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https://issues.apache.org/jira/browse/SOLR-17990?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SOLR-17990:
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Labels: pull-request-available (was: )
> FAISS integration for Solr vector search
> ----------------------------------------
>
> Key: SOLR-17990
> URL: https://issues.apache.org/jira/browse/SOLR-17990
> Project: Solr
> Issue Type: Task
> Reporter: Puneet Ahuja
> Priority: Major
> Labels: pull-request-available
> Time Spent: 10m
> Remaining Estimate: 0h
>
> This issue proposes to add integration of
> [FAISS|https://github.com/facebookresearch/faiss] (Facebook AI Similarity
> Search) into solr, as it offers different indexing strategies that can be
> better for some workloads. Lucene 11.0 (unreleased main branch) includes
> FAISS support via FaissKnnVectorsFormat, but Solr uses Lucene 10.3.1, which
> doesn't have it. Since FaissKnnVectorsFormat is only in Lucene's unreleased
> main branch (targeted for Lucene 11.0), we need to backport the FAISS-related
> code to make it available for current Solr.
> This requires backporting the FAISS codec from Lucene 11.0 to work with
> Lucene 10.3.1, creating a codec factory to integrate it, and using Java's
> Foreign Function & Memory API to call the native FAISS library. Users should
> be able to choose FAISS per field by setting knnAlgorithm="faiss" in their
> schema.xml, while keeping existing HNSW setups working. Because this
> backports unreleased Lucene code, it should go in the solr-sandbox repository
> rather than the main Solr repository, following the pattern for experimental
> or pre-release integrations.
> This would give Solr users access to FAISS capabilities and more flexibility
> for vector search, while staying compatible with current functionality.
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