Indexing vector data and force-merging

Once you've created a GPU-accelerated vector index on your domain or collection, you can add vector data and optimize your index using standard OpenSearch operations. GPU-acceleration automatically enhances both indexing performance and force-merge operations, making it faster to build and maintain large-scale vector search applications without requiring changes to your existing workflows.

Indexing vector data

Index vector data as you normally would. The GPU-acceleration automatically applies to indexing and force-merge operations. The following example demonstrates how to add vector documents to your index using the bulk API. Each document contains a vector field with numerical values and associated text content:

POST _bulk
{"index": {"_index": "my-vector-index"}}
{"vector_field": [0.1, 0.2, 0.3, ...], "text": "Sample document 1"}
{"index": {"_index": "my-vector-index"}}
{"vector_field": [0.4, 0.5, 0.6, ...], "text": "Sample document 2"}

Force-merge operations

GPU-acceleration also applies to force-merge operations, which can significantly reduce the time required to optimize vector indexes. Note that force-merge operations aren't supported on collections. The following example demonstrates how to optimize your vector index by consolidating all segments into a single segment:

POST my-vector-index/_forcemerge?max_num_segments=1