Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
Puoi eliminare caratteristiche specifiche da un gruppo di caratteristiche. L'eliminazione di una caratteristica
annulla la registrazione della colonna delle caratteristiche dal registro delle caratteristiche e
non influisce sui dati nella colonna della tabella o della vista di origine BigQuery registrata. Se necessario, puoi creare un'altra funzionalità in qualsiasi
gruppo di funzionalità per registrare di nuovo la stessa colonna.
Prima di iniziare
Autenticati su
Vertex AI, a meno che tu non l'abbia già fatto.
Per utilizzare gli esempi di API REST in questa pagina in un ambiente di sviluppo locale, utilizza le
credenziali che fornisci a gcloud CLI.
Installa Google Cloud CLI.
Dopo l'installazione,
inizializza Google Cloud CLI eseguendo il seguente comando:
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 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)."]]