``w.feature_engineering``: Feature Engineering ============================================== .. currentmodule:: databricks.sdk.service.ml .. py:class:: FeatureEngineeringAPI [description] .. py:method:: batch_create_materialized_features(requests: List[CreateMaterializedFeatureRequest]) -> BatchCreateMaterializedFeaturesResponse Batch create materialized features. :param requests: List[:class:`CreateMaterializedFeatureRequest`] The requests to create materialized features. :returns: :class:`BatchCreateMaterializedFeaturesResponse` .. py:method:: create_feature(feature: Feature) -> Feature Create a Feature. :param feature: :class:`Feature` Feature to create. :returns: :class:`Feature` .. py:method:: create_kafka_config(kafka_config: KafkaConfig) -> KafkaConfig Create a Kafka config. During PrPr, Kafka configs can be read and used when creating features under the entire metastore. Only the creator of the Kafka config can delete it. :param kafka_config: :class:`KafkaConfig` :returns: :class:`KafkaConfig` .. py:method:: create_materialized_feature(materialized_feature: MaterializedFeature) -> MaterializedFeature Create a materialized feature. :param materialized_feature: :class:`MaterializedFeature` The materialized feature to create. :returns: :class:`MaterializedFeature` .. py:method:: create_stream(stream: Stream) -> Stream Create a Stream, a governed UC entity representing an external streaming data source. :param stream: :class:`Stream` The Stream to create. :returns: :class:`Stream` .. py:method:: delete_feature(full_name: str) Delete a Feature. :param full_name: str Name of the feature to delete. .. py:method:: delete_kafka_config(name: str) Delete a Kafka config. During PrPr, Kafka configs can be read and used when creating features under the entire metastore. Only the creator of the Kafka config can delete it. :param name: str Name of the Kafka config to delete. .. py:method:: delete_materialized_feature(materialized_feature_id: str) Delete a materialized feature. :param materialized_feature_id: str The ID of the materialized feature to delete. .. py:method:: delete_stream(name: str) Delete a Stream by its full three-part name (catalog.schema.stream). :param name: str Full three-part name (catalog.schema.stream) of the Stream to delete. .. py:method:: get_feature(full_name: str) -> Feature Get a Feature. :param full_name: str Name of the feature to get. :returns: :class:`Feature` .. py:method:: get_kafka_config(name: str) -> KafkaConfig Get a Kafka config. During PrPr, Kafka configs can be read and used when creating features under the entire metastore. Only the creator of the Kafka config can delete it. :param name: str Name of the Kafka config to get. :returns: :class:`KafkaConfig` .. py:method:: get_materialized_feature(materialized_feature_id: str) -> MaterializedFeature Get a materialized feature. :param materialized_feature_id: str The ID of the materialized feature. :returns: :class:`MaterializedFeature` .. py:method:: get_stream(name: str) -> Stream Get a Stream by its full three-part name (catalog.schema.stream). :param name: str Full three-part name (catalog.schema.stream) of the Stream to get. :returns: :class:`Stream` .. py:method:: list_features(catalog_name: str, schema_name: str [, page_size: Optional[int], page_token: Optional[str]]) -> Iterator[Feature] List Features. :param catalog_name: str Name of parent catalog for features of interest. :param schema_name: str Name of parent schema relative to its parent catalog. :param page_size: int (optional) The maximum number of results to return. :param page_token: str (optional) Pagination token to go to the next page based on a previous query. :returns: Iterator over :class:`Feature` .. py:method:: list_kafka_configs( [, page_size: Optional[int], page_token: Optional[str]]) -> Iterator[KafkaConfig] List Kafka configs. During PrPr, Kafka configs can be read and used when creating features under the entire metastore. Only the creator of the Kafka config can delete it. :param page_size: int (optional) The maximum number of results to return. :param page_token: str (optional) Pagination token to go to the next page based on a previous query. :returns: Iterator over :class:`KafkaConfig` .. py:method:: list_materialized_features( [, feature_name: Optional[str], page_size: Optional[int], page_token: Optional[str]]) -> Iterator[MaterializedFeature] List materialized features. :param feature_name: str (optional) Filter by feature name. If specified, only materialized features materialized from this feature will be returned. :param page_size: int (optional) The maximum number of results to return. Defaults to 100 if not specified. Cannot be greater than 1000. :param page_token: str (optional) Pagination token to go to the next page based on a previous query. :returns: Iterator over :class:`MaterializedFeature` .. py:method:: list_streams( [, page_size: Optional[int], page_token: Optional[str], parent: Optional[str]]) -> Iterator[Stream] List Streams under a given catalog.schema parent. :param page_size: int (optional) The maximum number of results to return. :param page_token: str (optional) Pagination token to go to the next page based on a previous query. :param parent: str (optional) Two-part name (catalog.schema) of the parent under which to list Streams. :returns: Iterator over :class:`Stream` .. py:method:: update_feature(full_name: str, feature: Feature, update_mask: str) -> Feature Update a Feature. :param full_name: str The full three-part name (catalog, schema, name) of the feature. This is the feature's resource identifier; the catalog_name, schema_name, and name fields below are OUTPUT_ONLY decomposed views of this value. :param feature: :class:`Feature` Feature to update. :param update_mask: str The list of fields to update. :returns: :class:`Feature` .. py:method:: update_kafka_config(name: str, kafka_config: KafkaConfig, update_mask: FieldMask) -> KafkaConfig Update a Kafka config. During PrPr, Kafka configs can be read and used when creating features under the entire metastore. Only the creator of the Kafka config can delete it. :param name: str Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name. :param kafka_config: :class:`KafkaConfig` The Kafka config to update. :param update_mask: FieldMask The list of fields to update. :returns: :class:`KafkaConfig` .. py:method:: update_materialized_feature(materialized_feature_id: str, materialized_feature: MaterializedFeature, update_mask: str) -> MaterializedFeature Update a materialized feature (pause/resume). :param materialized_feature_id: str Server-assigned unique identifier for the materialized feature. :param materialized_feature: :class:`MaterializedFeature` The materialized feature to update. :param update_mask: str Provide the materialization feature fields which should be updated. Currently, only the pipeline_state field can be updated. :returns: :class:`MaterializedFeature` .. py:method:: update_stream(name: str, stream: Stream, update_mask: FieldMask) -> Stream Update a Stream. Only fields listed in `update_mask` are mutated. :param name: str Full three-part (catalog.schema.stream) name of the stream. :param stream: :class:`Stream` The Stream to update. :param update_mask: FieldMask The list of fields to update. :returns: :class:`Stream`