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From "Mark Miller (JIRA)" <>
Subject [jira] Commented: (LUCENE-1997) Explore performance of multi-PQ vs single-PQ sorting API
Date Fri, 23 Oct 2009 03:14:59 GMT


Mark Miller commented on LUCENE-1997:

Results from John Wang:

||Seg size||Query||Tot hits||Sort||Top N||QPS old||QPS new||Pct change||
|log|<all>|1000000|rand string|10|91.76|108.63|{color:green}18.4%{color}|
|log|<all>|1000000|rand string|25|92.39|106.79|{color:green}15.6%{color}|
|log|<all>|1000000|rand string|50|91.30|104.02|{color:green}13.9%{color}|
|log|<all>|1000000|rand string|500|86.16|63.27|{color:red}-26.6%{color}|
|log|<all>|1000000|rand string|1000|76.92|64.85|{color:red}-15.7%{color}|
|log|<all>|1000000|rand int|10|114.03|114.85|{color:green}0.7%{color}|
|log|<all>|1000000|rand int|25|113.77|112.92|{color:red}-0.7%{color}|
|log|<all>|1000000|rand int|50|113.36|109.56|{color:red}-3.4%{color}|
|log|<all>|1000000|rand int|500|103.90|66.29|{color:red}-36.2%{color}|
|log|<all>|1000000|rand int|1000|89.52|70.67|{color:red}-21.1%{color}|

> Explore performance of multi-PQ vs single-PQ sorting API
> --------------------------------------------------------
>                 Key: LUCENE-1997
>                 URL:
>             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
> 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/
> 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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