From a490897f551591831c5da361861e6d8adf6d3537 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Mon, 29 Jan 2024 18:50:33 +1300 Subject: [PATCH 1/6] Rework custom schema docs --- website/docs/docs/build/custom-schemas.md | 132 +++++++++++----------- 1 file changed, 67 insertions(+), 65 deletions(-) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index b20d4130725..feb9d41bf5d 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -4,25 +4,28 @@ id: "custom-schemas" pagination_next: "docs/build/custom-databases" --- -By default, all dbt models are built in the schema specified in your target. In dbt projects with lots of models, it may be useful to instead build some models in schemas other than your target schema – this can help logically group models together. +By default, all dbt models are built in the schema specified in your [environment](/docs/dbt-cloud-environments) (dbt Cloud) or [profile's target](/docs/core/dbt-core-environments) (dbt Core). This default schema is called your **target schema**. + +In dbt projects with lots of models, it is often preferable to build models across multiple schemas and group similar models together. For example, you may wish to: -For example, you may wish to: * Group models based on the business unit using the model, creating schemas such as `core`, `marketing`, `finance` and `support`; or, * Hide intermediate models in a `staging` schema, and only present models that should be queried by an end user in an `analytics` schema. -You can use **custom schemas** in dbt to build models in a schema other than your target schema. It's important to note that by default, dbt will generate the schema name for a model by **concatenating the custom schema to the target schema**, as in: `_;`. +To do this, specify a custom schema. dbt will then generate the schema name for a model by **appending the custom schema to the target schema**, as in: `_`. | Target schema | Custom schema | Resulting schema | | ------------- | ------------- | ---------------- | -| <target_schema> | None | <target_schema> | -| analytics | None | analytics | -| dbt_alice | None | dbt_alice | -| <target_schema> | <custom_schema> | <target_schema>\_<custom_schema> | -| analytics | marketing | analytics_marketing | -| dbt_alice | marketing | dbt_alice_marketing | +| analytics_prod | None | analytics_prod | +| alice_dev | None | alice_dev | +| dbt_cloud_pr_123_456 | None | dbt_cloud_pr_123_456 | +| analytics_prod | marketing | analytics_prod_marketing | +| alice_dev | marketing | alice_dev_marketing | +| dbt_cloud_pr_123_456 | marketing | dbt_cloud_pr_123_456_marketing | ## How do I use custom schemas? -Use the `schema` configuration key to specify a custom schema for a model. As with any configuration, you can either: + +Use the `schema` configuration key. As with any configuration, you can either: + * apply this configuration to a specific model by using a config block within a model, or * apply it to a subdirectory of models by specifying it in your `dbt_project.yml` file @@ -36,12 +39,10 @@ select ... - - ```yaml -# models in `models/marketing/ will be rendered to the "*_marketing" schema +# models in `models/marketing/ will be built in the "*_marketing" schema models: my_project: marketing: @@ -52,17 +53,17 @@ models: ## Understanding custom schemas -When first using custom schemas, it's common to assume that a model will be built in a schema that matches the `schema` configuration exactly, for example, a model that has the configuration `schema: marketing`, would be built in the `marketing` schema. However, dbt instead creates it in a schema like `_marketing` by default – there's a good reason for this! +When first using custom schemas, it's common to assume that a model will use _only_ the new `schema` configuration, for example, a model that has the configuration `schema: marketing`, would be built in the `marketing` schema. However, dbt will actually put it in a schema like `_marketing` – there's a good reason for this! -In a typical setup of dbt, each dbt user will use a separate target schema (see [Managing Environments](/docs/build/custom-schemas#managing-environments)). If dbt created models in a schema that matches a model's custom schema exactly, every dbt user would create models in the same schema. +Each dbt user has their own target schema for development (see [Managing Environments](#managing-environments)). If dbt ignored the target schema and only used the model's custom schema, every dbt user would create models in the same schema and would overwrite each other's work. -Further, the schema that your development models are built in would be the same schema that your production models are built in! Instead, concatenating the custom schema to the target schema helps create distinct schema names, reducing naming conflicts. +This would be bad enough if it was only development schemas overwriting each other, but it would _also_ impact your production models. By combining the target schema and the custom schema, dbt ensures that objects it creates in your data warehouse don't collide with one another. If you prefer to use different logic for generating a schema name, you can change the way dbt generates a schema name (see below). ### How does dbt generate a model's schema name? -dbt uses a default macro called `generate_schema_name` to determine the name of the schema that a model should be built in. +dbt uses