Vector Index Status, Checkpoint, and Advisor Procedures

Review these high-level details on the GET_INDEX_STATUS, ENABLE_CHECKPOINT, DISABLE_CHECKPOINT, and INDEX_VECTOR_MEMORY_ADVISOR procedures that are available with the DBMS_VECTOR PL/SQL package.

GET_INDEX_STATUS

Purpose: To query the status of a vector index creation.

Syntax:

DBMS_VECTOR.GET_INDEX_STATUS ('USER_NAME','INDEX_NAME');

Usage Notes:

You can use the GET_INDEX_STATUS procedure only during a vector index creation.
The Percentage value is shown in the output only for Hierarchical Navigable Small World (HNSW) indexes (and not for Inverted File Flat (IVF) indexes).
Along with the DB_DEVELOPER_ROLE privilege, you must have read access to the VECSYS.VECTOR$INDEX$BUILD$ table.
You can use the following query to view all auxiliary tables:
```
select IDX_AUXILIARY_TABLES from vecsys.vector$index;
```
- For HNSW indexes:
  
  rowid_vid_map stores the mapping between a row ID and vector ID. shared_journal_change_log stores the DML changes that are yet to be incorporated into an HNSW graph.
- For IVF indexes:
  
  centroids stores the location for each centroid. centroid_partitions stores the closest centroid for each vector.

The possible values of Stage for HNSW vector indexes are:

Value	Description
`HNSW Index Initialization`	Initialization phase for the HNSW vector index creation
`HNSW Index Auxiliary Tables Creation`	Creation of the internal auxiliary tables for the HNSW Neighbor Graph vector index
`HNSW Index Graph Allocation`	Allocation of memory from the vector memory pool for the HNSW graph
`HNSW Index Loading Vectors`	Loading of the base table vectors into the vector pool memory
`HNSW Index Graph Construction`	Creation of the multi-layered HNSW graph with the previously loaded vectors
`HNSW Index Creation Completed`	HNSW vector index creation finished

The possible values of Stage for IVF vector indexes are:

Value	Description
`IVF Index Initialization`	Initialization phase for the IVF vector index creation
`IVF Index Centroids Creation`	The K-means clustering phase that computes the cluster centroids on a sample of base table vectors
`IVF Index Centroid Partitions Creation`	Centroids assignment phase for the base table vectors
`IVF Index Creation Completed`	IVF vector index creation completed

Example:

exec DBMS_VECTOR.GET_INDEX_STATUS('VECTOR_USER','VIDX_HNSW');

Index objn: 74745
Stage: HNSW Index Loading Vectors
Percentage: 80%

ENABLE_CHECKPOINT

Purpose: To enable the Checkpoint feature for a given HNSW index user and HNSW index name.

Note: This procedure only allows the index to create checkpoints. The checkpoint is created as part of the next HNSW graph refresh.

The INDEX_NAME clause is optional. If you do not specify the index name, then this procedure enables the Checkpoint feature for all HNSW indexes under the given user.

Syntax:

DBMS_VECTOR.ENABLE_CHECKPOINT('INDEX_USER',['INDEX_NAME']);

Example 1: Using index name and index user:

DBMS_VECTOR.ENABLE_CHECKPOINT('VECTOR_USER','VIDX1');

Example 2: Using index user:

DBMS_VECTOR.ENABLE_CHECKPOINT('VECTOR_USER');

Note: By default, HNSW checkpointing is enabled. You can disable it using the DBMS_VECTOR.DISABLE_CHECKPOINT procedure.

DISABLE_CHECKPOINT

Purpose: To purge all older checkpoint data. This procedure disables the Checkpoint feature for a given HNSW index user and HNSW index name. It also disables the creation of future checkpoints as part of the HNSW graph refresh.

The INDEX_NAME clause is optional. If you do not specify the index name, then this procedure disables the Checkpoint feature for all HNSW indexes under the given user.

Syntax:

DBMS_VECTOR.DISABLE_CHECKPOINT('INDEX_USER',['INDEX_NAME']);

Example 1: Using index name and index user:

DBMS_VECTOR.DISABLE_CHECKPOINT('VECTOR_USER','VIDX1');

Example 2: Using index user:

DBMS_VECTOR.DISABLE_CHECKPOINT('VECTOR_USER');

INDEX_VECTOR_MEMORY_ADVISOR

Purpose: To determine the vector memory size needed for a particular vector index. This helps you evaluate the number of indexes (HNSW or IVF) that can fit for each simulated vector memory size.

Syntax:

Using the number and type of vector dimensions that you want to store in your vector index.

DBMS_VECTOR.INDEX_VECTOR_MEMORY_ADVISOR(
    INDEX_TYPE,
    NUM_VECTORS,
    DIM_COUNT,
    DIM_TYPE,
    PARAMETER_JSON,
    RESPONSE_JSON);

Using the table and vector column on which you want to create your vector index:

DBMS_VECTOR.INDEX_VECTOR_MEMORY_ADVISOR(
    TABLE_OWNER,
    TABLE_NAME,
    COLUMN_NAME,
    INDEX_TYPE,
    PARAMETER_JSON,
    RESPONSE_JSON);

INDEX_TYPE can be one of the following:

IVF for IVF vector indexes
HNSW for HNSW vector indexes

PARAMETER_JSON can have only one of the following form:

PARAMETER_JSON=>{"accuracy":value}
INDEX_TYPE=>IVF, parameter_json=>{"neighbor_partitions":value}
INDEX_TYPE=>HNSW, parameter_json=>{"neighbors":value}

Note: You cannot specify values for accuracy along with neighbor_partitions or neighbors.

Example 1: Using neighbors in the parameters list:

exec DBMS_VECTOR.INDEX_VECTOR_MEMORY_ADVISOR(
    INDEX_TYPE=>'HNSW',
    NUM_VECTORS=>10000,
    DIM_COUNT=>768,
    DIM_TYPE=>'FLOAT32',
    PARAMETER_JSON=>'{"neighbors":128}',
    RESPONSE_JSON=>:response_json);

Suggested vector memory pool size: 59918628 Bytes

Example 2: Using accuracy in the parameters list:

exec DBMS_VECTOR.INDEX_VECTOR_MEMORY_ADVISOR(
    INDEX_TYPE=>'HNSW',
    NUM_VECTORS=>10000,
    DIM_COUNT=>768,
    DIM_TYPE=>'FLOAT32',
    PARAMETER_JSON=>'{"accuracy":90}',
    RESPONSE_JSON=>:response_json);

Suggested vector memory pool size: 53926765 Bytes

Example 3: Using the table and vector column on which you want to create the vector index:

exec DBMS_VECTOR.INDEX_VECTOR_MEMORY_ADVISOR(
    'VECTOR_USER',
    'VECTAB',
    'DATA_VECTOR',
    'HNSW',
    RESPONSE_JSON=>:response_json);

Using default accuracy: 90%
Suggested vector memory pool size: 76396251 Bytes

See Also:

DBMS_VECTOR