다음과 비슷한 JSON 응답이 수신됩니다.
BIGQUERY_URI_1은 FEATURE_GROUP_NAME_1을 통해 등록된 BigQuery 소스 테이블 또는 뷰이고 BIGQUERY_URI_2는 FEATURE_GROUP_NAME_2에 등록된 BigQuery 소스 테이블 또는 뷰입니다. 응답에 나열된 기능 그룹에 전용 서비스 계정 구성이 있는 경우 세부정보에 서비스 계정 이메일 주소도 표시됩니다. 이 예에서 SERVICE_ACCOUNT_EMAIL은 기능 그룹 FEATURE_GROUP_NAME_1과 연결된 서비스 계정 이메일 주소입니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-07-08(UTC)"],[],[],null,["# List feature groups\n\nYou can retrieve a list of all the feature groups created for a specific\nlocation in your Google Cloud project, along with the URI of the\nBigQuery source table or view associated with each feature group.\n\nIf a feature group is configured to use a dedicated service account, then the\ndetails for that feature group also include the associated service account email\naddress. For more information about creating feature groups with dedicated\nservice account configurations, see\n[Configure the service account for a feature group](/vertex-ai/docs/featurestore/latest/create-featuregroup#serviceaccount).\n\nBefore you begin\n----------------\n\n\nto\nVertex AI, unless you've done so already.\n\nSelect the tab for how you plan to use the samples on this page: \n\n### Console\n\n\nWhen you use the Google Cloud console to access Google Cloud services and\nAPIs, you don't need to set up authentication.\n\n### REST\n\n\nTo use the REST API samples on this page in a local development environment, you use the\ncredentials you provide to the gcloud CLI.\n\n1. [Install](/sdk/docs/install) the Google Cloud CLI. After installation, [initialize](/sdk/docs/initializing) the Google Cloud CLI by running the following command: \n\n```bash\ngcloud init\n```\n2. If you're using an external identity provider (IdP), you must first [sign in to the gcloud CLI with your federated identity](/iam/docs/workforce-log-in-gcloud).\n\n\nFor more information, see\n[Authenticate for using REST](/docs/authentication/rest)\nin the Google Cloud authentication documentation.\n\nList feature groups\n-------------------\n\nUse the following samples to retrieve a list of all feature groups for a specific\nlocation in your project. \n\n### Console\n\nUse the following instructions to view the list of feature groups for a specific location using the Google Cloud console.\n\n1. In the Vertex AI section of the Google Cloud console, go\n to the **Feature Store** page.\n\n [Go to the Feature Store page](https://console.cloud.google.com/vertex-ai/feature-store)\n2. In the **Feature groups** section, you can view the list of all the feature groups for the selected location.\n\n### REST\n\n\nTo retrieve a list of all the [`FeatureGroup`](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups#resource:-featuregroup)\nresources for a specific location in your project, send a `GET` request by using the\n[featureGroups.list](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups/list)\nmethod.\n\n\nBefore using any of the request data,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003eLOCATION_ID\u003c/var\u003e: Region for which you want to view the list of feature groups, such as `us-central1`.\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n\n\nHTTP method and URL:\n\n```\nGET https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups\n```\n\nTo send your request, choose one of these options: \n\n#### curl\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nExecute the following command:\n\n```\ncurl -X GET \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n \"https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups\"\n```\n\n#### PowerShell\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nExecute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method GET `\n -Headers $headers `\n -Uri \"https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups\" | Select-Object -Expand Content\n```\nYou should receive a JSON response similar to the following. \u003cvar translate=\"no\"\u003eBIGQUERY_URI_1\u003c/var\u003e is the BigQuery source table or view registered via \u003cvar translate=\"no\"\u003eFEATURE_GROUP_NAME_1\u003c/var\u003e and \u003cvar translate=\"no\"\u003eBIGQUERY_URI_2\u003c/var\u003e is the BigQuery source table or view registered with \u003cvar translate=\"no\"\u003eFEATURE_GROUP_NAME_2\u003c/var\u003e. \nIf any of the feature groups listed in the response has a dedicated service account configuration, then the service account email address is also listed in its details. In this example, \u003cvar translate=\"no\"\u003eSERVICE_ACCOUNT_EMAIL\u003c/var\u003e is the service account email address associated with the feature group \u003cvar translate=\"no\"\u003eFEATURE_GROUP_NAME_1\u003c/var\u003e.\n\n```\n{\n \"featureGroups\": [\n {\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME_1\",\n \"createTime\": \"2023-09-07T00:57:00.142639Z\",\n \"updateTime\": \"2023-09-07T00:57:00.142639Z\",\n \"etag\": \"AMEw9yOY0byP8qKsDY0DoZyouAtX23zDru2l422C0affZZPYNFOGgIrONELNrM49uH4=\",\n \"bigQuery\": {\n \"bigQuerySource\": {\n \"inputUri\": \"BIGQUERY_URI_1\"\n }\n }\n \"serviceAccountEmail\": \"SERVICE_ACCOUNT_EMAIL\"\n },\n {\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME_2\",\n \"createTime\": \"2023-09-06T23:14:30.795502Z\",\n \"updateTime\": \"2023-09-06T23:14:30.795502Z\",\n \"etag\": \"AMEw9yO5UfrPWobGR2Ry-PnbJUQoklW5lX0uW4JmKqj6OgQui6p-rMdUHfuENpQjbJ3t\",\n \"bigQuery\": {\n \"bigQuerySource\": {\n \"inputUri\": \"BIGQUERY_URI_2\"\n }\n }\n }\n ]\n}\n```\n\n\u003cbr /\u003e\n\nWhat's next\n-----------\n\n- Learn how to [create a feature](/vertex-ai/docs/featurestore/latest/create-feature).\n\n- Learn how to [update a feature group](/vertex-ai/docs/featurestore/latest/update-featuregroup).\n\n- Learn how to [delete a feature group](/vertex-ai/docs/featurestore/latest/delete-featuregroup)."]]