a default macro called `generate_schema_name` to determine the name of the schema that a model should be built in. The following code represents the default macro's logic: @@ -83,30 +84,23 @@ The following code represents the default macro's logic: {%- endmacro %} ``` -## Advanced custom schema configuration - -You can customize schema name generation in dbt depending on your needs, such as creating a custom macro named `generate_schema_name` in your project or using the built-in macro for environment-based schema names. The built-in macro follows a pattern of generating schema names based on the environment, making it a convenient alternative. - -If your dbt project has a macro that’s also named `generate_schema_name`, dbt will always use the macro in your dbt project instead of the default macro. - -### Changing the way dbt generates a schema name +## Changing the way dbt generates a schema name -To modify how dbt generates schema names, you should add a macro named `generate_schema_name` to your project and customize it according to your needs: +If your dbt project has a custom macro called `generate_schema_name`, dbt will use it instead of the default macro. This allows you to customize the name generation according to your needs. -- Copy and paste the `generate_schema_name` macro into a file named 'generate_schema_name'. +To customize this macro, copy the example code above into a file named `macros/generate_schema_name.sql` and make changes as necessary. -- Modify the target schema by either using [target variables](/reference/dbt-jinja-functions/target) or [env_var](/reference/dbt-jinja-functions/env_var). Check out our [Advanced Deployment - Custom Environment and job behavior](https://courses.getdbt.com/courses/advanced-deployment) course video for more details. - -**Note**: dbt will ignore any custom `generate_schema_name` macros included in installed packages. +**Note**: dbt will ignore any custom `generate_schema_name` macros included in installed packages.
❗️ Warning: Don't replace default_schema in the macro. -If you're modifying how dbt generates schema names, don't just replace ```{{ default_schema }}_{{ custom_schema_name | trim }}``` with ```{{ custom_schema_name | trim }}``` in the ```generate_schema_name``` macro. +If you're modifying how dbt generates schema names, don't just replace ```{{ default_schema }}_{{ custom_schema_name | trim }}``` with ```{{ custom_schema_name | trim }}``` in the ```generate_schema_name``` macro. If you remove ```{{ default_schema }}```, it causes developers to override each other's models if they create their own custom schemas. This can also cause issues during development and continuous integration (CI). -❌ The following code block is an example of what your code _should not_ look like: +❌ The following code block is an example of what your code _should not_ look like: + ```sql {% macro generate_schema_name(custom_schema_name, node) -%} @@ -123,39 +117,9 @@ If you remove ```{{ default_schema }}```, it causes developers to override each {%- endmacro %} -``` -
- -### An alternative pattern for generating schema names - -A common way to generate schema names is by adjusting the behavior according to the environment in dbt. Here's how it works: - -**Production environment** - -- If a custom schema is specified, the schema name of a model should match the custom schema, instead of concatenating to the target schema. -- If no custom schema is specified, the schema name of a model should match the target schema. - -**Other environments** (like development or quality assurance (QA)): - -- Build _all_ models in the target schema, ignoring any custom schema configurations. - -dbt ships with a global, predefined macro that contains this logic - `generate_schema_name_for_env`. - -If you want to use this pattern, you'll need a `generate_schema_name` macro in your project that points to this logic. You can do this by creating a file in your `macros` directory (typically named `get_custom_schema.sql`), and copying/pasting the following code: - - - -```sql --- put this in macros/get_custom_schema.sql - -{% macro generate_schema_name(custom_schema_name, node) -%} - {{ generate_schema_name_for_env(custom_schema_name, node) }} -{%- endmacro %} ``` - - -**Note:** When using this macro, you'll need to set the target name in your job specifically to "prod" if you want custom schemas to be applied. + ### generate_schema_name arguments @@ -165,6 +129,7 @@ If you want to use this pattern, you'll need a `generate_schema_name` macro in y | node | The `node` that is currently being processed by dbt | `{"name": "my_model", "resource_type": "model",...