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name: Orchestration team - Request changes to docs | ||
description: File a docs update request that is not already tracked in Orch team's Release Plans (Notion database). | ||
labels: ["content","internal-orch-team"] | ||
body: | ||
- type: markdown | ||
attributes: | ||
value: | | ||
* You can ask questions or submit ideas for the dbt docs in [Issues](https://github.com/dbt-labs/docs-internal/issues/new/choose) | ||
* Before you file an issue read the [Contributing guide](https://github.com/dbt-labs/docs-internal#contributing). | ||
* Check to make sure someone hasn't already opened a similar [issue](https://github.com/dbt-labs/docs-internal/issues). | ||
- type: checkboxes | ||
id: contributions | ||
attributes: | ||
label: Contributions | ||
description: Please read the contribution docs before opening an issue or pull request. | ||
options: | ||
- label: I have read the contribution docs, and understand what's expected of me. | ||
|
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- type: textarea | ||
attributes: | ||
label: Link to the page on docs.getdbt.com requiring updates | ||
description: Please link to the page or pages you'd like to see improved. | ||
validations: | ||
required: true | ||
|
||
- type: textarea | ||
attributes: | ||
label: What part(s) of the page would you like to see updated? | ||
description: | | ||
- Give as much detail as you can to help us understand the change you want to see. | ||
- Why should the docs be changed? What use cases does it support? | ||
- What is the expected outcome? | ||
validations: | ||
required: true | ||
|
||
- type: textarea | ||
attributes: | ||
label: Reviewers/Stakeholders/SMEs | ||
description: List the reviewers, stakeholders, and subject matter experts (SMEs) to collaborate with for the docs update. | ||
validations: | ||
required: true | ||
|
||
- type: textarea | ||
attributes: | ||
label: Related Jira tickets | ||
description: Add any other context or screenshots about the feature request here. | ||
validations: | ||
required: false |
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name: Repo Sync | ||
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# **What it does**: Syncs docs.getdbt.com public repo into the docs private repo | ||
# This GitHub Actions workflow keeps the `current` branch of those two repos in sync. | ||
# **Why we have it**: To keep the open-source repository up-to-date | ||
# while still having an internal repository for sensitive work. | ||
# For more details, see https://github.com/repo-sync/repo-sync#how-it-works | ||
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on: | ||
schedule: | ||
- cron: '0 6,12,18 * * *' # Run at 6:00 AM, 12:00 PM, and 6:00 PM | ||
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jobs: | ||
repo-sync: | ||
permissions: | ||
contents: write | ||
pull-requests: write | ||
name: Repo Sync | ||
runs-on: ubuntu-latest | ||
steps: | ||
- uses: actions/checkout@v3 | ||
with: | ||
# Use the INTERMEDIATE_BRANCH as the checkout reference | ||
ref: ${{ secrets.INTERMEDIATE_BRANCH }} | ||
token: ${{ secrets.GITHUB_TOKEN }} | ||
# Fetch all history for all branches and tags | ||
fetch-depth: 0 | ||
|
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# Sync the source repo to the destination branch using repo-sync/github-sync | ||
- uses: repo-sync/github-sync@v2 | ||
name: Sync repo to branch | ||
with: | ||
# Source repository to sync from | ||
source_repo: ${{ secrets.SOURCE_REPO }} | ||
# Source branch to sync from | ||
source_branch: current | ||
# Destination branch to sync to | ||
destination_branch: ${{ secrets.INTERMEDIATE_BRANCH }} | ||
github_token: ${{ secrets.WORKFLOW_TOKEN }} | ||
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- name: Ship pull request | ||
uses: actions/github-script@v6 | ||
with: | ||
github-token: ${{ secrets.WORKFLOW_TOKEN }} | ||
result-encoding: string | ||
script: | | ||
const {owner, repo} = context.repo; | ||
const head = '${{ secrets.INTERMEDIATE_BRANCH }}'; | ||
const base = 'current' | ||
async function closePullRequest(prNumber) { | ||
console.log('closing PR', prNumber) | ||
await github.rest.pulls.update({ | ||
owner, | ||
repo, | ||
pull_number: prNumber, | ||
state: 'closed' | ||
}); | ||
console.log('closed PR', prNumber) | ||
} | ||
console.log('Creating new PR') | ||
let pull, pull_number | ||
try { | ||
const response = await github.rest.pulls.create({ | ||
owner, | ||
repo, | ||
head, | ||
base, | ||
title: 'REPO SYNC - Public to Private', | ||
body: 'This is an automated pull request to sync changes between the public and private repos.', | ||
}); | ||
pull = response.data | ||
pull_number = pull.number | ||
console.log('Created pull request successfully', pull.html_url) | ||
} catch (err) { | ||
// Don't error/alert if there's no commits to sync | ||
if (err.message?.includes('No commits')) { | ||
console.log(err.message) | ||
return | ||
} | ||
throw err | ||
} | ||
const { data: prFiles } = await github.rest.pulls.listFiles({ owner, repo, pull_number }) | ||
if (prFiles.length) { | ||
console.log(prFiles.length, 'files have changed') | ||
} else { | ||
console.log('No files changed, closing') | ||
await closePullRequest(pull_number) | ||
return | ||
} | ||
console.log('Checking for merge conflicts') | ||
if (pull.mergeable_state === 'dirty') { | ||
console.log('Pull request has a conflict', pull.html_url) | ||
await closePullRequest(pull_number) | ||
throw new Error('PR has a conflict, please resolve manually') | ||
} | ||
console.log('No detected merge conflicts') | ||
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console.log('Merging the PR') | ||
