diff --git a/website/docs/docs/cloud-integrations/configure-auto-exposures.md b/website/docs/docs/cloud-integrations/configure-auto-exposures.md index 24364077614..4574d69c164 100644 --- a/website/docs/docs/cloud-integrations/configure-auto-exposures.md +++ b/website/docs/docs/cloud-integrations/configure-auto-exposures.md @@ -6,7 +6,7 @@ description: "Import and auto-generate exposures from dashboards and understand image: /img/docs/cloud-integrations/auto-exposures/explorer-lineage2.jpg --- -# Configure auto-exposures +# Configure auto-exposures As a data team, it’s critical that you have context into the downstream use cases and users of your data products. [Auto-exposures](/docs/collaborate/auto-exposures) integrates natively with Tableau and [auto-generates downstream lineage](/docs/collaborate/auto-exposures#view-auto-exposures-in-dbt-explorer) in dbt Explorer for a richer experience. diff --git a/website/docs/docs/collaborate/auto-exposures.md b/website/docs/docs/collaborate/auto-exposures.md index 2b1d649abd1..9b25a2fb305 100644 --- a/website/docs/docs/collaborate/auto-exposures.md +++ b/website/docs/docs/collaborate/auto-exposures.md @@ -7,7 +7,7 @@ pagination_next: "docs/collaborate/data-tile" image: /img/docs/cloud-integrations/auto-exposures/explorer-lineage.jpg --- -# Auto-exposures +# Auto-exposures As a data team, it’s critical that you have context into the downstream use cases and users of your data products. Auto-exposures integrates natively with Tableau (Power BI coming soon) and auto-generates downstream lineage in dbt Explorer for a richer experience. diff --git a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md index f72fa5b318c..e4e2a91791d 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-api-overview.md +++ b/website/docs/docs/dbt-cloud-apis/sl-api-overview.md @@ -48,10 +48,4 @@ plan="dbt Cloud Team or Enterprise" link="/docs/dbt-cloud-apis/sl-python" icon="dbt-bit"/> - - diff --git a/website/docs/reference/artifacts/dbt-artifacts.md b/website/docs/reference/artifacts/dbt-artifacts.md index c38cc2768e1..b8998dba261 100644 --- a/website/docs/reference/artifacts/dbt-artifacts.md +++ b/website/docs/reference/artifacts/dbt-artifacts.md @@ -22,7 +22,7 @@ dbt has produced artifacts since the release of dbt-docs in v0.11.0. Starting in ### When are artifacts produced? Most dbt commands (and corresponding RPC methods) produce artifacts: -- [semantic manifest](/docs/dbt-cloud-apis/sl-manifest): produced whenever your dbt project is parsed +- [semantic manifest](/reference/artifacts/sl-manifest): produced whenever your dbt project is parsed - [manifest](/reference/artifacts/manifest-json): produced by commands that read and understand your project - [run results](/reference/artifacts/run-results-json): produced by commands that run, compile, or catalog nodes in your DAG - [catalog](catalog-json): produced by `docs generate` diff --git a/website/docs/reference/artifacts/other-artifacts.md b/website/docs/reference/artifacts/other-artifacts.md index 0216acccff0..e37662ae28c 100644 --- a/website/docs/reference/artifacts/other-artifacts.md +++ b/website/docs/reference/artifacts/other-artifacts.md @@ -39,7 +39,7 @@ Each of those points in time contains the `name` and `type` of each node and `su ### semantic_manifest.json -The [`semantic_manifest.json`](/docs/dbt-cloud-apis/sl-manifest) file is useful as an internal interface between `dbt-core` and MetricFlow. As such, it functions as a behind-the-scenes bridge for interaction between the two systems. You can find all of the `semantic_manifest.json` information in the [`semantic_manifest.json`](/docs/dbt-cloud-apis/sl-manifest). +The [`semantic_manifest.json`](/reference/artifacts/sl-manifest) file is useful as an internal interface between `dbt-core` and