def sample_batch_read_feature_values(): # Create a client client = aiplatform_v1.FeaturestoreServiceClient() # Initialize request argument(s) csv_read_instances = aiplatform_v1.CsvSource() csv_read_instances.gcs_source.uris = ['uris_value_1', 'uris_value_2'] destination = aiplatform_v1.FeatureValueDestination() destination.bigquery_destination.output_uri = "output_uri_value" entity_type_specs = aiplatform_v1.EntityTypeSpec() entity_type_specs.entity_type_id = "entity_type_id_value" entity_type_specs.feature_selector.id_matcher.ids = ['ids_value_1', 'ids_value_2'] request = aiplatform_v1.BatchReadFeatureValuesRequest( csv_read_instances=csv_read_instances, featurestore="featurestore_value", destination=destination, entity_type_specs=entity_type_specs, ) # Make the request operation = client.batch_read_feature_values(request=request) print("Waiting for operation to complete...") response = operation.result() # Handle the response print(response)
async def sample_export_feature_values(): # Create a client client = aiplatform_v1.FeaturestoreServiceAsyncClient() # Initialize request argument(s) destination = aiplatform_v1.FeatureValueDestination() destination.bigquery_destination.output_uri = "output_uri_value" feature_selector = aiplatform_v1.FeatureSelector() feature_selector.id_matcher.ids = ['ids_value_1', 'ids_value_2'] request = aiplatform_v1.ExportFeatureValuesRequest( entity_type="entity_type_value", destination=destination, feature_selector=feature_selector, ) # Make the request operation = client.export_feature_values(request=request) print("Waiting for operation to complete...") response = await operation.result() # Handle the response print(response)