confirm the pull request + * - Sending an email to the DAP Platform Team to notify them of the pull request + */ +## 6. Submit your *pull request* **`🖱`** Click the "**Create pull request**" button below the description on the right. ***GitHub*** should begin the process of pulling your **`[transform branch]`** into the `main` trunk or the `dap-airflow` repository: @@ -98,14 +75,16 @@ Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-pull-request**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-pull-request) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / github-pull-request**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=github-pull-request) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` criteria :::info ABILITY * Hackney **Google Workspace** user * Hackney `[service]` Data Analyst @@ -113,6 +92,7 @@ Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio ::: :::note BEHAVIOR +### How do I raise a *"pull request"* to merge my `[transform branch]` back into the `main` trunk of **DAP⇨flow**'s `[dap-airflow]` repository? **Measures** the ***GitHub*** and `dap-airflow` repository behavior: **Given** in my web browser, I am logged on to my ***GitHub*** account using my ***Hackney email address*** with two-factor authentication @@ -140,4 +120,40 @@ Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio **Scale** of 13 to 16 **~and** flow features. ::: +## 📚Appendix + +:::tip How will I know? + +Let's assume you set up your `[transform branch]` earlier but then you got distracted so, now, you are not certain if you actually *committed* your `[transform SQL]` to a `[transform].sql` file. + +### So, how will you know if you did or you didn't? + +Those that have ***GitHub*** integrated with their editors eg. ***Visual Studio Code*** can quickly pull up a *Git Graph* to simply find out. But what if you only have ***GitHub***'s web interface available, because you are on a Chromebook or you don't have a local copy of the repository? + +#### Here's a neat trick you can use! +You must be [logged into your ***GitHub*** account](#1-log-into-your-github-account) for this to work... + +**`🖱`** Use the following link to open a separate new tab in your web browser: +**[`https://github.com/LBHackney-IT/dap-airflow/activity?ref=[transform branch]`](https://github.com/LBHackney-IT/dap-airflow/activity?ref=transform%20branch)** + +**`🖮`** Then replace all the text immediately after `ref=` with the name of your `[transform branch]` before hitting *Enter*. +![Fig. 3-tip-a](../images/github-pull-request-three-tip-a.png) + +**`👁`** Then below, ***GitHub*** should appear with your **![][branch]`[transform branch]`** showing. +![Fig. 3-tip-b](../images/github-pull-request-three-tip-b.png) +**`👁`** If, below that, you get the message "**No activity matched your search**" then you can be certain you never actually *committed* a `[transform].sql` file. + +👉 If you did not *commit* your `[transform SQL]` to your `[transform branch]` then check back **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** + +**`👁`** Otherwise, you should see a list of one-or-more *commits* to your `[transform branch]`. + +**`🖱`** But if you are not sure about those, then you can click on `…` after each *commit message* and select "**Compare changes**" +![Fig. 3-tip-c](../images/github-pull-request-three-tip-c.png) +**`👁`** Then, on the next screen you will be presented with a list of changes that should remind you what you actually did! + +👉 If you are not sure you have properly *committed* your `[transform SQL]` to your `[transform branch]` then you should retrace your steps **here ►[DAP⇨flow📚Committing transforms](../onboarding/github-commit-transform)** + +::: + [branch]: + diff --git a/docs/dap-airflow/onboarding/prototype-legacy-transforms.md b/docs/dap-airflow/onboarding/prototype-legacy-transforms.md index e2e9dbf3..3970eb81 100644 --- a/docs/dap-airflow/onboarding/prototype-legacy-transforms.md +++ b/docs/dap-airflow/onboarding/prototype-legacy-transforms.md @@ -8,34 +8,34 @@ tags: [onboarding] # How do I use ***Amazon Athena*** to prototype a data transformation from my `[legacy SQL query]`? