From 81064171d0d34f845977bd588062688f4c0755fc Mon Sep 17 00:00:00 2001 From: mirnawong1 Date: Thu, 29 Feb 2024 17:04:36 +0000 Subject: [PATCH] update env var --- website/docs/docs/build/saved-queries.md | 4 +- .../release-notes/72-Feb-2024/exports-rn.md | 8 +-- .../docs/docs/deploy/deployment-overview.md | 2 +- .../docs/use-dbt-semantic-layer/dbt-sl.md | 4 +- .../docs/use-dbt-semantic-layer/exports.md | 56 +++++++++++++----- .../semantic-layer/env-var-dbt-exports.jpg | Bin 0 -> 59738 bytes 6 files changed, 51 insertions(+), 23 deletions(-) create mode 100644 website/static/img/docs/dbt-cloud/semantic-layer/env-var-dbt-exports.jpg diff --git a/website/docs/docs/build/saved-queries.md b/website/docs/docs/build/saved-queries.md index 4083d2fb6b8..0c3d8a7fc1c 100644 --- a/website/docs/docs/build/saved-queries.md +++ b/website/docs/docs/build/saved-queries.md @@ -15,8 +15,8 @@ Saved queries are distinct from [exports](/docs/use-dbt-semantic-layer/exports), | Feature | Exports |
Saved queries
| | ----------- | ----------- | ---------------- | | **Availability** | Available on dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plans on dbt versions 1.7 or newer.| Available in both dbt Core and dbt Cloud. | -| **Purpose** | To materialize saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, which includes metrics and dimensions. | -| **Usage** | Automatically runs saved queries and materializes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage.

**Example**: Creating a weekly aggregated table for active user metrics, automatically updated and stored in the data platform. | Used for organizing and reusing common MetricFlow queries within dbt projects.


**Example**: Group related metrics together for better organization, and include commonly uses dimensions and filters. | For materializing query results in the data platform. | +| **Purpose** | To write saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, which includes metrics and dimensions. | +| **Usage** | Automatically runs saved queries and writes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage.

**Example**: Creating a weekly aggregated table for active user metrics, automatically updated and stored in the data platform. | Used for organizing and reusing common MetricFlow queries within dbt projects.


**Example**: Group related metrics together for better organization, and include commonly uses dimensions and filters. | For materializing query results in the data platform. | | **Integration** | Must have the dbt Semantic Layer configured in your dbt project.

