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https://issues.apache.org/jira/browse/LUCENE-8836?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17527349#comment-17527349
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ASF subversion and git services commented on LUCENE-8836:
---------------------------------------------------------

Commit 2a4c21bb586c2c5afb8550b88cbfd9dd15d433c5 in lucene's branch 
refs/heads/main from Adrien Grand
[ https://gitbox.apache.org/repos/asf?p=lucene.git;h=2a4c21bb586 ]

LUCENE-8836: Speed up TermsEnum#lookupOrd on increasing sequences of ords. 
(#827)



> Optimize DocValues TermsDict to continue scanning from the last position when 
> possible
> --------------------------------------------------------------------------------------
>
>                 Key: LUCENE-8836
>                 URL: https://issues.apache.org/jira/browse/LUCENE-8836
>             Project: Lucene - Core
>          Issue Type: Improvement
>            Reporter: Bruno Roustant
>            Priority: Major
>              Labels: docValues, optimization
>          Time Spent: 2h 40m
>  Remaining Estimate: 0h
>
> Lucene80DocValuesProducer.TermsDict is used to lookup for either a term or a 
> term ordinal.
> Currently it does not have the optimization the FSTEnum has: to be able to 
> continue a sequential scan from where the last lookup was in the IndexInput. 
> For sparse lookups (when searching only a few terms or ordinal) it is not an 
> issue. But for multiple lookups in a row this optimization could save 
> re-scanning all the terms from the block start (since they are delat encoded).
> This patch proposes the optimization.
> To estimate the gain, we ran 3 Lucene tests while counting the seeks and the 
> term reads in the IndexInput, with and without the optimization:
> TestLucene70DocValuesFormat - the optimization saves 24% seeks and 15% term 
> reads.
> TestDocValuesQueries - the optimization adds 0.7% seeks and 0.003% term reads.
> TestDocValuesRewriteMethod.testRegexps - the optimization saves 71% seeks and 
> 82% term reads.
> In some cases, when scanning many terms in lexicographical order, the 
> optimization saves a lot. In some case, when only looking for some sparse 
> terms, the optimization does not bring improvement, but does not penalize 
> neither. It seems to be worth to always have it.



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