You can retrieve a list of all the feature groups created for a specific location in your Google Cloud project, along with the URI of the BigQuery source table or view associated with each feature group.
Before you begin
Authenticate to Vertex AI, unless you've done so already.
Select the tab for how you plan to use the samples on this page:
Console
When you use the Google Cloud console to access Google Cloud services and APIs, you don't need to set up authentication.
REST
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.
List feature groups
Use the following samples to retrieve a list of all feature groups for a specific location in your project.
Console
Use the following instructions to view the list of feature groups for a specific location using the Google Cloud console.
In the Vertex AI section of the Google Cloud console, go to the Feature Store page.
In the Feature groups section, you can view the list of all the feature groups for the selected location.
REST
To retrieve a list of all the FeatureGroup
resources for a specific location in your project, send a GET
request by using the
featureGroups.list
method.
Before using any of the request data, make the following replacements:
- LOCATION_ID: Region for which you want to view the list of feature groups, such as
us-central1
. - PROJECT_ID: Your project ID.
HTTP method and URL:
GET https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups
To send your request, choose one of these options:
curl
Execute the following command:
curl -X GET \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
"https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups"
PowerShell
Execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }
Invoke-WebRequest `
-Method GET `
-Headers $headers `
-Uri "https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups" | Select-Object -Expand Content
You should receive a JSON response similar to the following:
{ "featureGroups": [ { "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME_1", "createTime": "2023-09-07T00:57:00.142639Z", "updateTime": "2023-09-07T00:57:00.142639Z", "etag": "AMEw9yOY0byP8qKsDY0DoZyouAtX23zDru2l422C0affZZPYNFOGgIrONELNrM49uH4=", "bigQuery": { "bigQuerySource": { "inputUri": "BIGQUERY_URI_1" } } }, { "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME_2", "createTime": "2023-09-06T23:14:30.795502Z", "updateTime": "2023-09-06T23:14:30.795502Z", "etag": "AMEw9yO5UfrPWobGR2Ry-PnbJUQoklW5lX0uW4JmKqj6OgQui6p-rMdUHfuENpQjbJ3t", "bigQuery": { "bigQuerySource": { "inputUri": "BIGQUERY_URI_2" } } } ] }
What's next
Learn how to create a feature.
Learn how to update a feature group.
Learn how to delete a feature group.