gcp_aiplatform_feature_group

ancestors

Type: UNORDERED_LIST_STRING

big_query

Type: STRUCT
Provider name: bigQuery
Description: Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named feature_timestamp.

• big_query_source
  Type: STRUCT
  Provider name: bigQuerySource
  Description: Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View.
  
  • input_uri
    Type: STRING
    Provider name: inputUri
    Description: Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: bq://projectId.bqDatasetId.bqTableId.
    
• dense
  Type: BOOLEAN
  Provider name: dense
  Description: Optional. If set, all feature values will be fetched from a single row per unique entityId including nulls. If not set, will collapse all rows for each unique entityId into a singe row with any non-null values if present, if no non-null values are present will sync null. ex: If source has schema (entity_id, feature_timestamp, f0, f1) and the following rows: (e1, 2020-01-01T10:00:00.123Z, 10, 15) (e1, 2020-02-01T10:00:00.123Z, 20, null) If dense is set, (e1, 20, null) is synced to online stores. If dense is not set, (e1, 20, 15) is synced to online stores.
  
• entity_id_columns
  Type: UNORDERED_LIST_STRING
  Provider name: entityIdColumns
  Description: Optional. Columns to construct entity_id / row keys. If not provided defaults to entity_id.
  
• static_data_source
  Type: BOOLEAN
  Provider name: staticDataSource
  Description: Optional. Set if the data source is not a time-series.
  
• time_series
  Type: STRUCT
  Provider name: timeSeries
  Description: Optional. If the source is a time-series source, this can be set to control how downstream sources (ex: FeatureView ) will treat time-series sources. If not set, will treat the source as a time-series source with feature_timestamp as timestamp column and no scan boundary.
  
  • timestamp_column
    Type: STRING
    Provider name: timestampColumn
    Description: Optional. Column hosting timestamp values for a time-series source. Will be used to determine the latest feature_values for each entity. Optional. If not provided, column named feature_timestamp of type TIMESTAMP will be used.
    

create_time

Type: TIMESTAMP
Provider name: createTime
Description: Output only. Timestamp when this FeatureGroup was created.

description

Type: STRING
Provider name: description
Description: Optional. Description of the FeatureGroup.

etag

Type: STRING
Provider name: etag
Description: Optional. Used to perform consistent read-modify-write updates. If not set, a blind “overwrite” update happens.

labels

Type: UNORDERED_LIST_STRING

name

Type: STRING
Provider name: name
Description: Identifier. Name of the FeatureGroup. Format: projects/{project}/locations/{location}/featureGroups/{featureGroup}

organization_id

Type: STRING

parent

Type: STRING

project_id

Type: STRING

project_number

Type: STRING

resource_name

Type: STRING

service_account_email

Type: STRING
Provider name: serviceAccountEmail
Description: Output only. A Service Account unique to this FeatureGroup. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to access source data while running jobs under this FeatureGroup.

service_agent_type

Type: STRING
Provider name: serviceAgentType
Description: Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to SERVICE_AGENT_TYPE_FEATURE_GROUP. This will generate a separate service account to access the BigQuery source table.
Possible values:

• SERVICE_AGENT_TYPE_UNSPECIFIED - By default, the project-level Vertex AI Service Agent is enabled.
  
• SERVICE_AGENT_TYPE_PROJECT - Specifies the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
  
• SERVICE_AGENT_TYPE_FEATURE_GROUP - Enable a FeatureGroup service account to be created by Vertex AI and output in the field service_account_email. This service account will be used to read from the source BigQuery table during jobs under a FeatureGroup.
  

tags

Type: UNORDERED_LIST_STRING

update_time

Type: TIMESTAMP
Provider name: updateTime
Description: Output only. Timestamp when this FeatureGroup was last updated.