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access ***Amazon Athena*** +## 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. 👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your `[service workgroup]` +## 2. Select your `[service workgroup]` **`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 3. Select your `[service raw zone]` database +## 3. Select your `[service raw zone]` database **`🖱`** Ensure you select your `[service raw zone]` from the list box under the "**Database**" section on the left side of the Athena interface. **`👁`** You should observe your `[service database]` equivalent tables and columns with their respective data types listed below "**`▼` Views**". -### 4.Prepare your `[transform SQL]` query +## 4.Prepare your `[transform SQL]` query **`🖱`** *Copy-and-paste* your `[legacy SQL query]` lifted from your `[service database]` into ***Amazon Athena***'s query editor to become your new `[transform SQL]` code. You should take this opportunity to tidy up and format your SQL code, making it easier to read, maintain, and spot errors. 👉 You'll find considerations for SQL development discussed **►[💡here](../onboarding/prototype-simple-transforms#considerations-when-adopting-amazon-athena-for-your-future-sql-development)**. -### 5. Verify table and column availability +## 5. Verify table and column availability **`🖱`** Over on the left of the Athena interface, expand the list under “**`▼` Views**” to verify your `[service raw zone]` includes your `[service database]` equivalent tables and columns matching those in your `[transform SQL]`. **`Fig. 5a`** ![Fig. 5a](../images/prototype-legacy-transforms-five-a.png) **`Fig. 5b`** ![Fig. 5b](../images/prototype-legacy-transforms-five-b.png) -### 6. Ensure your `[transform SQL]` is compatible with ***Amazon Athena*** +## 6. Ensure your `[transform SQL]` is compatible with ***Amazon Athena*** **`👁`** Review your `[transform SQL]` code to ensure all column functions and expressions are compatible with ***Amazon Athena***, aiming to produce the same column output as the original `[legacy SQL query]`. Often the easy way to test your SQL code compatibility is to simply try running it (as per **Step 7**). It might succeed, or fail with errors that should inform you about what you need to change. @@ -50,17 +50,17 @@ Often the easy way to test your SQL code compatibility is to simply try running - Your original `[service database]` database name will not be used by **DAP⇨flow**, so you will need to swap it out with your `[service raw zone]`. -### 7. Run your `[transform SQL]` query +## 7. Run your `[transform SQL]` query **`🖱`** After customizing the SQL code, click “**Run**” or “**Run again**” located underneath the code window on the left side in the ***Amazon Athena*** interface. **`Fig. 7`** ![Fig. 7](../images/prototype-legacy-transforms-seven.png) -### 8. Review the results +## 8. Review the results **`👁`** ***Amazon Athena*** should fetch the same results as your `[legacy SQL query]` would have, when run by your original `[service database]`. If it is possible to make a direct comparison with the legacy system output then that should help you have confidence in the results of your prototype SQL. **`Fig. 8`** ![Fig. 8](../images/prototype-legacy-transforms-eight.png) -### 9. Save your query as `[transform].sql` +## 9. Save your query as `[transform].sql` **`🖱`** Check you are in your correct `[service workgroup]` before clicking on the three dots **⋮** to the right of your Query tab, and clicking “**Save as**”. **`Fig. 9a`** ![Fig. 9a](../images/prototype-legacy-transforms-nine-a.png) @@ -76,15 +76,17 @@ Often the easy way to test your SQL code compatibility is to simply try running ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / prototype-legacy-transforms**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=prototype-legacy-transforms) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / prototype-legacy-transforms**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=prototype-legacy-transforms) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * **AWS Management Console** user * **Amazon Athena** beginner @@ -93,6 +95,7 @@ Often the easy way to test your SQL code compatibility is to simply try running ::: :::note BEHAVIOR +### How do I use ***Amazon Athena*** to prototype a data transformation from my `[legacy SQL query]`? **Measures** the behavior of ***Amazon Athena*** while users convert there `[legacy SQL query]` into transforms: **Given** in my web browser, I have accessed ***Amazon Athena*** diff --git a/docs/dap-airflow/onboarding/prototype-simple-transforms.md b/docs/dap-airflow/onboarding/prototype-simple-transforms.md index 5c8448f4..9414228a 100644 --- a/docs/dap-airflow/onboarding/prototype-simple-transforms.md +++ b/docs/dap-airflow/onboarding/prototype-simple-transforms.md @@ -8,15 +8,15 @@ tags: [onboarding] # How can I use ***Amazon Athena*** to prototype a simple table-join data transformation? