feature_lookup

class databricks.feature_store.entities.feature_lookup.FeatureLookup(table_name: str, lookup_key: Union[str, List[str]], *, feature_names: Union[str, List[str], None] = None, rename_outputs: Optional[Dict[str, str]] = None, **kwargs)

Bases: databricks.feature_store.entities._feature_store_object._FeatureStoreObject

Value class used to specify a feature to use in a TrainingSet.

Parameters:
  • table_name – Feature table name.
  • lookup_key – Key to use when joining this feature table with the DataFrame passed to FeatureStoreClient.create_training_set(). The lookup_key must be the columns in the DataFrame passed to FeatureStoreClient.create_training_set(). The type of lookup_key columns in that DataFrame must match the type of the primary key of the feature table referenced in this FeatureLookup.
  • feature_names – A single feature name, a list of feature names, or None to lookup all features (excluding primary keys) in the feature table at the time that the training set is created. If your model requires primary keys as features, you can declare them as independent FeatureLookups.
  • rename_outputs – If provided, renames features in the TrainingSet returned by of FeatureStoreClient.create_training_set.
  • feature_name – Feature name. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use feature_names.
  • output_name – If provided, rename this feature in the output of FeatureStoreClient.create_training_set. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use rename_outputs.

Properties

table_name

The table name to use in this FeatureLookup.

lookup_key

The lookup key(s) to use in this FeatureLookup.

feature_name

The feature name to use in this FeatureLookup. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use feature_names.

output_name

The output name to use in this FeatureLookup. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use feature_names.