Update a feature view

You can update a feature view to modify the list of feature data sources associated with it. For example, you might want to make the following updates:

Associate a different feature group and features, or a different set of features from the same feature group.
Specify a different BigQuery table or view containing the feature data. Note that in this case, you also need to specify one or more entity ID columns from the updated data source.
Specify a different set of entity ID columns from the same BigQuery data source.

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

Note that you can't update a feature view that's configured for continuous data sync.

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 view based on feature group

Use the following sample to update a feature view by specifying features from an existing feature group.

REST

To update a FeatureView resource, send a PATCH request by using the featureViews.patch method.

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

LOCATION_ID: Region where the online store is located, such as us-central1.
PROJECT_ID: Your project ID.
FEATUREONLINESTORE_NAME: The name of the online store containing the feature view.
FEATUREVIEW_NAME: The name of the feature view you want to update.
FEATUREGROUP_NAME: The name of the feature group you want to associate with the feature view.
FEATURE_ID_1 and FEATURE_ID_2: Feature IDs that you want to add to the feature view from the FEATUREGROUP_NAME feature group.

HTTP method and URL:

PATCH https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME

Request JSON body:

{
  "feature_registry_source":
    { "feature_groups": [
      {
        "feature_group_id": "FEATUREGROUP_NAME",
        "feature_ids": [ "FEATURE_ID_1", "FEATURE_ID_2" ]
      }
    ]
  }
}

To send your request, choose one of these options:

curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

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/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME"

PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

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/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.UpdateFeatureViewOperationMetadata",
    "genericMetadata": {
      "createTime": "2023-09-15T04:53:22.794004Z",
      "updateTime": "2023-09-15T04:53:22.794004Z"
    }
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.FeatureView",
    "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME"
  }
}

Update a feature view based on a BigQuery source

Use the following sample to update a feature view by specifying feature columns from a BigQuery table or view.

REST

To update a FeatureView instance based on a BigQuery data source, send a PATCH request by using the featureViews.patch method.

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

LOCATION_ID: Region where the online store is located, such as us-central1.
PROJECT_ID: Your project ID.
FEATUREONLINESTORE_NAME: The name of the online store containing the feature view.
FEATUREVIEW_NAME: The name of the feature view you want to update.
BIGQUERY_SOURCE_URI: URI of the BigQuery table or view containing the feature data.
ENTITY_ID_COLUMNS:
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", ...].

HTTP method and URL:

PATCH https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME

Request JSON body:

{
  "big_query_source":
  {
    "uri": "BIGQUERY_SOURCE_URI",
    "entity_id_columns": "ENTITY_ID_COLUMNS"
  }
}

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/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_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/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.UpdateFeatureViewOperationMetadata",
    "genericMetadata": {
      "createTime": "2023-09-15T04:53:34.832192Z",
      "updateTime": "2023-09-15T04:53:34.832192Z"
    }
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1.FeatureView",
    "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureOnlineStores/FEATUREONLINESTORE_NAME/featureViews/FEATUREVIEW_NAME"
  }
}

What's next

Start online serving feature data.
Learn how to delete a feature view.