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.

    Install the Google Cloud CLI, then initialize it by running the following command: 

    gcloud init

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