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access ***Amazon Athena*** +## 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the ***AWS Management Console***, and open ***Amazon Athena***. 👉 First time ***Amazon Athena*** users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your `[service workgroup]` +## 2. Select your `[service workgroup]` **`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 3. Exploring your `[service raw zone]` database +## 3. Exploring your `[service raw zone]` database **`🖱`** Ensure you have selected your `[service raw zone]` from the list box under "**Database**" on the left side of the Athena interface. **`🖱`** You can then expand the lists under "**`►` Tables**" or "**`►` Views**", then expand each name further to reveal column names and data types, as follows: @@ -27,7 +27,7 @@ tags: [onboarding] * "**`▼` Views**" 👉 Documented here ► **[📚My current service data](../onboarding/access-my-current-service-data)** -### 4. Understanding the data model +## 4. Understanding the data model **`👁`** Identify which tables and columns you need to use for your data transformation: - Wherever you want a `

` originally from your `[service database]` you should be able to find it's name listed under "**`▼` Views**" below your `[service raw zone]` database. @@ -38,7 +38,7 @@ tags: [onboarding] * The **``** with a unique `` and a foreign key pointing to the `` of the ``. -### 5. Prepare your `[transform SQL]` query +## 5. Prepare your `[transform SQL]` query **`🖱`** You can either: * Start completely from scratch and building up your query in the editor as you go along; @@ -74,19 +74,9 @@ ORDER BY limit 100; ``` -#### 💡Considerations when adopting ***Amazon Athena*** for your future SQL development +👉 You'll find considerations for SQL development discussed **here ► [📚Appendix](#considerations-when-adopting-amazon-athena-for-your-future-sql-development)** -Migrating to a new technology or platform offers an ideal opportunity to raise coding standards and shed common old habits of the past. - -* You have complete freedom over the SQL code formatting however we recommend always putting each element, table or column, on its own line. This helps debugging and readability. You should endeavour to be consistent in your style and agree a particular style among your service colleagues. In our examples, we will use 4-space tabulation and use "hard left" nesting, which you are welcome to adopt. - -* Nesting has no syntactic significance to SQL interpreters so its only impact is aesthetic alone. JOIN-clauses join everything previously to the table following, and not just the previous table, so nesting them does change order of execution. Execution order can only be affected by the use of bracketed sub-queries. The hard-left nesting style, on the other hand, is designed to help the reader be conscious of the execution order above all else. - -* Avoid using lazy cartesian table products without JOIN-clauses in between the tables (or subqueries or CTEs). Likewise avoid using WHERE-clauses to perform cartesian filters and use JOIN-clauses instead. Conversely, Athena does not mind non-cartesian filters within JOIN-clauses and is even recommended where partition-columns are involved because it reduces the quantity of data scanned before any subsequent joins are executed. - -* Always consider using CTEs in place of subqueries to help debugging and readability. ***Amazon Athena*** permits VALUES table constructors in CTEs allowing replacement of very lengthy WHERE-CASE filters with the more efficient JOIN-CTE filters. - -### 6. Customizing a template query +## 6. Customizing a template query When, for example, using the **`Fig. 5`** `[SQL template]`: **`🖱`** You will need to