MetricFlow. As such, it functions as a behind-the-scenes bridge for interaction between the two systems. You can find all of the `semantic_manifest.json` information in the [`semantic_manifest.json`](/reference/artifacts/sl-manifest). There are two reasons why `semantic_manifest.json` exists alongside `manifest.json`: diff --git a/website/docs/docs/dbt-cloud-apis/sl-manifest.md b/website/docs/reference/artifacts/sl-manifest.md similarity index 90% rename from website/docs/docs/dbt-cloud-apis/sl-manifest.md rename to website/docs/reference/artifacts/sl-manifest.md index d5bcf5a6774..03e661841c4 100644 --- a/website/docs/docs/dbt-cloud-apis/sl-manifest.md +++ b/website/docs/reference/artifacts/sl-manifest.md @@ -7,26 +7,24 @@ sidebar_label: "Semantic manifest" pagination_next: null --- +**Produced by:** Any command that parses your project. This includes all commands _except_ [`deps`](/reference/commands/deps), [`clean`](/reference/commands/clean), [`debug`](/reference/commands/debug), and [`init`](/reference/commands/init). + dbt creates an [artifact](/reference/artifacts/dbt-artifacts) file called the _Semantic Manifest_ (`semantic_manifest.json`), which MetricFlow requires to build and run metric queries properly for the dbt Semantic Layer. This artifact contains comprehensive information about your dbt Semantic Layer. It is an internal file that acts as the integration point with MetricFlow. By using the semantic manifest produced by dbt Core, MetricFlow will instantiate a data flow plan and generate SQL from Semantic Layer query requests. It's a valuable reference that you can use to understand the structure and details of your data models. Similar to the [`manifest.json` file](/reference/artifacts/manifest-json), the `semantic_manifest.json` file also lives in the [target directory](/reference/global-configs/json-artifacts) of your dbt project where dbt stores various artifacts (such as compiled models and tests) generated during the execution of your project. -## How it's produced - -Just like `manifest.json`, the `semantic_manifest.json` is produced whenever your dbt project is parsed. All dbt commands will parse your project and create a `semantic_manifest.json` file, _except_ [`deps`](/reference/commands/deps), [`clean`](/reference/commands/clean), [`debug`](/reference/commands/debug), and [`init`](/reference/commands/init). - - -## Top level keys +## Top-level keys Top-level keys for the semantic manifest are: - `semantic_models` — Starting points of data with entities, dimensions, and measures, and correspond to models in your dbt project. - `metrics` — Functions combining measures, constraints, and so on to define quantitative indicators. - `project_configuration` — Contains information around your project configurations -
-Example target/semantic_manifest.json file +### Example + + ```json { @@ -112,7 +110,7 @@ Top-level keys for the semantic manifest are: } ``` -
+ ## Related docs diff --git a/website/docusaurus.config.js b/website/docusaurus.config.js index 82eb6df54f4..dbd389a2299 100644 --- a/website/docusaurus.config.js +++ b/website/docusaurus.config.js @@ -72,19 +72,21 @@ var siteSettings = { }, announcementBar: { id: "biweekly-demos", - content: "Register now for Coalesce 2024 ✨ The Analytics Engineering Conference!", + content: + "Register now for Coalesce 2024 ✨ The Analytics Engineering Conference!", backgroundColor: "#7444FD", textColor: "#fff", isCloseable: true, }, announcementBarActive: true, - announcementBarLink: "https://coalesce.getdbt.com/register/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_coalesce-2024_aw&utm_content=coalesce____&utm_term=all_all__", + announcementBarLink: + "https://coalesce.getdbt.com/register/?utm_medium=internal&utm_source=docs&utm_campaign=q3-2025_coalesce-2024_aw&utm_content=coalesce____&utm_term=all_all__", // Set community spotlight member on homepage // This is the ID for a specific file under docs/community/spotlight communitySpotlightMember: "meagan-palmer", prism: { theme: (() => { - var theme = themes.nightOwl; + var theme = themes.nightOwl; // Add additional rule to nightowl theme in order to change // the color of YAML keys (to be different than values). // There weren't many Prism themes that differentiated @@ -200,6 +202,12 @@ var siteSettings = { links: [ { html: ` + +
