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https://issues.apache.org/jira/browse/LUCENE-1997?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael McCandless updated LUCENE-1997:
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Attachment: LUCENE-1997.patch
Attached patch.
Note that patch is based on 2.9.x branch, so first checkout 2.9.x,
apply the patch, then:
cd contrib/benchmark
ant compile
<edit constants @ top of sortBench.py>
python -u sortBench.py -run results
python -u sortBench.py -report results
The important constants are INDEX_DIR_BASE (where created indexes are
stored), WIKI_FILE (points to .tar.bz2 or .tar export of wikipedia; if
this file can't be found the script just skips the wikipedia tests).
You can also change INDEX_NUM_DOCS and INDEX_NUM_THREADS.
If you don't have the wiki export downloaded, that's fine... the
script should just run the tests based on the random index.
> 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
>
>
> 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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