replace the `` and `` template placeholders with actual names listed under “**`▼` Views**” over from the left-hand side of the interface. The Athena editor allows you to insert names directly into the code by simply clicking on the three dots **`⋮`** right of the name, then selecting “***insert into editor***”. @@ -133,12 +123,12 @@ When, for example, using the **`Fig. 5`** `[SQL template]`: * Adding a `limit` clause at the end of your query when testing SQL queries in the Athena console normally prevents long-running queries when testing. You will routinely remove the `limit` clause later when your transform goes into production. -### 7. Run your `[transform SQL]` query +## 7. Run your `[transform SQL]` query **`🖱`** After customizing the SQL code, click “**Run**” or “**Run again**” located underneath the code window on the left side in the Athena interface. **`Fig. 7`** ![Fig. 7](../images/prototype-simple-transforms-seven.png) -### 8. Review the results +## 8. Review the results **`👁`** ***Amazon Athena*** should fetch a number of rows based on your set `[limit]` (eg. `limit 100;` as in the **`Fig. 5`** `[SQL template]`). * If you included it, the first column `original_import_data` will inform us when the underlying data was ingested from your `[service database]`. If you do not see today’s date then you’ll immediately know that the data ingestion had failed sometime after the date shown, and you should contact the DAP Team to find out what the problem is. But so long as you have data of any given generation you can still test your transform query. @@ -149,7 +139,7 @@ When, for example, using the **`Fig. 5`** `[SQL template]`: **`Fig. 8`** ![Fig. 8](../images/prototype-simple-transforms-eight.png) -### 9. Save your query as `[transform SQL]` +## 9. Save your query as `[transform SQL]` **`🖱`** Check you are in your correct `[service workgroup]` before clicking on the three dots **⋮** to the right of your Query tab, and clicking “**Save as**”. **`🖮`** When the dialogue pops up, enter a name for your `[transform SQL]` eg. `[transform].sql` and write a description before clicking the “**Save query**” button. @@ -165,15 +155,16 @@ When, for example, using the **`Fig. 5`** `[SQL template]`: ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / prototype-simple-transforms**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=prototype-simple-transforms) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / prototype-simple-transforms**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=prototype-simple-transforms) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** -::: + ☝ **Please use this link to help us understand your user experience!** +::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * **AWS Management Console** user * ***Amazon Athena*** beginner @@ -182,6 +173,7 @@ When, for example, using the **`Fig. 5`** `[SQL template]`: ::: :::note BEHAVIOR +### How can I use ***Amazon Athena*** to prototype a simple table-join data transformation? **Measures** the behavior of ***Amazon Athena*** while users prototype simple transforms: **Given** in my web browser, I have accessed ***Amazon Athena*** @@ -206,3 +198,23 @@ When, for example, using the **`Fig. 5`** `[SQL template]`: **Scale** of 7 to 14 **~and** flow features. ::: + + +## 📚Appendix + +:::tip Considerations + +### Considerations when adopting ***Amazon Athena*** for your future SQL development + +💡Migrating to a new technology or platform offers an ideal opportunity to raise coding standards and shed common old habits of the past. + +* You have complete freedom over the SQL code formatting however we recommend always putting each element, table or column, on its own line. This helps debugging and readability. You should endeavour to be consistent in your style and agree a particular style among your service colleagues. In our examples, we will use 4-space tabulation and use "hard left" nesting, which you are welcome to adopt. + +* Nesting has no syntactic significance to SQL interpreters so its only impact is aesthetic alone. JOIN-clauses join everything previously to the table following, and not just the previous table, so nesting them does change order of execution. Execution order can only be affected by the use of bracketed sub-queries. The hard-left