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https://issues.apache.org/jira/browse/LUCENE-1997?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12769863#action_12769863
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Mark Miller commented on LUCENE-1997:
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Given good enough reasons, I could see saying we made a mistake and switching
back - as it is, for the reasons I've said, I don't find that to be the case. I
don't feel the new API was a mistake yet.
Lots of other guys to weigh in though. If everyone else feels like its the
right move, I'm not going to -1 it - just weighing in with how I feel.
I'm not seeing 10-20% faster across the board - on my system it doesnt even hit
10% and I'm a linux user and advocate. I'm all for performance, but < 10% here
and there is not enough to sway me against 30-50% loses in the large queue
cases, combined with having to shift back. Its not a clear win either way, but
I've said which way I lean.
Luckily, its not just me you have to convince. Lots of smart people still to
weigh in.
> Explore performance of multi-PQ vs single-PQ sorting API
> --------------------------------------------------------
>
> Key: LUCENE-1997
> URL: https://issues.apache.org/jira/browse/LUCENE-1997
> Project: Lucene - Java
> Issue Type: Improvement
> Components: Search
> Affects Versions: 2.9
> Reporter: Michael McCandless
> Assignee: Michael McCandless
> Attachments: LUCENE-1997.patch, LUCENE-1997.patch, LUCENE-1997.patch,
> LUCENE-1997.patch
>
>
> Spinoff from recent "lucene 2.9 sorting algorithm" thread on java-dev,
> where a simpler (non-segment-based) comparator API is proposed that
> gathers results into multiple PQs (one per segment) and then merges
> them in the end.
> I started from John's multi-PQ code and worked it into
> contrib/benchmark so that we could run perf tests. Then I generified
> the Python script I use for running search benchmarks (in
> contrib/benchmark/sortBench.py).
> The script first creates indexes with 1M docs (based on
> SortableSingleDocSource, and based on wikipedia, if available). Then
> it runs various combinations:
> * Index with 20 balanced segments vs index with the "normal" log
> segment size
> * Queries with different numbers of hits (only for wikipedia index)
> * Different top N
> * Different sorts (by title, for wikipedia, and by random string,
> random int, and country for the random index)
> For each test, 7 search rounds are run and the best QPS is kept. The
> script runs singlePQ then multiPQ, and records the resulting best QPS
> for each and produces table (in Jira format) as output.
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