REST Resource: projects.locations.featureGroups

Resource: FeatureGroup

Vertex AI feature Group.

Fields
name string

Identifier. name of the FeatureGroup. Format: projects/{project}/locations/{location}/featureGroups/{featureGroup}

createTime string (Timestamp format)

Output only. timestamp when this FeatureGroup was created.

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".

updateTime string (Timestamp format)

Output only. timestamp when this FeatureGroup was last updated.

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".

etag string

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

labels map (key: string, value: string)

Optional. The labels with user-defined metadata to organize your FeatureGroup.

label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

description string

Optional. description of the FeatureGroup.

serviceAgentType enum (ServiceAgentType)

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.

serviceAccountEmail string

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.

source Union type
source can be only one of the following:
bigQuery object (BigQuery)

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.

JSON representation
{
  "name": string,
  "createTime": string,
  "updateTime": string,
  "etag": string,
  "labels": {
    string: string,
    ...
  },
  "description": string,
  "serviceAgentType": enum (ServiceAgentType),
  "serviceAccountEmail": string,

  // source
  "bigQuery": {
    object (BigQuery)
  }
  // Union type
}

BigQuery

Input source type for BigQuery Tables and Views.

Fields
bigQuerySource object (BigQuerySource)

Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View.

entityIdColumns[] string

Optional. columns to construct entityId / row keys. If not provided defaults to entityId.

staticDataSource boolean

Optional. Set if the data source is not a time-series.

timeSeries object (TimeSeries)

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.

dense boolean

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 (entityId, 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.

JSON representation
{
  "bigQuerySource": {
    object (BigQuerySource)
  },
  "entityIdColumns": [
    string
  ],
  "staticDataSource": boolean,
  "timeSeries": {
    object (TimeSeries)
  },
  "dense": boolean
}

TimeSeries

Fields
timestampColumn string

Optional. column hosting timestamp values for a time-series source. Will be used to determine the latest featureValues for each entity. Optional. If not provided, column named feature_timestamp of type TIMESTAMP will be used.

JSON representation
{
  "timestampColumn": string
}

ServiceAgentType

service agent type used during jobs under a FeatureGroup.

Enums
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 serviceAccountEmail. This service account will be used to read from the source BigQuery table during jobs under a FeatureGroup.

Methods

create

Creates a new FeatureGroup in a given project and location.

delete

Deletes a single FeatureGroup.

get

Gets details of a single FeatureGroup.

getIamPolicy

Gets the access control policy for a resource.

list

Lists FeatureGroups in a given project and location.

patch

Updates the parameters of a single FeatureGroup.

setIamPolicy

Sets the access control policy on the specified resource.

testIamPermissions

Returns permissions that a caller has on the specified resource.