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meta

dbt_project.yml
models:
  <resource-path>:
    +meta: {<dictionary>}

models/schema.yml

models:
  - name: model_name
    config:
      meta: {<dictionary>}

    columns:
      - name: column_name
        config:
          meta: {<dictionary>} # changed to config in v1.10 and backported to 1.9

The meta config can be defined:

  • Under the models config in the project file (shown in previous 'models/schema.yml' example)
  • Under the models config in the project file (dbt_project.yml)
  • in a config() Jinja macro within a model's SQL file

See configs and properties for details.

Definition​

The meta field can be used to set metadata for a resource and accepts any key-value pairs. This metadata is compiled into the manifest.json file generated by dbt, and is viewable in the auto-generated documentation.

Depending on the resource you're configuring, meta may be available within the config property, and/or as a top-level key. (For backwards compatibility, meta is often (but not always) supported as a top-level key, though without the capabilities of config inheritance.)

Examples​

To demonstrate how to use the meta config, here are some examples:

Designate a model owner​

Additionally, indicate the maturity of a model using a model_maturity: key.

models/schema.yml

models:
  - name: users
    config:
      meta:
        owner: "@alice"
        model_maturity: in dev

Designate a source column as containing PII​

models/schema.yml

sources:
  - name: salesforce
    tables:
      - name: account
        config:
          meta:
            contains_pii: true
        columns:
          - name: email
            config:
              meta: # changed to config in v1.10 and backported to 1.9
                contains_pii: true

Configure one meta attribute for all seeds​

dbt_project.yml
seeds:
  +meta:
    favorite_color: red

Override one meta attribute for a single model​

models/my_model.sql
{{ config(meta = {
    'single_key': 'override'
}) }}

select 1 as id

Assign owner and favorite_color in the dbt_project.yml as a config property​

dbt_project.yml
models:
  jaffle_shop:
    +meta:
      owner: "@alice"
      favorite_color: red

Assign meta to semantic model​

Assign meta to dimensions, measures, entities​

Access meta values in Python models​

To access custom meta values in Python models, first retrieve the meta object using the dbt.config.get() method, then access your custom values from it.

For example, if you have a model named my_python_model and you want to store custom values, you can do the following:

models/schema.yml
models:
  - name: my_python_model
    config:
      meta:
        batch_size: 1000
        processing_mode: "incremental"
models/my_python_model.py
def model(dbt, session):
    # First, get the meta object
    meta = dbt.config.get("meta")
    
    # Then access your custom values from meta
    batch_size = meta.get("batch_size")
    processing_mode = meta.get("processing_mode")
    
    # Use the meta values in your model logic
    df = dbt.ref("upstream_model")
    
    if processing_mode == "incremental":
        df = df.limit(batch_size)
    
    return df

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