}` | ### Jinja context available in generate_schema_name + If you choose to write custom logic to generate a schema name, it's worth noting that not all variables and methods are available to you when defining this logic. In other words: the `generate_schema_name` macro is compiled with a limited Jinja context. The following context methods _are_ available in the `generate_schema_name` macro: @@ -192,12 +157,49 @@ See docs on macro `dispatch`: ["Managing different global overrides across packa +## A built-in alternative pattern for generating schema names + +A common customization is to ignore the target schema in production environments, and ignore the custom schema configurations in other environments (such as development and CI). + +Production Environment (`target.name == 'prod'`) +| Target schema | Custom schema | Resulting schema | +| ------------- | ------------- | ---------------- | +| analytics_prod | None | analytics_prod | +| analytics_prod | marketing | marketing | + +Development/CI Environment (`target.name != 'prod'`) +| Target schema | Custom schema | Resulting schema | +| ------------- | ------------- | ---------------- | +| alice_dev | None | alice_dev | +| alice_dev | marketing | alice_dev | +| dbt_cloud_pr_123_456 | None | dbt_cloud_pr_123_456 | +| dbt_cloud_pr_123_456 | marketing | dbt_cloud_pr_123_456 | + +Just like the normal macro, this approach guarantees that schemas from different environments will not collide. + +dbt ships with a macro for this use case – called `generate_schema_name_for_env` – which is disabled by default. To enable it, add a custom `generate_schema_name` macro to your project that contains the following code: + + + +```sql +-- put this in macros/get_custom_schema.sql + +{% macro generate_schema_name(custom_schema_name, node) -%} + {{ generate_schema_name_for_env(custom_schema_name, node) }} +{%- endmacro %} +``` + + + +**Note:** When using this macro, you'll need to set the target name in your production job to `prod`. + ## Managing environments -In the `generate_schema_name` macro examples shown above, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must additionally ensure that your different dbt environments are configured appropriately. While you can use any naming scheme you'd like, we typically recommend: - - **dev**: Your local development environment; configured in a `profiles.yml` file on your computer. +In the `generate_schema_name` macro examples shown above, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must ensure that your different dbt environments are configured accordingly. While you can use any naming scheme you'd like, we typically recommend: + +* **dev**: Your local development environment; configured in a `profiles.yml` file on your computer. * **ci**: A [continuous integration](/docs/cloud/git/connect-github) environment running on Pull Requests in GitHub, GitLab, etc. - - **prod**: The production deployment of your dbt project, like in dbt Cloud, Airflow, or [similar](/docs/deploy/deployments). +* **prod**: The production deployment of your dbt project, like in dbt Cloud, Airflow, or [similar](/docs/deploy/deployments). If your schema names are being generated incorrectly, double check your target name in the relevant environment. From 1f6a30d90ebd893f579699bd523c22c0518af523 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Mon, 29 Jan 2024 19:08:53 +1300 Subject: [PATCH 2/6] add line breaks --- website/docs/docs/build/custom-schemas.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index feb9d41bf5d..eb28c46fab1 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -162,12 +162,14 @@ See docs on macro `dispatch`: ["Managing different global overrides across packa A common customization is to ignore the target schema in production environments, and ignore the custom schema configurations in other environments (such as development and CI). Production Environment (`target.name == 'prod'`) + | Target schema | Custom schema | Resulting schema | | ------------- | ------------- | ---------------- | | analytics_prod | None | analytics_prod | | analytics_prod | marketing | marketing | Development/CI Environment (`target.name != 'prod'`) + | Target schema | Custom schema | Resulting schema | | ------------- | ------------- | ---------------- | | alice_dev | None | alice_dev | From 8281981ae404a50de0063e5c80491101bbb5a878 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Thu, 1 Feb 2024 11:08:41 +1300 Subject: [PATCH 3/6] tweak on self-review --- website/docs/docs/build/custom-schemas.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index eb28c46fab1..b9a8ccfff81 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -53,11 +53,11 @@ models: ## Understanding custom schemas -When first using custom schemas, it's common to assume that a model will use _only_ the new `schema` configuration, for example, a model that has the configuration `schema: marketing`, would be built in the `marketing` schema. However, dbt will actually put it in a schema like `_marketing` – there's a good reason for this! +When first using custom schemas, it's a common misunderstanding to assume that a model will use _only_ the new `schema` configuration, for example, a model that has the configuration `schema: marketing` would be built in the `marketing` schema. However, dbt will actually put it in a schema like `_marketing`. -Each dbt user has their own target schema for development (see [Managing Environments](#managing-environments)). If dbt ignored the target schema and only used the model's custom schema, every dbt user would create models in the same schema and would overwrite each other's work. +There's a good reason for this deviation! Each dbt user has their own target schema for development (see [Managing Environments](#managing-environments)). If dbt ignored the target schema and only used the model's custom schema, every dbt user would create models in the same schema and would overwrite each other's work. -This would be bad enough if it was only development schemas overwriting each other, but it would _also_ impact your production models. By combining the target schema and the custom schema, dbt ensures that objects