This page lists the Cloud SQL information schema table additions.

## information_schema.innodb_vector_indexes

Gives all the vector indexes that are opened in the memory after restart.

|---|---|
| Column name | Description |
| INDEX_NAME | Name of the index |
| TABLE_NAME | Qualified table name in db_name.table_name format |
| INDEX_TYPE | TREE_SQ is supported |
| DIMENSION | Dimensionality of the vector column |
| DIST_MEASURE | Distance Measure on which index is built |
| STATUS | A string describing the current state of the index |
| STATE | Internal state of the index |
| NUM_LEAVES | Number of leaves as configured by the user or computed internally based on the size of the base table |
| NUM_LEAVES_TO_SEARCH | Number of leaves to search in ANN. Can be overridden at query time |
| QUERIES | Number of ANN queries on this index since server start |
| MUTATIONS | Number of DML operations on base table that resulted in updating the vector index |
| TREE_MEMORY | Memory occupied by the non-leaf part of the vector index |

## information_schema.innodb_all_vector_indexes

Contains all the vector indexes that exists on the instance (even if they are
not opened in the memory yet).

|---|---|
| Column name | Description |
| id | same as innodb_indexes.index_id |
| table_id | An identifier representing the table associated with the index |
| sub_table_id | An identifier representing the sub table associated with the vector index |
| state | Internal state of the index. Same as `information_schema.innodb_vector_indexes` |
| corrupted | Indicates whether the index is corrupted or not. `1` means corrupted, `0` means not corrupted. |
| config | A json value showing index configuration. In configuration: - "D" implies it is a static default value of this parameter. - "G" implies that the value is generated or computed internally. - "C" means that the value is explicitly specified by the user. The order of precedence is C \> G \> D. |

## information_schema.innodb_vector_indexes_memory

Provides information about overall memory usage of vector indexes in the
instance.

|---|---|
| Column name | Description |
| STATE | Memory management for vector indexes is enabled. |
| TOTAL_MEMORY | cloudsql_vector_max_mem_size |
| INDEX_MEMORY | Amount of memory that is used to load `index_tree` into the memory. |
| TRAINING_MEMORY | Amount of memory that is allocated for training during index build. |
| LOADED_INDEX | Number of indexes that are loaded in the memory. |

## What's next

- Read the [overview about vector search on Cloud SQL](https://docs.cloud.google.com/sql/docs/mysql/vector-search.md.txt).
- Learn how to [enable and disable vector embeddings on your instance](https://docs.cloud.google.com/sql/docs/mysql/enable-vector-search.md.txt).
- Learn how to [generate vector embeddings](https://docs.cloud.google.com/sql/docs/mysql/generate-manage-vector-embeddings.md.txt#generate_vector_embeddings_based_on_row_data).
- Learn how to [create vector indexes](https://docs.cloud.google.com/sql/docs/mysql/create-manage-vector-indexes.md.txt).
- Learn how to [perform searches on vector embeddings](https://docs.cloud.google.com/sql/docs/mysql/search-filter-vector-embeddings.md.txt).