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https://issues.apache.org/jira/browse/LUCENE-10624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17558700#comment-17558700
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Greg Miller commented on LUCENE-10624:
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For what it's worth, I ran a benchmark on the Amazon Product Search engine with
this change, where we do lots of doc value access for various purposes, and saw
effectively no change to latency or throughput (qps). Just adding that as a
datapoint from a real-world, large-scale application.
> Binary Search for Sparse IndexedDISI advanceWithinBlock &
> advanceExactWithinBlock
> ---------------------------------------------------------------------------------
>
> Key: LUCENE-10624
> URL: https://issues.apache.org/jira/browse/LUCENE-10624
> Project: Lucene - Core
> Issue Type: Improvement
> Components: core/codecs
> Affects Versions: 9.0, 9.1, 9.2
> Reporter: Weiming Wu
> Priority: Major
> Attachments: baseline_sparseTaxis_searchsparse-sorted.0.log,
> candiate-exponential-searchsparse-sorted.0.log,
> candidate_sparseTaxis_searchsparse-sorted.0.log
>
> Time Spent: 40m
> Remaining Estimate: 0h
>
> h3. Problem Statement
> We noticed DocValue read performance regression with the iterative API when
> upgrading from Lucene 5 to Lucene 9. Our latency is increased by 50%. The
> degradation is similar to what's described in
> https://issues.apache.org/jira/browse/SOLR-9599
> By analyzing profiling data, we found method "advanceWithinBlock" and
> "advanceExactWithinBlock" for Sparse IndexedDISI is slow in Lucene 9 due to
> their O(N) doc lookup algorithm.
> h3. Changes
> Used binary search algorithm to replace current O(N) lookup algorithm in
> Sparse IndexedDISI "advanceWithinBlock" and "advanceExactWithinBlock" because
> docs are in ascending order.
> h3. Test
> {code:java}
> ./gradlew tidy
> ./gradlew check {code}
> h3. Benchmark
> Ran sparseTaxis test cases from {color:#1d1c1d}luceneutil. Attached the
> reports of baseline and candidates in attachments section.{color}
> {color:#1d1c1d}1. Most cases have 5-10% search latency reduction.{color}
> {color:#1d1c1d}2. Some highlights (>20%):{color}
> * *{color:#1d1c1d}T0 green_pickup_latitude:[40.75 TO 40.9]
> yellow_pickup_latitude:[40.75 TO 40.9] sort=null{color}*
> ** {color:#1d1c1d}*Baseline:* 10973978+ hits hits in *726.81967 msec*{color}
> ** {color:#1d1c1d}*Candidate:* 10973978+ hits hits in *484.544594
> msec*{color}
> * *{color:#1d1c1d}T0 cab_color:y cab_color:g sort=null{color}*
> ** {color:#1d1c1d}*Baseline:* 2300174+ hits hits in *95.698324 msec*{color}
> ** {color:#1d1c1d}*Candidate:* 2300174+ hits hits in *78.336193 msec*{color}
> * {color:#1d1c1d}*T1 cab_color:y cab_color:g sort=null*{color}
> ** {color:#1d1c1d}*Baseline:* 2300174+ hits hits in *391.565239 msec*{color}
> ** {color:#1d1c1d}*Candidate:* 300174+ hits hits in *227.592885
> msec*{color}{*}{*}
> * {color:#1d1c1d}*...*{color}
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