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https://issues.apache.org/jira/browse/LUCENE-9322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17220065#comment-17220065
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Michael Sokolov commented on LUCENE-9322:
-----------------------------------------

Ooh, a fun failure - ah I see it's because we got an index with multiple 
segments, but we only expect one. I'll add a forceMerge(1) here and in a few 
other tests that have similar assumptions

> Discussing a unified vectors format API
> ---------------------------------------
>
>                 Key: LUCENE-9322
>                 URL: https://issues.apache.org/jira/browse/LUCENE-9322
>             Project: Lucene - Core
>          Issue Type: New Feature
>            Reporter: Julie Tibshirani
>            Priority: Major
>             Fix For: master (9.0)
>
>          Time Spent: 6h 10m
>  Remaining Estimate: 0h
>
> Two different approximate nearest neighbor approaches are currently being 
> developed, one based on HNSW (LUCENE-9004) and another based on coarse 
> quantization ([#LUCENE-9136]). Each prototype proposes to add a new format to 
> handle vectors. In LUCENE-9136 we discussed the possibility of a unified API 
> that could support both approaches. The two ANN strategies give different 
> trade-offs in terms of speed, memory, and complexity, and it’s likely that 
> we’ll want to support both. Vector search is also an active research area, 
> and it would be great to be able to prototype and incorporate new approaches 
> without introducing more formats.
> To me it seems like a good time to begin discussing a unified API. The 
> prototype for coarse quantization 
> ([https://github.com/apache/lucene-solr/pull/1314]) could be ready to commit 
> soon (this depends on everyone's feedback of course). The approach is simple 
> and shows solid search performance, as seen 
> [here|https://github.com/apache/lucene-solr/pull/1314#issuecomment-608645326].
>  I think this API discussion is an important step in moving that 
> implementation forward.
> The goals of the API would be
> # Support for storing and retrieving individual float vectors.
> # Support for approximate nearest neighbor search -- given a query vector, 
> return the indexed vectors that are closest to it.



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