Terms of Service Privacy Policy diff --git a/website/sidebars.js b/website/sidebars.js index 3b93c19616a..d31f6d03f57 100644 --- a/website/sidebars.js +++ b/website/sidebars.js @@ -727,7 +727,6 @@ const sidebarSettings = { "docs/dbt-cloud-apis/sl-jdbc", "docs/dbt-cloud-apis/sl-graphql", "docs/dbt-cloud-apis/sl-python", - "docs/dbt-cloud-apis/sl-manifest", ], }, ], @@ -1174,6 +1173,7 @@ const sidebarSettings = { "reference/artifacts/run-results-json", "reference/artifacts/catalog-json", "reference/artifacts/sources-json", + "reference/artifacts/sl-manifest", "reference/artifacts/other-artifacts", ], }, diff --git a/website/snippets/_auto-exposures-view.md b/website/snippets/_auto-exposures-view.md index 95f81782cab..d30b47ae21d 100644 --- a/website/snippets/_auto-exposures-view.md +++ b/website/snippets/_auto-exposures-view.md @@ -1,4 +1,4 @@ -## View auto-exposures in dbt Explorer +## View auto-exposures in dbt Explorer After setting up auto-exposures in dbt Cloud, you can view them in dbt Explorer for a richer experience: 1. Navigate to dbt Explorer by clicking on the **Explore** link in the navigation. diff --git a/website/snippets/_sl-run-prod-job.md b/website/snippets/_sl-run-prod-job.md index f820b7f3f79..318b8d27cbf 100644 --- a/website/snippets/_sl-run-prod-job.md +++ b/website/snippets/_sl-run-prod-job.md @@ -6,7 +6,7 @@ This section explains how you can perform a job run in your deployment environme 3. To create a new environment, navigate to **Deploy** in the navigation menu, select **Environments**, and then select **Create new environment**. 4. Fill in your deployment credentials with your Snowflake username and password. You can name the schema anything you want. Click **Save** to create your new production environment. 5. [Create a new deploy job](/docs/deploy/deploy-jobs#create-and-schedule-jobs) that runs in the environment you just created. Go back to the **Deploy** menu, select **Jobs**, select **Create job**, and click **Deploy job**. -6. Set the job to run a `dbt parse` job to parse your projects and generate a [`semantic_manifest.json` artifact](/docs/dbt-cloud-apis/sl-manifest) file. Although running `dbt build` isn't required, you can choose to do so if needed. +6. Set the job to run a `dbt parse` job to parse your projects and generate a [`semantic_manifest.json` artifact](/reference/artifacts/sl-manifest) file. Although running `dbt build` isn't required, you can choose to do so if needed. 7. Run the job by clicking the **Run now** button. Monitor the job's progress in real-time through the **Run summary** tab. Once the job completes successfully, your dbt project, including the generated documentation, will be fully deployed and available for use in your production environment. If any issues arise, review the logs to diagnose and address any errors. diff --git a/website/vercel.json b/website/vercel.json index 4f5a92ccb08..0674313f3f5 100644 --- a/website/vercel.json +++ b/website/vercel.json @@ -2,6 +2,11 @@ "cleanUrls": true, "trailingSlash": false, "redirects": [ + { + "source": "/docs/dbt-cloud-apis/sl-manifest", + "destination": "/reference/artifacts/sl-manifest", + "permanent": true + }, { "source": "/docs/cloud/dbt-assist-data", "destination": "/docs/cloud/dbt-copilot-data",