Help Center/ Cloud Search Service/ User Guide/ Using Elasticsearch for Data Search/ Enhancing Search Capabilities for Elasticsearch Clusters/ Configuring Vector Search for Elasticsearch Clusters/ Managing the Vector Index Cache
Updated on 2024-09-14 GMT+08:00
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Managing the Vector Index Cache

The vector search engine is developed in C++ and uses off-heap memory. You can use the following APIs to manage the index cache.

  • View cache statistics. 
    GET /_vector/stats

    In the implementation of the vector plug-in, the vector index is the same as other types of Lucene indexes. Each segment constructs and stores an index file. During query, the index file is loaded to the non-heap memory. The plug-in uses the cache mechanism to manage the non-heap memory. You can use this API to query the non-heap memory usage, number of cache hits, and number of loading times.

  • Preload the vector index. 
    PUT /_vector/warmup/{index_name}

    You can use this API to preload the vector index specified by index_name to the off-heap memory for query.

  • Clear the cache. 
    PUT /_vector/clear/cache 
    PUT /_vector/clear/cache/index_name

    The caching mechanism limits the non-heap memory usage when vector indexes are used. When the total index size exceeds the cache size limit, index entry swap-in and swap-out occur, which affects the query performance. You can use this API to clear unnecessary index cache to ensure the query performance of hot data indexes.