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https://issues.apache.org/jira/browse/LUCENE-10233?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17445143#comment-17445143
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Feng Guo edited comment on LUCENE-10233 at 11/17/21, 2:08 PM:
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[~jpountz] I execute a low cardinality terms query on baseline/ docbase /
SparseFixedBitSet:
Origin: 158ms
Docbase: 6ms
SparseFixedBitSet: 71ms
And this is the script:
[https://github.com/apache/lucene/blob/2586014ca8575d55ae25fa4b35d8df6d2f8f40f2/lucene/core/src/java/org/apache/lucene/util/bkd/Run.java]
I hope there can be some more optimization for SparseFixedBitSet so that it can
perform better.
was (Author: gf2121):
[~jpountz] I execute a low cardinality terms query on origin code/ initial
implement / SparseFixedBitSet:
Origin: 158ms
Initial implement: 6ms
SparseFixedBitSet: 71ms
And this is the script:
[https://github.com/apache/lucene/blob/2586014ca8575d55ae25fa4b35d8df6d2f8f40f2/lucene/core/src/java/org/apache/lucene/util/bkd/Run.java]
I hope there can be some more optimization for SparseFixedBitSet so that it can
perform better.
> Store docIds as bitset when leafCardinality = 1 to speed up addAll
> ------------------------------------------------------------------
>
> Key: LUCENE-10233
> URL: https://issues.apache.org/jira/browse/LUCENE-10233
> Project: Lucene - Core
> Issue Type: Improvement
> Components: core/codecs
> Reporter: Feng Guo
> Priority: Major
> Time Spent: 20m
> Remaining Estimate: 0h
>
> In low cardinality points cases, id blocks will usually store doc ids that
> have the same point value, and {{intersect}} will get into {{addAll}} logic.
> If we store ids as bitset, and give the IntersectVisitor bulk visiting
> ability, we can speed up addAll because we can just execute the 'or' logic
> between the result and the block ids.
> Optimization will be triggered when the following conditions are met at the
> same time:
> # leafCardinality = 1
> # max(docId) - min(docId) <= 16 * pointCount (in order to avoid expanding
> too much storage)
> # no duplicate doc id
> I mocked a field that has 10,000,000 docs per value and search it with a 1
> term PointInSetQuery, the build scorer time decreased from 71ms to 8ms.
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