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, timestamp_lookup_key: Union[str, List[str], None] = 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 toFeatureStoreClient.create_training_set()
. Thelookup_key
must be the columns in the DataFrame passed toFeatureStoreClient.create_training_set()
. The type oflookup_key
columns in that DataFrame must match the type of the primary key of the feature table referenced in thisFeatureLookup
.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 ofFeatureStoreClient.create_training_set
.timestamp_lookup_key –
Key to use when performing point-in-time lookup on this feature table with the
DataFrame
passed toFeatureStoreClient.create_training_set()
. Thetimestamp_lookup_key
must be the columns in the DataFrame passed toFeatureStoreClient.create_training_set()
. The type oftimestamp_lookup_key
columns in that DataFrame must match the type of the timestamp key of the feature table referenced in thisFeatureLookup
... note:
Experimental: This argument may change or be removed in a future release without warning.
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]. Userename_outputs
.
-
__init__
(table_name: str, lookup_key: Union[str, List[str]], *, feature_names: Union[str, List[str], None] = None, rename_outputs: Optional[Dict[str, str]] = None, timestamp_lookup_key: Union[str, List[str], None] = None, **kwargs) Initialize a FeatureLookup object.
-
property
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
.