Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ImportFeatureValuesRequest (v0.3.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ImportFeatureValuesRequest.

Request message for FeaturestoreService.ImportFeatureValues.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#avro_source

def avro_source() -> ::Google::Cloud::AIPlatform::V1::AvroSource

#avro_source=

def avro_source=(value) -> ::Google::Cloud::AIPlatform::V1::AvroSource

#bigquery_source

def bigquery_source() -> ::Google::Cloud::AIPlatform::V1::BigQuerySource

#bigquery_source=

def bigquery_source=(value) -> ::Google::Cloud::AIPlatform::V1::BigQuerySource

#csv_source

def csv_source() -> ::Google::Cloud::AIPlatform::V1::CsvSource

#csv_source=

def csv_source=(value) -> ::Google::Cloud::AIPlatform::V1::CsvSource

#disable_ingestion_analysis

def disable_ingestion_analysis() -> ::Boolean
Returns
  • (::Boolean) — If true, API doesn't start ingestion analysis pipeline.

#disable_ingestion_analysis=

def disable_ingestion_analysis=(value) -> ::Boolean
Parameter
  • value (::Boolean) — If true, API doesn't start ingestion analysis pipeline.
Returns
  • (::Boolean) — If true, API doesn't start ingestion analysis pipeline.

#disable_online_serving

def disable_online_serving() -> ::Boolean
Returns
  • (::Boolean) — If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.

#disable_online_serving=

def disable_online_serving=(value) -> ::Boolean
Parameter
  • value (::Boolean) — If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.
Returns
  • (::Boolean) — If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving.

#entity_id_field

def entity_id_field() -> ::String
Returns
  • (::String) — Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.

#entity_id_field=

def entity_id_field=(value) -> ::String
Parameter
  • value (::String) — Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.
Returns
  • (::String) — Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.

#entity_type

def entity_type() -> ::String
Returns
  • (::String) — Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}

#entity_type=

def entity_type=(value) -> ::String
Parameter
  • value (::String) — Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}
Returns
  • (::String) — Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}

#feature_specs

def feature_specs() -> ::Array<::Google::Cloud::AIPlatform::V1::ImportFeatureValuesRequest::FeatureSpec>
Returns

#feature_specs=

def feature_specs=(value) -> ::Array<::Google::Cloud::AIPlatform::V1::ImportFeatureValuesRequest::FeatureSpec>
Parameter
Returns

#feature_time

def feature_time() -> ::Google::Protobuf::Timestamp
Returns
  • (::Google::Protobuf::Timestamp) — Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.

#feature_time=

def feature_time=(value) -> ::Google::Protobuf::Timestamp
Parameter
  • value (::Google::Protobuf::Timestamp) — Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.
Returns
  • (::Google::Protobuf::Timestamp) — Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision.

#feature_time_field

def feature_time_field() -> ::String
Returns
  • (::String) — Source column that holds the Feature timestamp for all Feature values in each entity.

#feature_time_field=

def feature_time_field=(value) -> ::String
Parameter
  • value (::String) — Source column that holds the Feature timestamp for all Feature values in each entity.
Returns
  • (::String) — Source column that holds the Feature timestamp for all Feature values in each entity.

#worker_count

def worker_count() -> ::Integer
Returns
  • (::Integer) — Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.

#worker_count=

def worker_count=(value) -> ::Integer
Parameter
  • value (::Integer) — Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.
Returns
  • (::Integer) — Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance.