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https://issues.apache.org/jira/browse/LUCENE-2061?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael McCandless updated LUCENE-2061:
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Attachment: LUCENE-2061.patch
Attached first cut python script nrtBench.py.
You have to edit the constants up top, to point to both Wiki XML
export and a Wiki line file. It use the XML export to build up the
base index, and then the line file to do the "live" indexing.
It first runs a baseline, redline searching with 9 (default) threads,
and reports the net qps. (You'll have to write a queries.txt w/ the
queries to test). Then it steps through NRT reopen rates of every
0.1, 1.0, 2.5, 5.0 seconds X indexing rate of 1, 10, 100, 1000 per sec
(using 2 indexing threads), and then redlines the search threads,
comparing their search throughput to the baseline.
> Create benchmark & approach for testing Lucene's near real-time performance
> ---------------------------------------------------------------------------
>
> Key: LUCENE-2061
> URL: https://issues.apache.org/jira/browse/LUCENE-2061
> Project: Lucene - Java
> Issue Type: Task
> Components: Index
> Reporter: Michael McCandless
> Assignee: Michael McCandless
> Priority: Minor
> Attachments: LUCENE-2061.patch
>
>
> With the improvements to contrib/benchmark in LUCENE-2050, it's now
> possible to create compelling algs to test indexing & searching
> throughput against a periodically reopened near-real-time reader from
> the IndexWriter.
> Coming out of the discussions in LUCENE-1526, I think to properly
> characterize NRT, we should measure net search throughput as a
> function of both reopen rate (ie how often you get a new NRT reader
> from the writer) and indexing rate. We should also separately measure
> pure adds vs updates (deletes + adds); the latter is much more work
> for Lucene.
> This can help apps make capacity decisions... and can help us test
> performance of pending improvements for NRT (eg LUCENE-1313,
> LUCENE-2047).
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