Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::UpdateEntityTypeRequest (v0.11.0)

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

Request message for FeaturestoreService.UpdateEntityType.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#entity_type

def entity_type() -> ::Google::Cloud::AIPlatform::V1::EntityType
Returns
  • (::Google::Cloud::AIPlatform::V1::EntityType) — Required. The EntityType's name field is used to identify the EntityType to be updated. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}

#entity_type=

def entity_type=(value) -> ::Google::Cloud::AIPlatform::V1::EntityType
Parameter
  • value (::Google::Cloud::AIPlatform::V1::EntityType) — Required. The EntityType's name field is used to identify the EntityType to be updated. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}
Returns
  • (::Google::Cloud::AIPlatform::V1::EntityType) — Required. The EntityType's name field is used to identify the EntityType to be updated. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}

#update_mask

def update_mask() -> ::Google::Protobuf::FieldMask
Returns
  • (::Google::Protobuf::FieldMask) —

    Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

    Updatable fields:

    • description
    • labels
    • monitoring_config.snapshot_analysis.disabled
    • monitoring_config.snapshot_analysis.monitoring_interval_days
    • monitoring_config.snapshot_analysis.staleness_days
    • monitoring_config.import_features_analysis.state
    • monitoring_config.import_features_analysis.anomaly_detection_baseline
    • monitoring_config.numerical_threshold_config.value
    • monitoring_config.categorical_threshold_config.value

#update_mask=

def update_mask=(value) -> ::Google::Protobuf::FieldMask
Parameter
  • value (::Google::Protobuf::FieldMask) —

    Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

    Updatable fields:

    • description
    • labels
    • monitoring_config.snapshot_analysis.disabled
    • monitoring_config.snapshot_analysis.monitoring_interval_days
    • monitoring_config.snapshot_analysis.staleness_days
    • monitoring_config.import_features_analysis.state
    • monitoring_config.import_features_analysis.anomaly_detection_baseline
    • monitoring_config.numerical_threshold_config.value
    • monitoring_config.categorical_threshold_config.value
Returns
  • (::Google::Protobuf::FieldMask) —

    Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

    Updatable fields:

    • description
    • labels
    • monitoring_config.snapshot_analysis.disabled
    • monitoring_config.snapshot_analysis.monitoring_interval_days
    • monitoring_config.snapshot_analysis.staleness_days
    • monitoring_config.import_features_analysis.state
    • monitoring_config.import_features_analysis.anomaly_detection_baseline
    • monitoring_config.numerical_threshold_config.value
    • monitoring_config.categorical_threshold_config.value