nesting style, on the other hand, is designed to help the reader be conscious of the execution order above all else. + +* Avoid using lazy cartesian table products without JOIN-clauses in between the tables (or subqueries or CTEs). Likewise avoid using WHERE-clauses to perform cartesian filters and use JOIN-clauses instead. Conversely, Athena does not mind non-cartesian filters within JOIN-clauses and is even recommended where partition-columns are involved because it reduces the quantity of data scanned before any subsequent joins are executed. + +* Always consider using CTEs in place of subqueries to help debugging and readability. ***Amazon Athena*** permits VALUES table constructors in CTEs allowing replacement of very lengthy WHERE-CASE filters with the more efficient JOIN-CTE filters. + +::: + diff --git a/docs/dap-airflow/onboarding/query-my-service-data.md b/docs/dap-airflow/onboarding/query-my-service-data.md index 9e327a47..c80aaec5 100644 --- a/docs/dap-airflow/onboarding/query-my-service-data.md +++ b/docs/dap-airflow/onboarding/query-my-service-data.md @@ -5,18 +5,18 @@ description: "Onboarding data analysts and engineers to DAP⇨flow, the Data Ana layout: playbook_js tags: [onboarding] --- -# How will I query and analyze my `[service]` data with ***Amazon Athena***? +# How will I query and analyze my `[service]`'s data with ***Amazon Athena***? ![DAP⇨flow](../images/DAPairflowFLOWleft.png) -### 1. Access ***Amazon Athena*** +## 1. Access ***Amazon Athena*** **`🖱`** In your web browser, log in to your AWS account, navigate to the AWS Management Console, and open Amazon Athena. 👉 First time Amazon Athena users should **start here ►** **[DAP⇨flow📚Amazon Athena](../onboarding/access-my-Amazon-Athena-database)** -### 2. Select your `[service workgroup]` +## 2. Select your `[service workgroup]` **`🖱`** Ensure you have selected your `[service workgroup]` from the list box next to “**Workgroup**”. -### 3. Explore your database +## 3. Explore your database **`🖱`** Ensure you have selected your `[service raw zone]` database from the list box under "**Database**" on the left side of the Athena interface, before expanding the lists under "**`►` Tables**" and/or "**`►` Views**. Expanding further should reveal column names and data types, as follows: - "**`▼` Tables**" @@ -25,17 +25,17 @@ tags: [onboarding] - "**`▼` Views**" 👉 Documented here ► **[📚My current service data](../onboarding/access-my-current-service-data)** -### 4. Familiarize yourself with SQL queries +## 4. Familiarize yourself with SQL queries **`🕮`** You will need to understand the concepts and basic requirements of writing SQL queries. This includes knowing how to select columns, filter data, join tables, etc. 👉 You can learn more about using Amazon Athena **►** [**here**](https://docs.aws.amazon.com/athena/latest/ug/using-athena-sql.html) -### 5. Run SQL queries +## 5. Run SQL queries **`🖱`** Use the SQL query editor in ***Amazon Athena*** to write and run queries involving tables and columns equivalent to the your original `[service database]`. **`Fig. 5`** ![Fig. 5](../images/query-my-service-data-five.png) -### 6. Analyze your data +## 6. Analyze your data **`👁`** Review the results of your SQL queries to find answers to your questions about your `[service database]`. **`Fig. 6`** ![Fig. 6](../images/query-my-service-data-six.png) @@ -50,15 +50,17 @@ tags: [onboarding] ## ***"We* ♡ *your feedback!"*** ![DAP⇨flow](../images/DAPairflowFLOWleft.png) :::tip UX -👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / query-my-service-data**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=query-my-service-data) +### 👉 Please use **this link ►** [**DAP⇨flow** `UX` **Feedback / query-my-service-data**](https://docs.google.com/forms/d/e/1FAIpQLSdqeNyWIPMNBHEr-YSyxnXQ4ggTwJPkffMYgFaJ4hGEhIL6LA/viewform?usp=pp_url&entry.339550210=query-my-service-data) + - Your feedback enables us to improve **DAP⇨flow** and our Data Analytics Platform service. - We encourage all our users to be generous with their time, in giving us their recollections and honest opinions about our service. - We especially encourage our new users to give feedback at the end of every **📚Onboarding** task because the quality of the onboarding experience really matters. -☝ **Please use this link to help us understand your user experience!