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From "Yonik Seeley (JIRA)" <j...@apache.org>
Subject [jira] Commented: (LUCENE-1997) Explore performance of multi-PQ vs single-PQ sorting API
Date Wed, 28 Oct 2009 12:56:59 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-1997?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12770919#action_12770919
] 

Yonik Seeley commented on LUCENE-1997:
--------------------------------------

When I tried changing 5000000 to 4999999 I got exceptions... is this expected?

{code}
RUN: balanced=balanced source=random query=*:* sort=sort_field:int nhits=10
  log: logs/singlePQ_balanced=20_numHits=10_query=*:*_sort=sort_field:int_source=random
Traceback (most recent call last):
  File "sortBench.py", line 517, in <module>
    main()
  File "sortBench.py", line 374, in main
    run(mode, name)
  File "sortBench.py", line 486, in run
    singlePQ = r.runOne(s, 'singlePQ_%s' % prefix, INDEX_NUM_DOCS, query, verify=doVerify)
  File "sortBench.py", line 271, in runOne
    raise RuntimeError('indexNumDocs mismatch: expected %d but got %d' % (indexNumDocs, ndocs))
RuntimeError: indexNumDocs mismatch: expected 4999999 but got 4999996
{code}

> 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,
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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