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Julie Tibshirani commented on LUCENE-10404: ------------------------------------------- Checking I understand the numbers: in addition to indexing slowing down, it looks like search latency is a bit worse too. The main difference is that the graph is better connected (higher maxConn) and we explore more nodes during index (beamWidth). The slowdown is not huge but significant (~5% slower for both index + search). This would support the theory that for larger numbers of 'visited' nodes, the IntIntHashMap solution doesn't perform as well. Maybe we could consider a more custom approach as Adrien suggests ? > Use hash set for visited nodes in HNSW search? > ---------------------------------------------- > > Key: LUCENE-10404 > URL: https://issues.apache.org/jira/browse/LUCENE-10404 > Project: Lucene - Core > Issue Type: Improvement > Reporter: Julie Tibshirani > Priority: Minor > > While searching each layer, HNSW tracks the nodes it has already visited > using a BitSet. We could look into using something like IntHashSet instead. I > tried out the idea quickly by switching to IntIntHashMap (which has already > been copied from hppc) and saw an improvement in index performance. > *Baseline:* 760896 msec to write vectors > *Using IntIntHashMap:* 733017 msec to write vectors > I noticed search performance actually got a little bit worse with the change > -- that is something to look into. > For background, it's good to be aware that HNSW can visit a lot of nodes. For > example, on the glove-100-angular dataset with ~1.2 million docs, HNSW search > visits ~1000 - 15,000 docs depending on the recall. This number can increase > when searching with deleted docs, especially if you hit a "pathological" case > where the deleted docs happen to be closest to the query vector. -- This message was sent by Atlassian Jira (v8.20.10#820010) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org