it creates in your data warehouse don't collide with one another. +By combining the target schema and the custom schema, dbt ensures that objects it creates in your data warehouse don't collide with one another. If you prefer to use different logic for generating a schema name, you can change the way dbt generates a schema name (see below). From 7d59f7469bd2b344c977dcd3e8fdcfc93b19ffbd Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Fri, 2 Feb 2024 15:31:25 +1300 Subject: [PATCH 4/6] Apply suggestions from code review Co-authored-by: Ly Nguyen <107218380+nghi-ly@users.noreply.github.com> --- website/docs/docs/build/custom-schemas.md | 34 +++++++++++------------ 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index b9a8ccfff81..086aeae0853 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -4,14 +4,14 @@ id: "custom-schemas" pagination_next: "docs/build/custom-databases" --- -By default, all dbt models are built in the schema specified in your [environment](/docs/dbt-cloud-environments) (dbt Cloud) or [profile's target](/docs/core/dbt-core-environments) (dbt Core). This default schema is called your **target schema**. +By default, all dbt models are built in the schema specified in your [environment](/docs/dbt-cloud-environments) (dbt Cloud) or [profile's target](/docs/core/dbt-core-environments) (dbt Core). This default schema is called your _target schema_. -In dbt projects with lots of models, it is often preferable to build models across multiple schemas and group similar models together. For example, you may wish to: +For dbt projects with lots of models, it's common to build models across multiple schemas and group similar models together. For example, you might want to: -* Group models based on the business unit using the model, creating schemas such as `core`, `marketing`, `finance` and `support`; or, +* Group models based on the business unit using the model, creating schemas such as `core`, `marketing`, `finance` and `support` * Hide intermediate models in a `staging` schema, and only present models that should be queried by an end user in an `analytics` schema. -To do this, specify a custom schema. dbt will then generate the schema name for a model by **appending the custom schema to the target schema**, as in: `_`. +To do this, specify a custom schema. dbt generates the schema name for a model by appending the custom schema to the target schema. For example, `_`. | Target schema | Custom schema | Resulting schema | | ------------- | ------------- | ---------------- | @@ -24,9 +24,9 @@ To do this, specify a custom schema. dbt will then generate the schema name for ## How do I use custom schemas? -Use the `schema` configuration key. As with any configuration, you can either: +To specify a custom schema for a model, use the `schema` configuration key. As with any configuration, you can do one of the following: -* apply this configuration to a specific model by using a config block within a model, or +* apply this configuration to a specific model by using a config block within a model * apply it to a subdirectory of models by specifying it in your `dbt_project.yml` file @@ -53,9 +53,9 @@ models: ## Understanding custom schemas -When first using custom schemas, it's a common misunderstanding to assume that a model will use _only_ the new `schema` configuration, for example, a model that has the configuration `schema: marketing` would be built in the `marketing` schema. However, dbt will actually put it in a schema like `_marketing`. +When first using custom schemas, it's a common misunderstanding to assume that a model _only_ uses the new `schema` configuration; for example, a model that has the configuration `schema: marketing` would be built in the `marketing` schema. However, dbt puts it in a schema like `_marketing`. -There's a good reason for this deviation! Each dbt user has their own target schema for development (see [Managing Environments](#managing-environments)). If dbt ignored the target schema and only used the model's custom schema, every dbt user would create models in the same schema and would overwrite each other's work. +There's a good reason for this deviation. Each dbt user has their own target schema for development (refer to [Managing Environments](#managing-environments)). If dbt ignored the target schema and only used the model's custom schema, every dbt user would create models in the same schema and would overwrite each other's work. By combining the target schema and the custom schema, dbt ensures that objects it creates in your data warehouse don't collide with one another. @@ -88,9 +88,9 @@ The following code represents the default macro's logic: If your dbt project has a custom macro called `generate_schema_name`, dbt will use it instead of the default macro. This allows you to customize the name generation according to your needs. -To customize this macro, copy the example code above into a file named `macros/generate_schema_name.sql` and make changes as necessary. +To customize this macro, copy the example code in the section [How does dbt generate a model's schema name](#how-does-dbt-generate-a-models-schema-name) into a file named `macros/generate_schema_name.sql` and make changes as necessary. -**Note**: dbt will ignore any custom `generate_schema_name` macros included in installed packages. +Be careful. dbt will ignore any custom `generate_schema_name` macros included in installed packages.
