Apache Solr 10: What’s Coming up for Vector Search
Session Abstract
With Apache Solr 10 out, there are plenty of goodies coming up for vector-search aficionados.
From scalar and binary quantization to speed up your search and reduce the memory footprint, to early termination and hybrid approaches to navigate the HNSW graph.
Join us if you want to learn about the big steps forward of Apache Solr vector search!
Session Description
Apache Solr 10 introduces many advancements in the realm of vector search, making many interesting Lucene features surface.
Starting from scalar and binary quantization, this feature helps users in reducing both the query time and memory footprint at the cost of some accuracy and disk space: a welcome trade-off for those using Solr on massive amounts of vectors.
Early termination introduces the ability of speeding up certain queries that saturate a configurable threshold, and Seeded KNN gives the ability to start the HNSW graph exploration from a lexical result set, rather than random entry documents (core mechanism of the Solr vector search implementation).
ACORN filtering improves the way pre-filtering happens when you mix traditional keyword searches with knn queries, and the query combiner finally offers a comprehensive strategy to mix up query results, opening the door to a more flexible hybrid search.
To conclude with a cherry on top of the cake, we’ll go through many bug fixes and minor improvements, still worth mentioning.
The audience is expected to get an overview of all the new interesting vector search features coming with Solr 10 and learn how to use them and benefit from them in their use cases.
