Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Dalam sebuah grup fitur, Anda dapat memperbarui fitur untuk mengaitkannya dengan kolom spesifik dalam sumber data BigQuery yang terkait dengan grup fitur tersebut.
Saat membuat atau memperbarui fitur, Anda memiliki opsi untuk menambahkan metadata yang ditentukan pengguna dalam bentuk label ke fitur tersebut. Untuk mengetahui informasi selengkapnya tentang cara memperbarui label yang ditentukan pengguna untuk fitur, lihat Memperbarui label untuk fitur.
Sebelum memulai
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Untuk menggunakan contoh REST API di halaman ini dalam lingkungan pengembangan lokal, Anda menggunakan
kredensial yang Anda berikan ke gcloud CLI.
Menginstal Google Cloud CLI.
Setelah penginstalan,
lakukan inisialisasi Google Cloud CLI dengan menjalankan perintah berikut:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-18 UTC."],[],[],null,["# Update a feature\n\nWithin a feature group, you can update a feature to associate it with a specific column\nin the BigQuery data source that's associated with the feature group.\n\nWhile creating or updating a feature, you have the option to add user-defined\nmetadata in the form of labels to the feature. For more information about how\nto update user-defined labels for a feature, see\n[Update labels for a feature](/vertex-ai/docs/featurestore/latest/feature-labels#feature).\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\nUpdate a feature\n----------------\n\nUse the following sample to update a feature within a feature group. \n\n### REST\n\n\nTo update a [`Feature`](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups.features#resource:-feature)\nresource, send a `PATCH` request by using the\n[features.patch](/vertex-ai/docs/reference/rest/v1/projects.locations.featureGroups.features/patch)\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 containing the feature 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 you want to update.\n- \u003cvar translate=\"no\"\u003eVERSION_COLUMN_NAME\u003c/var\u003e: The column from the BigQuery source table or view that you want to associate while updating the feature.\n\n\nHTTP method and URL:\n\n```\nPATCH https://LOCATION_ID-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features?feature_id=FEATURE_NAME\n```\n\n\nRequest JSON body:\n\n```\n{\n \"version_column_name\": \"VERSION_COLUMN_NAME\"\n}\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\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\ncurl -X PATCH \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n -H \"Content-Type: application/json; charset=utf-8\" \\\n -d @request.json \\\n \"https://LOCATION_ID-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features?feature_id=FEATURE_NAME\"\n```\n\n#### PowerShell\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nSave the request body in a file named `request.json`,\nand execute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method PATCH `\n -Headers $headers `\n -ContentType: \"application/json; charset=utf-8\" `\n -InFile request.json `\n -Uri \"https://LOCATION_ID-aiplatform.googleapis.com/v1beta1/projects/PROJECT_ID/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features?feature_id=FEATURE_NAME\" | Select-Object -Expand Content\n```\n\nYou should receive a JSON response similar to the following:\n\n```\n{\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features/FEATURE_NAME/operations/OPERATION_ID\",\n \"metadata\": {\n \"@type\": \"type.googleapis.com/google.cloud.aiplatform.v1beta1.UpdateFeatureOperationMetadata\",\n \"genericMetadata\": {\n \"createTime\": \"2023-09-18T02:36:22.870679Z\",\n \"updateTime\": \"2023-09-18T02:36:22.870679Z\"\n }\n },\n \"done\": true,\n \"response\": {\n \"@type\": \"type.googleapis.com/google.cloud.aiplatform.v1beta1.Feature\",\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/featureGroups/FEATURE_GROUP_NAME/features/FEATURE_NAME\"\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 [delete a feature view](/vertex-ai/docs/featurestore/latest/delete-featureview)."]]
