[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-09-04。"],[[["\u003cp\u003eThe \u003ccode\u003eINFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS\u003c/code\u003e view provides metadata about each vector-indexed column within a dataset, with one row per indexed column.\u003c/p\u003e\n"],["\u003cp\u003eAccessing vector index metadata requires specific IAM permissions, such as \u003ccode\u003ebigquery.tables.get\u003c/code\u003e or \u003ccode\u003ebigquery.tables.list\u003c/code\u003e, which are included in roles like \u003ccode\u003eroles/bigquery.admin\u003c/code\u003e, \u003ccode\u003eroles/bigquery.dataViewer\u003c/code\u003e, and others.\u003c/p\u003e\n"],["\u003cp\u003eQuery results from this view include details like \u003ccode\u003eindex_catalog\u003c/code\u003e, \u003ccode\u003eindex_schema\u003c/code\u003e, \u003ccode\u003etable_name\u003c/code\u003e, \u003ccode\u003eindex_name\u003c/code\u003e, \u003ccode\u003eindex_column_name\u003c/code\u003e, and \u003ccode\u003eindex_field_path\u003c/code\u003e, providing comprehensive information about the indexed columns.\u003c/p\u003e\n"],["\u003cp\u003eQueries against the \u003ccode\u003eVECTOR_INDEX_COLUMNS\u003c/code\u003e view must specify a dataset qualifier and must be executed within the same region as the \u003ccode\u003eINFORMATION_SCHEMA\u003c/code\u003e view.\u003c/p\u003e\n"],["\u003cp\u003eThe view is queried at a dataset level, with the syntax including optional \u003ccode\u003ePROJECT_ID\u003c/code\u003e and a required \u003ccode\u003eDATASET_ID\u003c/code\u003e, and can provide insights into indexed columns across multiple tables like in the example.\u003c/p\u003e\n"]]],[],null,["# VECTOR_INDEX_COLUMNS view\n=========================\n\nThe `INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS` view contains one row for each\nvector-indexed column on each table in a dataset.\n\nRequired permissions\n--------------------\n\nTo see [vector index](/bigquery/docs/vector-index) metadata, you need the\n`bigquery.tables.get` or `bigquery.tables.list` Identity and Access Management (IAM)\npermission on the table with the index. Each of the following predefined\nIAM roles includes at least one of these permissions:\n\n- `roles/bigquery.admin`\n- `roles/bigquery.dataEditor`\n- `roles/bigquery.dataOwner`\n- `roles/bigquery.dataViewer`\n- `roles/bigquery.metadataViewer`\n- `roles/bigquery.user`\n\nFor more information about BigQuery permissions, see\n[Access control with IAM](/bigquery/docs/access-control).\n\nSchema\n------\n\nWhen you query the `INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS` view, the query results contain one row for each indexed column on each table in a dataset.\n\n\u003cbr /\u003e\n\nThe `INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS` view has the following schema:\n\nScope and syntax\n----------------\n\nQueries against this view must have a [dataset qualifier](/bigquery/docs/information-schema-intro#syntax). The\nfollowing table explains the region scope for this view:\n\n\u003cbr /\u003e\n\nReplace the following:\n\n- Optional: \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: the ID of your Google Cloud project. If not specified, the default project is used.\n- \u003cvar translate=\"no\"\u003eDATASET_ID\u003c/var\u003e: the ID of your dataset. For more information, see [Dataset qualifier](/bigquery/docs/information-schema-intro#dataset_qualifier).\n\n \u003cbr /\u003e\n\n \u003cbr /\u003e\n\n | **Note:** You must use [a region qualifier](/bigquery/docs/information-schema-intro#region_qualifier) to query `INFORMATION_SCHEMA` views. The location of the query execution must match the region of the `INFORMATION_SCHEMA` view.\n\n\u003cbr /\u003e\n\n**Example** \n\n -- Returns metadata for vector indexes in a single dataset.\n SELECT * FROM myDataset.INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS;\n\nExamples\n--------\n\nThe following query extracts information on columns that have vector indexes: \n\n```googlesql\nSELECT table_name, index_name, index_column_name, index_field_path\nFROM my_project.dataset.INFORMATION_SCHEMA.VECTOR_INDEX_COLUMNS;\n```\n\nThe result is similar to the following: \n\n```\n+------------+------------+-------------------+------------------+\n| table_name | index_name | index_column_name | index_field_path |\n+------------+------------+-------------------+------------------+\n| table1 | indexa | embeddings | embeddings |\n| table2 | indexb | vectors | vectors |\n| table3 | indexc | vectors | vectors |\n+------------+------------+-------------------+------------------+\n```"]]