Tightly integrated with the [MetricFlow Server](/docs/use-dbt-semantic-layer/sl-architecture#components) and dbt Cloud's job scheduler. | Integrated into the dbt and managed alongside other dbt nodes. | | **Configuration** | Defined within the `saved_queries` configuration. Set up within the dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files. | diff --git a/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md b/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md index bccff7995b1..e6fbb2e3f4d 100644 --- a/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md +++ b/website/docs/docs/dbt-versions/release-notes/72-Feb-2024/exports-rn.md @@ -1,13 +1,13 @@ --- -title: "New: Use exports to materialize saved queries" -description: "February 2024: Use the exports feature to materialize and schedule saved queries with dbt Cloud, and integrate with additional tools." -sidebar_label: "New: Use exports to materialize saved queries" +title: "New: Use exports to write saved queries" +description: "February 2024: Use the exports feature to write and schedule saved queries with dbt Cloud, and integrate with additional tools." +sidebar_label: "New: Use exports to write saved queries" sidebar_position: 09 tags: [Feb-2024] date: 2024-02-07 --- -You can now use the [exports](/docs/use-dbt-semantic-layer/exports) feature with [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), allowing you to query reliable metrics and fast data reporting. Exports enhance the saved queries feature, allowing you to materialize commonly used queries directly within your data platform using dbt Cloud's job scheduler. +You can now use the [exports](/docs/use-dbt-semantic-layer/exports) feature with [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), allowing you to query reliable metrics and fast data reporting. Exports enhance the saved queries feature, allowing you to write commonly used queries directly within your data platform using dbt Cloud's job scheduler. By exposing tables of metrics and dimensions, exports enable you to integrate with additional tools that don't natively connect with the dbt Semantic Layer, such as PowerBI. diff --git a/website/docs/docs/deploy/deployment-overview.md b/website/docs/docs/deploy/deployment-overview.md index 8731e9f0c1b..8b87625bd09 100644 --- a/website/docs/docs/deploy/deployment-overview.md +++ b/website/docs/docs/deploy/deployment-overview.md @@ -16,7 +16,7 @@ dbt Cloud offers the easiest and most reliable way to run your dbt project in pr - Identify the root cause of failures in deployment environments - Maintain high-quality code and data in production - Gain visibility into the health of deployment jobs, models, and tests -- Uses [exports](/docs/use-dbt-semantic-layer/exports) to materialize [saved queries](/docs/build/saved-queries) in your data platform for reliable and fast metric reporting +- Uses [exports](/docs/use-dbt-semantic-layer/exports) to write [saved queries](/docs/build/saved-queries) in your data platform for reliable and fast metric reporting Before continuing, make sure you understand dbt's approach to [deployment environments](/docs/deploy/deploy-environments). diff --git a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md index 3b81e700fce..6fe63b08a7a 100644 --- a/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md +++ b/website/docs/docs/use-dbt-semantic-layer/dbt-sl.md @@ -48,8 +48,8 @@ plan="dbt Cloud Team or Enterprise" icon="dbt-bit"/> diff --git a/website/docs/docs/use-dbt-semantic-layer/exports.md b/website/docs/docs/use-dbt-semantic-layer/exports.md index 79d94f7bebf..1077da69f4e 100644 --- a/website/docs/docs/use-dbt-semantic-layer/exports.md +++ b/website/docs/docs/use-dbt-semantic-layer/exports.md @@ -1,16 +1,14 @@ --- -title: "Materialize queries with exports" -description: "Use exports to materialize tables to the data platform on a schedule." -sidebar_label: "Materialize with exports" +title: "Write queries with exports" +description: "Use exports to write tables to the data platform on a schedule." +sidebar_label: "Write commonly used queries" --- -# Materialize queries with exports - -The exports feature in the dbt Semantic Layer enhances the [saved queries](/docs/build/saved-queries) by allowing you to materialize commonly used queries directly within your data platform. +The exports feature in the dbt Semantic Layer enhances the [saved queries](/docs/build/saved-queries) by allowing you to write commonly used queries directly within your data platform. While saved queries are a way to save and reuse commonly used queries in MetricFlow, exports take this functionality a step further by: -- Enabling you to materialize these queries within your data platform using dbt Cloud. +- Enabling you to write these queries within your data platform using dbt Cloud. - Proving an integration path for tools that don't natively support the dbt Semantic Layer by exposing tables of metrics and dimensions. Essentially, exports are like any other table in your data platform. They enable you to query metric definitions through any SQL interface or connect to downstream tools without a first-class Semantic Layer integration. Refer to [Available integrations](/docs/use-dbt-semantic-layer/avail-sl-integrations) for more information. @@ -29,14 +27,14 @@ Essentially, exports are like any other table in your data platform. They enable | Feature | Exports |
Saved queries
| | ----------- | ----------- | ---------------- | | **Availability** | Available on dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plans with dbt versions 1.7 or newer.| Available in both dbt Core and dbt Cloud. | -| **Purpose** | To materialize saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, including metrics and dimensions. | -| **Usage** | Automatically runs saved queries and materializes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage.

Example: Create a weekly aggregated table for active user metrics, automatically updated and stored in the data platform. | Used for organizing and reusing common MetricFlow queries within dbt projects.


Example: Group related metrics together for better organization, and include commonly used dimensions and filters. | For materializing query results in the data platform. | +| **Purpose** | To write saved queries in your data platform and expose metrics and dimensions as a view or table. | To define and manage common Semantic Layer queries in YAML, including metrics and dimensions. | +| **Usage** | Automatically runs saved queries and writes them within your data platform. Exports count towards [queried metrics](/docs/cloud/billing#what-counts-as-a-queried-metric) usage.

Example: Create a weekly aggregated table for active user metrics, automatically updated and stored in the data platform. | Used for organizing and reusing common MetricFlow queries within dbt projects.


Example: Group related metrics together for better organization, and include commonly used dimensions and filters. | For materializing query results in the data platform. | | **Integration** | Must have the dbt Semantic Layer configured in your dbt project.

