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https://issues.apache.org/jira/browse/LUCENE-3328?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13068455#comment-13068455
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Robert Muir commented on LUCENE-3328:
-------------------------------------
Also, I am usually positive on backporting improvements to 3.x to get them back
to the users quickly, but I think
we should do this only in trunk.
The reason is: 3.x is going to be very hairy here, since the computation of
scoring (including score caches and shit) is
conflated into the postings list matching for termquery, since it has no
termstate to pull from, ...
> Specialize BooleanQuery if all clauses are TermQueries
> ------------------------------------------------------
>
> Key: LUCENE-3328
> URL: https://issues.apache.org/jira/browse/LUCENE-3328
> Project: Lucene - Java
> Issue Type: Improvement
> Components: core/search
> Affects Versions: 3.4, 4.0
> Reporter: Simon Willnauer
> Fix For: 3.4, 4.0
>
> Attachments: LUCENE-3328.patch, LUCENE-3328.patch
>
>
> During work on LUCENE-3319 I ran into issues with BooleanQuery compared to
> PhraseQuery in the exact case. If I disable scoring on PhraseQuery and bypass
> the position matching, essentially doing a conjunction match,
> ExactPhraseScorer beats plain boolean scorer by 40% which is a sizeable gain.
> I converted a ConjunctionScorer to use DocsEnum directly but still didn't get
> all the 40% from PhraseQuery. Yet, it turned out with further optimizations
> this gets very close to PhraseQuery. The biggest gain here came from
> converting the hand crafted loop in ConjunctionScorer#doNext to a for loop
> which seems to be less confusing to hotspot. In this particular case I think
> code specialization makes lots of sense since BQ with TQ is by far one of the
> most common queries.
> I will upload a patch shortly
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