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https://issues.apache.org/jira/browse/LUCENE-10421?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17497920#comment-17497920
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ASF subversion and git services commented on LUCENE-10421:
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Commit 466278e14921572ceb54a0a52a8a262476ee24b7 in lucene's branch
refs/heads/main from Robert Muir
[ https://gitbox.apache.org/repos/asf?p=lucene.git;h=466278e ]
LUCENE-10421: use Constant instead of relying upon timestamp (#686)
> Non-deterministic results from KnnVectorQuery?
> ----------------------------------------------
>
> Key: LUCENE-10421
> URL: https://issues.apache.org/jira/browse/LUCENE-10421
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Michael McCandless
> Priority: Major
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> [Nightly benchmarks|https://home.apache.org/~mikemccand/lucenebench/] have
> been upset for the past ~1.5 weeks because it looks like {{KnnVectorQuery}}
> is giving slightly different results on every run, even on an identical
> (deterministically constructed – single thread indexing, flush by doc count,
> {{{}SerialMergeSchedule{}}}, {{{}LogDocCountMergePolicy{}}}, etc.) index each
> night. It produces failures like this, which then abort the benchmark to
> help us catch any recent accidental bug that alters our precise top N search
> hits and scores:
> {noformat}
> Traceback (most recent call last):
> File “/l/util.nightly/src/python/nightlyBench.py”, line 2177, in <module>
> run()
> File “/l/util.nightly/src/python/nightlyBench.py”, line 1225, in run
> raise RuntimeError(‘search result differences: %s’ % str(errors))
> RuntimeError: search result differences:
> [“query=KnnVectorQuery:vector[-0.07267512,...][10] filter=None sort=None
> groupField=None hitCount=10: hit 4 has wrong field/score value ([20844660],
> ‘0.92060816’) vs ([254438\
> 06], ‘0.920046’)“, “query=KnnVectorQuery:vector[-0.12073054,...][10]
> filter=None sort=None groupField=None hitCount=10: hit 7 has wrong
> field/score value ([25501982], ‘0.99630797’) vs ([13688085], ‘0.9961489’)“,
> “qu\
> ery=KnnVectorQuery:vector[0.02227773,...][10] filter=None sort=None
> groupField=None hitCount=10: hit 0 has wrong field/score value ([4741915],
> ‘0.9481132’) vs ([14220828], ‘0.9579846’)“, “query=KnnVectorQuery:vector\
> [0.024077624,...][10] filter=None sort=None groupField=None hitCount=10: hit
> 0 has wrong field/score value ([7472373], ‘0.8460249’) vs ([12577825],
> ‘0.8378446’)“]{noformat}
> At first I thought this might be expected because of the recent (awesome!!)
> improvements to HNSW, so I tried to simply "regold". But the regold did not
> "take", so it indeed looks like there is some non-determinism here.
> I pinged [~msoko...@gmail.com] and he found this random seeding that is most
> likely the cause?
> {noformat}
> public final class HnswGraphBuilder {
> /** Default random seed for level generation * */
> private static final long DEFAULT_RAND_SEED = System.currentTimeMillis();
> {noformat}
> Can we somehow make this deterministic instead? Or maybe the nightly
> benchmarks could somehow pass something in to make results deterministic for
> benchmarking? Or ... we could also relax the benchmarks to accept
> non-determinism for {{KnnVectorQuery}} task?
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