Update a feature group

You can update a feature group to register a BigQuery table or view as the feature data source for that feature group. If the feature group already has an associated data source, you can associate a different BigQuery table or view as the feature data source.

While creating or updating a feature group, you have the option to add user-defined metadata in the form of labels to the feature group. For more information about how to update user-defined labels for a feature group, see Update labels for a feature group.

Before you begin

Authenticate to Vertex AI, unless you've done so already.

To use the REST API samples on this page in a local development environment, you use the credentials you provide to the gcloud CLI.

    After installing the Google Cloud CLI, initialize it by running the following command: 

    gcloud init

    If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity.

For more information, see Authenticate for using REST in the Google Cloud authentication documentation.

Update a feature group

Use the following sample to update a feature group.

REST

To update a FeatureGroup resource, send a PATCH request by using the featureGroups.patch method.

Before using any of the request data, make the following replacements:

  • LOCATION_ID: Region where the feature group is located, such as us-central1.
  • PROJECT_ID: Your project ID.
  • FEATURE_GROUP_NAME: The name of the feature group that you want to update.
  • ENTITY_ID_COLUMNS: The names of the column(s) containing the entity IDs. You can specify either one column or multiple columns.
    • To specify only one entity ID column, specify the column name in the following format:
      "entity_id_column_name".
    • To specify multiple entity ID columns, specify the column names in the following format:
      ["entity_id_column_1_name", "entity_id_column_2_name", ...].
  • BIGQUERY_SOURCE_URI: URI of the BigQuery source table or view that you want to associate with the feature group.

HTTP method and URL: 

PATCH https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups?feature_group_id=FEATURE_GROUP_NAME

Request JSON body: 

{
  "big_query": {
    "entity_id_columns": "ENTITY_ID_COLUMNS",
    "big_query_source": {
      "input_uri": "BIGQUERY_SOURCE_URI"
    }
  }
}

To send your request, choose one of these options:

curl

Save the request body in a file named request.json, and execute the following command: 

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups?feature_group_id=FEATURE_GROUP_NAME"

PowerShell

Save the request body in a file named request.json, and execute the following command: 

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method PATCH `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups?feature_group_id=FEATURE_GROUP_NAME" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.UpdateFeatureGroupOperationMetadata",
    "genericMetadata": {
      "createTime": "2023-09-18T03:00:13.060636Z",
      "updateTime": "2023-09-18T03:00:13.060636Z"
    }
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.FeatureGroup",
    "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME"
  }
}

What's next