** + + ☝ **Please use this link to help us understand your user experience!** ::: -#### UX Criteria +## 📚`UX` Criteria :::info ABILITY * **AWS Management Console** user * **Amazon Athena** user @@ -67,6 +69,7 @@ tags: [onboarding] ::: :::note BEHAVIOR +### How will I query and analyze my `[service]`'s data with ***Amazon Athena***? **Measures** the behavior of **Amazon Athena** when users' run working SQL queries: **Given** in my web browser, I have accessed ***Amazon Athena*** diff --git a/docs/dap-airflow/ux.md b/docs/dap-airflow/ux.md new file mode 100644 index 00000000..6ab11dde --- /dev/null +++ b/docs/dap-airflow/ux.md @@ -0,0 +1,68 @@ +--- +id: ux +title: 📚UX +description: "The DAP⇨flow guide for data analysts and engineers, for developing and deploying Airflow DAGs, running data pipelines in the Data Analytics Platform (DAP)." +layout: playbook_js +tags: [dap-airflow] +--- + +# 📚`UX` +![DAP⇨flow](../dap-airflow/images/DAPairflowFLOWwide.png) + +## 📚User eXperience criteria +The links below will take you directly to the **📚`UX` criteria** within each of the **DAP⇨flow** onboarding guides. + +### [Before you begin](../dap-airflow/onboarding/begin#ux-criteria) +What must happen before I can begin **DAP⇨flow**? + +### [AWS Console access](../dap-airflow/onboarding/access-the-AWS-Management-Console#ux-criteria) +How will I access the ***AWS Management Console***? + +### [AWS region](../dap-airflow/onboarding/access-the-AWS-region#ux-criteria) +How will I ensure I am in the correct **AWS region**? + +### [Amazon Athena](../dap-airflow/onboarding/access-my-Amazon-Athena-database#ux-criteria) +How will I use ***Amazon Athena*** to access my database? + +### [My current service data](../dap-airflow/onboarding/access-my-current-service-data#ux-criteria) +How will I access my `[service]`'s current data from ***Amazon Athena***? + +### [My service data history](../dap-airflow/onboarding/access-my-service-data-history#ux-criteria) +How will I access my `[service]`'s data history from ***Amazon Athena***? + +### [Query my service data](../dap-airflow/onboarding/query-my-service-data#ux-criteria) +How will I query and analyze my `[service]`'s data with ***Amazon Athena***? + +### [Prototype simple transforms](../dap-airflow/onboarding/prototype-simple-transforms#ux-criteria) +How can I use ***Amazon Athena*** to prototype a simple table-join data transformation? + +### [Prototype legacy transforms](../dap-airflow/onboarding/prototype-legacy-transforms#ux-criteria) +How do I use ***Amazon Athena*** to prototype a data transformation from my `[legacy SQL query]`? + +### [GitHub access](../dap-airflow/onboarding/github-access#ux-criteria) +How do I set up my ***GitHub*** access for **DAP⇨flow**? + +### [GitHub branching](../dap-airflow/onboarding/github-branch#ux-criteria) +How do I create `[transform branch]` as my new working branch of **DAP⇨flow**'s repository? + +### [Committing transforms](../dap-airflow/onboarding/github-commit-transform#ux-criteria) +How do I commit my working `[transform SQL]` to **DAP⇨flow**'s repository? + +### [GitHub pull requests](../dap-airflow/onboarding/github-pull-request#ux-criteria) +How do I raise a *"pull request"* to merge my `[transform branch]` into the `main` trunk of the **DAP⇨flow** repository? + +## 📚Coming soon... +The following guides are due for completion. + +### Merging branches +How do i complete the merge of `[transform branch]` into the main trunk of **DAP⇨flow**'s repository? + +### Airflow +How will I access my data transforms using ***Airflow*** on the web? + +### Adding tables to the raw-zone +How do i add a new table ingestion to my `[service raw-zone]` database? + +