await github.rest.pulls.merge({ | ||
owner, | ||
repo, | ||
pull_number, | ||
merge_method: 'merge', | ||
}) | ||
console.log('Merged the PR successfully') |
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--- | ||
title: "Column-level lineage" | ||
description: "Use dbt Explorer's column-level lineage to gain insights about your data at a granular level." | ||
--- | ||
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# Column-level lineage <Lifecycle status='beta' /> | ||
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dbt Explorer now offers column-level lineage (CLL) for the resources in your dbt project. Analytics engineers can quickly and easily gain insight into the provenance of their data products at a more granular level. For each column in a resource (model, source, or snapshot) in a dbt project, Explorer provides end-to-end lineage for the data in that column given how it's used. | ||
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CLL is available to dbt Cloud Enterprise accounts that can use Explorer. It’s also available through the [Discovery API](/docs/dbt-cloud-apis/discovery-api). | ||
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:::tip Check out our beta | ||
Explorer's CLL is currently available as a [public beta](/docs/dbt-versions/product-lifecycles#dbt-cloud) for Enterprise plan accounts. Please check it out! | ||
::: | ||
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## Access the column-level lineage | ||
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There is no additional setup required for CLL if your account is on an Enterprise plan that can use Explorer. You can access the CLL by expanding the column card in the **Columns** tab of an Explorer [resource details page](/docs/collaborate/explore-projects#view-resource-details) for a model, source, or snapshot. | ||
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dbt updates the lineage after each run that's executed in the production environment. You must make sure that `dbt docs generate` runs within at least one job in the environment. Refer to [Generating metadata](/docs/collaborate/explore-projects#generate-metadata) for more details. | ||
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<Lightbox src="/img/docs/collaborate/dbt-explorer/example-cll.png" width="40%" title="Example of the Columns tab and where to expand for the CLL"/> | ||
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<LoomVideo id='3040bf2a2ade45eca7942a7aed6b730c' /> | ||
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## Column-level lineage use cases {#use-cases} | ||
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Learn more about why and how you can use CLL in the following sections. | ||
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### Root cause analysis | ||
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When there is an unexpected breakage in a data pipeline, column-level lineage can be a valuable tool to understand the exact point where the error occurred in the pipeline. For example, a failing data test on a particular column in your dbt model might've stemmed from an untested column upstream. Using CLL can help quickly identify and fix breakages when they happen. | ||
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### Impact analysis | ||
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During development, analytics engineers can use column-level lineage to understand the full scope of the impact of their proposed changes. This knowledge empowers them to create higher quality pull requests that require fewer edits, as they can anticipate and preempt issues that would've been unchecked without column-level insights. | ||
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### Collaboration and efficiency | ||
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When exploring your data products, navigating column lineage allows analytics engineers and data analysts to more easily navigate and understand the origin and usage of their data, enabling them to make better decisions with higher confidence. | ||
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## Caveats | ||
|
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Column-level lineage relies on SQL parsing. Errors can occur when parsing fails or a column's origin is unknown (like with JSON unpacking, lateral joins, and so on). In these cases, lineage may be incomplete and dbt Cloud will provide a warning about it in the column lineage. | ||
|
||
<Lightbox src="/img/docs/collaborate/dbt-explorer/example-parsing-error-pill.png" title="Example of warning in the full lineage graph"/> | ||
|
||
To review the error details: | ||
1. Click the **Expand** icon in the upper right corner to open the column's lineage graph | ||
1. Select the node to open the column’s details panel | ||
|
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Possible error cases are: | ||
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- **Parsing error** — Error occurs when the SQL is ambiguous or too complex for parsing. An example of ambiguous parsing scenarios are _complex_ lateral joins. | ||
- **Python error** — Error occurs when a Python model is used within the lineage. Due to the nature of Python models, it's not possible to parse and determine the lineage. | ||
- **Unknown error** — Error occurs when the lineage can't be determined for an unknown reason. An example of this would be if a dbt best practice is not being followed, like using hardcoded table names instead of `ref` statements. |
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