w.materialized_features: Materialized Features

class databricks.sdk.service.ml.MaterializedFeaturesAPI

Materialized Features are columns in tables and views that can be directly used as features to train and serve ML models.

create_feature_tag(table_name: str, feature_name: str, feature_tag: FeatureTag) → FeatureTag

Creates a FeatureTag.

Parameters:

  • table_name – str

  • feature_name – str

  • feature_tag – FeatureTag

Returns:

FeatureTag

delete_feature_tag(table_name: str, feature_name: str, key: str)

Deletes a FeatureTag.

Parameters:

  • table_name – str The name of the feature table.

  • feature_name – str The name of the feature within the feature table.

  • key – str The key of the tag to delete.

get_feature_lineage(table_name: str, feature_name: str) → FeatureLineage

Get Feature Lineage.

Parameters:

  • table_name – str The full name of the feature table in Unity Catalog.

  • feature_name – str The name of the feature.

Returns:

FeatureLineage

get_feature_tag(table_name: str, feature_name: str, key: str) → FeatureTag

Gets a FeatureTag.

Parameters:

  • table_name – str

  • feature_name – str

  • key – str

Returns:

FeatureTag

list_feature_tags(table_name: str, feature_name: str [, page_size: Optional[int], page_token: Optional[str]]) → Iterator[FeatureTag]

Lists FeatureTags.

Parameters:

  • table_name – str

  • feature_name – str

  • page_size – int (optional) The maximum number of results to return.

  • page_token – str (optional) Pagination token to go to the next page based on a previous query.

Returns:

Iterator over FeatureTag

update_feature_tag(table_name: str, feature_name: str, key: str, feature_tag: FeatureTag [, update_mask: Optional[str]]) → FeatureTag

Updates a FeatureTag.

Parameters:

  • table_name – str

  • feature_name – str

  • key – str

  • feature_tag – FeatureTag

  • update_mask – str (optional) The list of fields to update.

Returns:

FeatureTag