Struct googapis::google::cloud::aiplatform::v1::ImportFeatureValuesRequest[][src]

pub struct ImportFeatureValuesRequest {
    pub entity_type: String,
    pub entity_id_field: String,
    pub feature_specs: Vec<FeatureSpec>,
    pub disable_online_serving: bool,
    pub worker_count: i32,
    pub source: Option<Source>,
    pub feature_time_source: Option<FeatureTimeSource>,
}
Expand description

Request message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ImportFeatureValues].

Fields

entity_type: 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_id_field: String

Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id.

feature_specs: Vec<FeatureSpec>

Required. Specifications defining which Feature values to import from the entity. The request fails if no feature_specs are provided, and having multiple feature_specs for one Feature is not allowed.

disable_online_serving: bool

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.

worker_count: i32

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.

source: Option<Source>

Details about the source data, including the location of the storage and the format.

feature_time_source: Option<FeatureTimeSource>

Source of Feature timestamp for all Feature values of each entity. Timestamps must be millisecond-aligned.

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