schema
- Model
- Seeds
- Snapshots
- Saved queries
- Test
Specify a custom schema for a group of models in your dbt_project.yml
file or a config block.
For example, if you have a group of marketing-related models and want to place them in a separate schema called marketing
, you can configure it like this:
models:
your_project:
marketing: # Grouping or folder for set of models
+schema: marketing
This would result in the generated relations for these models being located in the marketing
schema, so the full relation names would be analytics.target_schema_marketing.model_name
. This is because the schema of the relation is {{ target.schema }}_{{ schema }}
. The definition section explains this in more detail.
Configure a custom schema in your dbt_project.yml
file.
For example, if you have a seed that should be placed in a separate schema called mappings
, you can configure it like this:
seeds:
your_project:
product_mappings:
+schema: mappings
This would result in the generated relation being located in the mappings
schema, so the full relation name would be analytics.mappings.seed_name
.
saved-queries:
+schema: metrics
Customize the schema for storing test results in your dbt_project.yml
file.
For example, to save test results in a specific schema, you can configure it like this:
tests:
+store_failures: true
+schema: test_results
This would result in the test results being stored in the test_results
schema.
Refer to Usage for more examples.
Definition
Optionally specify a custom schema for a model, seed, snapshot, saved query, or test.
For users on dbt Cloud v1.8 or earlier, use the target_schema
config to specify a custom schema for a snapshot.
When dbt creates a relation (table/view) in a database, it creates it as: {{ database }}.{{ schema }}.{{ identifier }}
, e.g. analytics.finance.payments
The standard behavior of dbt is:
- If a custom schema is not specified, the schema of the relation is the target schema (
{{ target.schema }}
). - If a custom schema is specified, by default, the schema of the relation is
{{ target.schema }}_{{ schema }}
.
To learn more about changing the way that dbt generates a relation's schema
, read Using Custom Schemas
Usage
Models
Configure groups of models from the dbt_project.yml
file.
models:
jaffle_shop: # the name of a project
marketing:
+schema: marketing
Configure individual models using a config block:
{{ config(
schema='marketing'
) }}
Seeds
seeds:
+schema: mappings
Tests
Customize the name of the schema in which tests configured to store failures will save their results.
The resulting schema is {{ profile.schema }}_{{ tests.schema }}
, with a default suffix of dbt_test__audit
.
To use the same profile schema, set +schema: null
.
tests:
+store_failures: true
+schema: _sad_test_failures # Will write tables to my_database.my_schema__sad_test_failures
Ensure you have the authorization to create or access schemas for your work. To ensure that the required schemas have the correct permissions, run a sql statement in your respective data platform environment. For example, run the following command if using Redshift (exact authorization query may differ from one data platform to another):
create schema if not exists dev_username_dbt_test__audit authorization username;
Replace dev_username
with your specific development schema name and username
with the appropriate user who should have the permissions.
This command grants the appropriate permissions to create and access the dbt_test__audit
schema, which is often used with the store_failures
configuration.
Warehouse specific information
- BigQuery:
dataset
andschema
are interchangeable