Resource: FeatureGroup
Vertex AI feature Group.
name
string
Identifier. name of the FeatureGroup. Format: projects/{project}/locations/{location}/featureGroups/{featureGroup}
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"
.
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.
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: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 |
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{ "name": string, "createTime": string, "updateTime": string, "etag": string, "labels": { string: string, ... }, "description": string, "serviceAgentType": enum ( |
BigQuery
Input source type for BigQuery Tables and Views.
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.
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 ( |
TimeSeries
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 |
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{ "timestampColumn": string } |
ServiceAgentType
service agent type used during jobs under a FeatureGroup.
Enums | |
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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 |
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Creates a new FeatureGroup in a given project and location. |
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Deletes a single FeatureGroup. |
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Gets details of a single FeatureGroup. |
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Gets the access control policy for a resource. |
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Lists FeatureGroups in a given project and location. |
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Updates the parameters of a single FeatureGroup. |
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Sets the access control policy on the specified resource. |
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Returns permissions that a caller has on the specified resource. |