Stay organized with collections
Save and categorize content based on your preferences.
VECTOR_INDEXES view
The INFORMATION_SCHEMA.VECTOR_INDEXES view contains one row for each vector
index in a dataset.
Required permissions
To see vector index metadata, you need the
bigquery.tables.get or bigquery.tables.list Identity and Access Management (IAM)
permission on the table with the index. Each of the following predefined
IAM roles includes at least one of these permissions:
When you query the INFORMATION_SCHEMA.VECTOR_INDEXES view, the query results
contain one row for each vector index in a dataset.
The INFORMATION_SCHEMA.VECTOR_INDEXES view has the following schema:
Column name
Data type
Value
index_catalog
STRING
The name of the project that contains the dataset.
index_schema
STRING
The name of the dataset that contains the index.
table_name
STRING
The name of the table that the index is created on.
index_name
STRING
The name of the vector index.
index_status
STRING
The status of the index: ACTIVE, PENDING
DISABLEMENT, TEMPORARILY DISABLED, or
PERMANENTLY DISABLED.
ACTIVE means that the index is
usable or being created. Refer to the coverage_percentage
to see the progress of index creation.
PENDING DISABLEMENT means that the total
size of indexed tables exceeds your organization's
limit; the index is
queued for deletion. While in this state, the index is usable in
vector search queries and you are charged for the vector index
storage.
TEMPORARILY DISABLED means that either the total
size of indexed tables exceeds your organization's
limit, or the
indexed table is smaller than 10 MB. While in this state, the
index isn't used in vector search queries and you aren't charged
for the vector index storage.
PERMANENTLY DISABLED means that there is an
incompatible schema change on the indexed table.
creation_time
TIMESTAMP
The time the index was created.
last_modification_time
TIMESTAMP
The last time the index configuration was modified. For example,
deleting an indexed column.
last_refresh_time
TIMESTAMP
The last time the table data was indexed. A NULL value
means the index is not yet available.
disable_time
TIMESTAMP
The time the status of the index was set to DISABLED. The
value is NULL if the index status is not
DISABLED.
disable_reason
STRING
The reason the index was disabled. NULL if the index
status is not DISABLED.
DDL
STRING
The data definition language (DDL) statement used to create the
index.
coverage_percentage
INTEGER
The approximate percentage of table data that has been indexed.
0% means the index is not usable in a VECTOR_SEARCH query,
even if some data has already been indexed.
unindexed_row_count
INTEGER
The number of rows in the table that have not been indexed.
total_logical_bytes
INTEGER
The number of billable logical bytes for the index.
total_storage_bytes
INTEGER
The number of billable storage bytes for the index.
Scope and syntax
Queries against this view must have a dataset qualifier. The
following table explains the region scope for this view:
Optional: PROJECT_ID: the ID of your
Google Cloud project. If not specified, the default project is used.
DATASET_ID: the ID of your dataset. For more
information, see Dataset qualifier.
Example
-- Returns metadata for vector indexes in a single dataset.SELECT*FROMmyDataset.INFORMATION_SCHEMA.VECTOR_INDEXES;
Example
The following example shows all active vector indexes on tables in the dataset
my_dataset, located in the project my_project. It includes their names, the
DDL statements used to create them, and their coverage percentage. If an
indexed base table is less than 10 MB, then its index is not populated, in
which case the coverage_percentage value is 0.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-25 UTC."],[[["\u003cp\u003eThe \u003ccode\u003eINFORMATION_SCHEMA.VECTOR_INDEXES\u003c/code\u003e view provides metadata for each vector index within a dataset, with each row representing a unique index.\u003c/p\u003e\n"],["\u003cp\u003eAccessing vector index metadata requires \u003ccode\u003ebigquery.tables.get\u003c/code\u003e or \u003ccode\u003ebigquery.tables.list\u003c/code\u003e IAM permissions, which are included in several predefined roles such as \u003ccode\u003eroles/bigquery.admin\u003c/code\u003e and \u003ccode\u003eroles/bigquery.dataViewer\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eVECTOR_INDEXES\u003c/code\u003e schema includes details like \u003ccode\u003eindex_name\u003c/code\u003e, \u003ccode\u003eindex_status\u003c/code\u003e (\u003ccode\u003eACTIVE\u003c/code\u003e, \u003ccode\u003ePENDING DISABLEMENT\u003c/code\u003e, \u003ccode\u003eTEMPORARILY DISABLED\u003c/code\u003e, or \u003ccode\u003ePERMANENTLY DISABLED\u003c/code\u003e), \u003ccode\u003ecreation_time\u003c/code\u003e, \u003ccode\u003ecoverage_percentage\u003c/code\u003e, and the \u003ccode\u003eDDL\u003c/code\u003e statement used to create the index.\u003c/p\u003e\n"],["\u003cp\u003eQueries on this view must include a dataset qualifier and the query execution location must match the region of the \u003ccode\u003eINFORMATION_SCHEMA\u003c/code\u003e view.\u003c/p\u003e\n"],["\u003cp\u003eAn index might not be populated if the indexed base table is less than 10MB, in which case the \u003ccode\u003ecoverage_percentage\u003c/code\u003e is 0, meaning it is not usable.\u003c/p\u003e\n"]]],[],null,["# VECTOR_INDEXES view\n===================\n\nThe `INFORMATION_SCHEMA.VECTOR_INDEXES` view contains one row for each vector\nindex 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_INDEXES` view, the query results contain one row for each vector index in a dataset.\n\n\u003cbr /\u003e\n\nThe `INFORMATION_SCHEMA.VECTOR_INDEXES` 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_INDEXES;\n\nExample\n-------\n\nThe following example shows all active vector indexes on tables in the dataset\n`my_dataset`, located in the project `my_project`. It includes their names, the\nDDL statements used to create them, and their coverage percentage. If an\nindexed base table is less than 10 MB, then its index is not populated, in\nwhich case the `coverage_percentage` value is 0. \n\n```googlesql\nSELECT table_name, index_name, ddl, coverage_percentage\nFROM my_project.my_dataset.INFORMATION_SCHEMA.VECTOR_INDEXES\nWHERE index_status = 'ACTIVE';\n```\n\nThe result is similar to the following: \n\n```\n+------------+------------+-------------------------------------------------------------------------------------------------+---------------------+\n| table_name | index_name | ddl | coverage_percentage |\n+------------+------------+-------------------------------------------------------------------------------------------------+---------------------+\n| table1 | indexa | CREATE VECTOR INDEX `indexa` ON `my_project.my_dataset.table1`(embeddings) | 100 |\n| | | OPTIONS (distance_type = 'EUCLIDEAN', index_type = 'IVF', ivf_options = '{\"num_lists\": 100}') | |\n+------------+------------+-------------------------------------------------------------------------------------------------+---------------------+\n| table2 | indexb | CREATE VECTOR INDEX `indexb` ON `my_project.my_dataset.table2`(vectors) | 42 |\n| | | OPTIONS (distance_type = 'COSINE', index_type = 'IVF', ivf_options = '{\"num_lists\": 500}') | |\n+------------+------------+-------------------------------------------------------------------------------------------------+---------------------+\n| table3 | indexc | CREATE VECTOR INDEX `indexc` ON `my_project.my_dataset.table3`(vectors) | 98 |\n| | | OPTIONS (distance_type = 'DOT_PRODUCT', index_type = 'TREE_AH', | |\n| | | tree_ah_options = '{\"leaf_node_embedding_count\": 1000, \"normalization_type\": \"NONE\"}') | |\n+------------+------------+-------------------------------------------------------------------------------------------------+---------------------+\n```"]]