Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::StreamingReadFeatureValuesRequest (v1.27.0)

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

Request message for FeaturestoreOnlineServingService.StreamingReadFeatureValues.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#entity_ids

def entity_ids() -> ::Array<::String>
Returns
  • (::Array<::String>) — Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be user_123.

#entity_ids=

def entity_ids=(value) -> ::Array<::String>
Parameter
  • value (::Array<::String>) — Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be user_123.
Returns
  • (::Array<::String>) — Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be user_123.

#entity_type

def entity_type() -> ::String
Returns
  • (::String) — Required. The resource name of the entities' type. Value format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be user.

#entity_type=

def entity_type=(value) -> ::String
Parameter
  • value (::String) — Required. The resource name of the entities' type. Value format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be user.
Returns
  • (::String) — Required. The resource name of the entities' type. Value format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entityType}. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be user.

#feature_selector

def feature_selector() -> ::Google::Cloud::AIPlatform::V1::FeatureSelector
Returns

#feature_selector=

def feature_selector=(value) -> ::Google::Cloud::AIPlatform::V1::FeatureSelector
Parameter
Returns