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)
Value class used to specify a feature to use in a
- table_name – Feature table name.
- lookup_key – Key to use when joining this feature table with the
lookup_keymust be the columns in the DataFrame passed to
FeatureStoreClient.create_training_set(). The type of
lookup_keycolumns in that DataFrame must match the type of the primary key of the feature table referenced in this
- 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
TrainingSetreturned by of
- feature_name – Feature name. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use
- 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
The feature name to use in this FeatureLookup. Deprecated as of 0.3.4 [Databricks Runtime for ML 9.1]. Use