Tightly integrated with the [MetricFlow Server](/docs/use-dbt-semantic-layer/sl-architecture#components) and dbt Cloud's job scheduler. | Integrated into the dbt and managed alongside other dbt nodes. | | **Configuration** | Defined within the `saved_queries` configuration. Set up within the dbt Cloud environment and job scheduler settings. | Defined in YAML format within dbt project files. | ## Define exports -Exports are an additional configuration added to a saved query. They define how to materialize a saved query, along with the schema and table name. +Exports are an additional configuration added to a saved query. They define how to write a saved query, along with the schema and table name. You can define `exports` in YAML format as a key within the `saved_queries` configuration and in the same file as your metric definitions. @@ -92,7 +90,7 @@ You can run an export in your development environment using your development cre dbt sl export ``` -You can also run any export defined for the saved query and materialize the table or view in your development environment. Refer to the following command example and output: +You can also run any export defined for the saved query and write the table or view in your development environment. Refer to the following command example and output: **Example** ```bash @@ -121,8 +119,8 @@ dbt sl export --saved-query sq_name --select export_1,export2 The `--select` flag is mainly used to include or exclude specific exports. If you need to change these settings, you can use the following flags to override export configurations: - `--export-as` — Defines the materialization type (table or view) for the export. This creates a new export with its own settings and is useful for testing in development. -- `--schema` — Specifies the schema to use for the materialized table or view. -- `--alias` — Assigns a custom alias to the materialized table or view. This overrides the default export name. +- `--schema` — Specifies the schema to use for the written table or view. +- `--alias` — Assigns a custom alias to the written table or view. This overrides the default export name. Be careful. The `--select` flag _can't_ be used with `alias` or `schema`. @@ -141,6 +139,8 @@ To enable exports in production using the dbt Cloud job scheduler: 1. [Create and execute exports](#create-and-execute-exports) #### Set environment variable + + 1. Click **Deploy** in the top navigation bar and choose **Environments**. 2. Select **Environment variables**. @@ -152,12 +152,40 @@ If exports aren't needed, you can set the value(s) to `FALSE` (`DBT_INCLUDE_SAVE + + + + + +1. Click **Deploy** in the top navigation bar and choose **Environments**. +2. Select **Environment variables**. +3. [Set the environment variable](/docs/build/environment-variables#setting-and-overriding-environment-variables) key to `DBT_EXPORT_SAVED_QUERIES` and the environment variable's value to `TRUE` (`DBT_EXPORT_SAVED_QUERIES=TRUE`). + +Doing this ensures saved queries and exports are included in your dbt build job. For example, running `dbt build sq_name` runs the equivalent of `dbt sl export --saved-query sq_name` in the dbt Cloud Job scheduler. + +If exports aren't needed, you can set the value(s) to `FALSE` (`DBT_EXPORT_SAVED_QUERIES=FALSE`). + + + + + When you run a build job, any saved queries downstream of the dbt models in that job will also run. To make sure your export data is up-to-date, run the export as a downstream step (after the model). #### Create and execute exports + + +1. Create a [deploy job](/docs/deploy/deploy-jobs) and ensure the `DBT_INCLUDE_SAVED_QUERY=TRUE` environment variable is set, as described in [Set environment variable](#set-environment-variable). + - This enables you to run any export that needs to be refreshed after a model is built. -1. Create a [deploy job](/docs/deploy/deploy-jobs) and ensure the `DBT_INCLUDE_SAVED_QUERY=TRUE` environment variable is set, as described in [Set environment variable](#set-environment-variable). + + + + +1. Create a [deploy job](/docs/deploy/deploy-jobs) and ensure the `DBT_EXPORT_SAVED_QUERIES=TRUE` environment variable is set, as described in [Set environment variable](#set-environment-variable). - This enables you to run any export that needs to be refreshed after a model is built. + + + 2. After dbt finishes building the models, the MetricFlow Server processes the exports, compiles the necessary SQL, and executes this SQL against your data platform. 3. Review the exports' execution details in the jobs logs and confirm the export was run successfully. This helps troubleshoot and to ensure accuracy. Since saved queries are integrated into the dbt DAG, all outputs related to exports are available in the job logs. 4. 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