❗️ Warning: Don't replace default_schema in the macro. @@ -177,9 +177,9 @@ Development/CI Environment (`target.name != 'prod'`) | dbt_cloud_pr_123_456 | None | dbt_cloud_pr_123_456 | | dbt_cloud_pr_123_456 | marketing | dbt_cloud_pr_123_456 | -Just like the normal macro, this approach guarantees that schemas from different environments will not collide. +Similar to the regular macro, this approach guarantees that schemas from different environments will not collide. -dbt ships with a macro for this use case – called `generate_schema_name_for_env` – which is disabled by default. To enable it, add a custom `generate_schema_name` macro to your project that contains the following code: +dbt ships with a macro for this use case — called `generate_schema_name_for_env` — which is disabled by default. To enable it, add a custom `generate_schema_name` macro to your project that contains the following code: @@ -193,16 +193,16 @@ dbt ships with a macro for this use case – called `generate_schema_name_for_en -**Note:** When using this macro, you'll need to set the target name in your production job to `prod`. +When using this macro, you'll need to set the target name in your production job to `prod`. ## Managing environments In the `generate_schema_name` macro examples shown above, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must ensure that your different dbt environments are configured accordingly. While you can use any naming scheme you'd like, we typically recommend: -* **dev**: Your local development environment; configured in a `profiles.yml` file on your computer. -* **ci**: A [continuous integration](/docs/cloud/git/connect-github) environment running on Pull Requests in GitHub, GitLab, etc. -* **prod**: The production deployment of your dbt project, like in dbt Cloud, Airflow, or [similar](/docs/deploy/deployments). +* **dev** — Your local development environment; configured in a `profiles.yml` file on your computer. +* **ci** — A [continuous integration](/docs/cloud/git/connect-github) environment running on pull pequests in GitHub, GitLab, and so on. +* **prod** — The production deployment of your dbt project, like in dbt Cloud, Airflow, or [similar](/docs/deploy/deployments). -If your schema names are being generated incorrectly, double check your target name in the relevant environment. +If your schema names are being generated incorrectly, double-check your target name in the relevant environment. For more information, consult the [managing environments in dbt Core](/docs/core/dbt-core-environments) guide. From d5d62ec6cd37794a9392a21a06690a84b724b543 Mon Sep 17 00:00:00 2001 From: Joel Labes Date: Fri, 2 Feb 2024 15:34:21 +1300 Subject: [PATCH 5/6] Apply final change from code review --- website/docs/docs/build/custom-schemas.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index 086aeae0853..042bb45a744 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -197,7 +197,7 @@ When using this macro, you'll need to set the target name in your production job ## Managing environments -In the `generate_schema_name` macro examples shown above, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must ensure that your different dbt environments are configured accordingly. While you can use any naming scheme you'd like, we typically recommend: +In the `generate_schema_name` macro examples shown in the [built-in alternative pattern](#a-built-in-alternative-pattern-for-generating-schema-names) section, the `target.name` context variable is used to change the schema name that dbt generates for models. If the `generate_schema_name` macro in your project uses the `target.name` context variable, you must ensure that your different dbt environments are configured accordingly. While you can use any naming scheme you'd like, we typically recommend: * **dev** — Your local development environment; configured in a `profiles.yml` file on your computer. * **ci** — A [continuous integration](/docs/cloud/git/connect-github) environment running on pull pequests in GitHub, GitLab, and so on. From 97b27a0b9436956292d6cad0d6a12dd8b4af4ea1 Mon Sep 17 00:00:00 2001 From: Ly Nguyen <107218380+nghi-ly@users.noreply.github.com> Date: Fri, 2 Feb 2024 15:53:29 -0800 Subject: [PATCH 6/6] Update website/docs/docs/build/custom-schemas.md --- website/docs/docs/build/custom-schemas.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/docs/docs/build/custom-schemas.md b/website/docs/docs/build/custom-schemas.md index 042bb45a744..24cd4194a1c 100644 --- a/website/docs/docs/build/custom-schemas.md +++ b/website/docs/docs/build/custom-schemas.md @@ -8,7 +8,7 @@ By default, all dbt models are built in the schema specified in your [environmen For dbt projects with lots of models, it's common to build models across multiple schemas and group similar models together. For example, you might want to: -* Group models based on the business unit using the model, creating schemas such as `core`, `marketing`, `finance` and `support` +* Group models based on the business unit using the model, creating schemas such as `core`, `marketing`, `finance` and `support`. * Hide intermediate models in a `staging` schema, and only present models that should be queried by an end user in an `analytics` schema. To do this, specify a custom schema. dbt generates the schema name for a model by appending the custom schema to the target schema. For example, `_`.