특성 그룹에서 특정 특성을 삭제할 수 있습니다. 특성을 삭제하면 특성 레지스트리에서 특성 열이 등록 취소되고 등록된 BigQuery 소스 테이블 또는 뷰의 열에 있는 데이터에는 영향을 주지 않습니다. 필요한 경우 특성 그룹에 다른 특성을 만들어 동일한 열을 다시 등록할 수 있습니다.
시작하기 전에
아직 인증하지 않은 경우 Vertex AI에 인증합니다.
로컬 개발 환경에서 이 페이지의 REST API 샘플을 사용하려면 gcloud CLI에 제공한 사용자 인증 정보를 사용합니다.
Install the Google Cloud CLI.
After installation,
initialize the Google Cloud CLI by running the following command:
[[["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: 2025-09-04(UTC)"],[],[],null,["# Delete a feature\n\nYou can delete specific features from a feature group. Deleting a feature\nunregisters the feature column from the Feature Registry and\ndoesn't affect the data in the column in the registered BigQuery\nsource table or view. You can [create another feature](/vertex-ai/docs/featurestore/latest/create-feature) in any\nfeature group to register the same column again, if necessary.\n\nBefore you begin\n----------------\n\n\nto\nVertex AI, unless you've done so already.\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\nDelete a feature\n----------------\n\nUse the following sample to delete a feature from a feature group. \n\n### REST\n\n\nTo delete a [`Feature`](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups.features#resource:-feature) resource, send a `DELETE` request by using the\n[features.delete](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups.features/delete)\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 where the feature group is located, such as `us-central1`.\n- \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: Your project ID.\n- \u003cvar translate=\"no\"\u003eFEATURE_GROUP_NAME\u003c/var\u003e: The name of the feature group containing the feature.\n- \u003cvar translate=\"no\"\u003eFEATURE_NAME\u003c/var\u003e: The name of the feature that you want to delete.\n\n\nHTTP method and URL:\n\n```\nDELETE https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features/FEATURE_NAME\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 DELETE \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n \"https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features/FEATURE_NAME\"\n```\n\n#### PowerShell\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nExecute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method DELETE `\n -Headers $headers `\n -Uri \"https://LOCATION_ID-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features/FEATURE_NAME\" | Select-Object -Expand Content\n```\n\nYou should receive a JSON response similar to the following:\n\n```\n\"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/operations/OPERATION_ID\",\n \"metadata\": {\n \"@type\": \"type.googleapis.com/google.cloud.aiplatform.v1.DeleteOperationMetadata\",\n \"genericMetadata\": {\n \"createTime\": \"2023-09-25T18:52:42.092928Z\",\n \"updateTime\": \"2023-09-25T18:52:42.092928Z\"\n }\n },\n \"done\": true,\n \"response\": {\n \"@type\": \"type.googleapis.com/google.protobuf.Empty\"\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](/vertex-ai/docs/featurestore/latest/update-feature).\n\n- Learn how to [delete a feature group along with its features](/vertex-ai/docs/featurestore/latest/delete-featuregroup)."]]