+ +![Apache Airflow](../dap-airflow/images/worker_tap_valve_800_wht.jpg) diff --git a/sidebars.js b/sidebars.js index 8d4ccc0d..314cd1ac 100644 --- a/sidebars.js +++ b/sidebars.js @@ -142,6 +142,7 @@ module.exports = { "dap-airflow/onboarding/github-pull-request", ], }, + "dap-airflow/ux", ], }, { From b7bd520a0bec8d2249b64d0d80e47915a227baef Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Sun, 1 Sep 2024 00:58:49 +0100 Subject: [PATCH 15/16] =?UTF-8?q?Updated=20DAP=E2=87=A8flow=20onboarding?= =?UTF-8?q?=20/=20UX?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/introduction.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/dap-airflow/introduction.md b/docs/dap-airflow/introduction.md index b3b638c6..8966ba95 100644 --- a/docs/dap-airflow/introduction.md +++ b/docs/dap-airflow/introduction.md @@ -16,7 +16,7 @@ Building data pipelines used to be harder and more complex and time consuming. Data Analysts, after prototyping their SQL queries using ***Amazon Athena*** were required to convert *Athena SQL* code to *Spark SQL*, a different SQL dialect, then embed their code within an ***Amazon Glue*** job which they had to deploy using ***Terraform***. -Data Analysts were forced to query across multiple generations of the same data stored in the ***Amazon S3*** Data lake when al they actually wanted was their current data. That meant they could not simply take a legacy SQL query and run it in ***Amazon Athena*** or create an ***Amazon Glue*** product directly from it. +Data Analysts were forced to query across multiple generations of the same data stored in the ***Amazon S3*** Data lake when all they actually wanted was just their current data. That meant they could not simply take legacy SQL queries and run them directly in ***Amazon Athena***. #### How **DAP⇨flow** solves these problems * Firstly, Data Analysts no longer need to convert and re-test their prototype SQL transforms to run in the separate and more complex ***Amazon Glue*** run-time environment. @@ -41,9 +41,9 @@ Data Analysts were forced to query across multiple generations of the same data Anyone new to **DAP⇨flow** will need read [**📚Before you begin**](../dap-airflow/onboarding/begin). -Thereafter, Data Analysts do not need to read every documents in the order they are listed below, especially if they are already familiar with the ***AWS Management Console*** and have used ***Amazon Athena*** before. +Thereafter, Data Analysts do not need to read every document in the order they are listed below, especially if they are already familiar with the ***AWS Management Console*** and have used ***Amazon Athena*** before. -Data Analysts are encouraged to think about what they need to do before deciding which document to read next. For example, if they have a ***legacy SQL query*** that they want to migrate to **DAP⇨flow**, they might jump straight to [**📚Prototype legacy transforms**](../dap-airflow/onboarding/prototype-legacy-transforms). +Data Analysts are encouraged to think about what they need to do before deciding which document to read next. For example, if they have a ***legacy SQL query*** that they want to migrate to **DAP⇨flow**, they could jump straight to [**📚Prototype legacy transforms**](../dap-airflow/onboarding/prototype-legacy-transforms). #### ***"We* ♡ *your feedback!"*** Your continuous feedback enables us to improve **DAP⇨flow** and our ***Data Analytics Platform*** service. Survey links are provided at the end of each onboarding document. From 711a6c6fdd80bd54a75d20d35405517ffc0a2492 Mon Sep 17 00:00:00 2001 From: Steve Farr <36167148+stevefarrhackneygovuk@users.noreply.github.com> Date: Sun, 1 Sep 2024 01:05:06 +0100 Subject: [PATCH 16/16] =?UTF-8?q?Updated=20DAP=E2=87=A8flow=20onboarding?= =?UTF-8?q?=20/=20UX?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/dap-airflow/onboarding/github-pull-request.md | 8 -------- 1 file changed, 8 deletions(-) diff --git a/docs/dap-airflow/onboarding/github-pull-request.md b/docs/dap-airflow/onboarding/github-pull-request.md index f3a03a13..48e8e43e 100644 --- a/docs/dap-airflow/onboarding/github-pull-request.md +++ b/docs/dap-airflow/onboarding/github-pull-request.md @@ -53,14 +53,6 @@ tags: [onboarding] **`Fig. 5 & 6`** ![Fig. 5 & 6](../images/github-pull-request-five-six.png) -/** - * Submits a pull request to merge the user's `[transform branch]` into the `main` trunk of the `dap-airflow` repository. - * - * This step completes the pull request process by: - * - Clicking the "Create pull request" button to submit the pull request - * - Sending the user an email to confirm the pull request - * - Sending an email to the DAP Platform Team to notify them of the pull request - */ ## 6. Submit your *pull request* **`🖱`** Click the "**Create pull request**" button below the description on the right.

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