mirror of https://github.com/apache/lucene.git
- Modified docs.
git-svn-id: https://svn.apache.org/repos/asf/lucene/java/trunk@149903 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
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bf5028d9ac
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<!-- start the processing -->
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<!-- ====================================================================== -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<!-- ====================================================================== -->
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<html>
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@ -122,17 +123,17 @@
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<blockquote>
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<p>
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The purpose of these user-submitted performance figures is to
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give current and potential users of Lucene a sense
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give current and potential users of Lucene a sense
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of how well Lucene scales. If the requirements for an upcoming
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project is similar to an existing benchmark, you
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project is similar to an existing benchmark, you
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will also have something to work with when designing the system
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architecture for the application.
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architecture for the application.
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</p>
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<p>
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If you've conducted performance tests with Lucene, we'd
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appreciate if you can submit these figures for display
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appreciate if you can submit these figures for display
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on this page. Post these figures to the lucene-user mailing list
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using this
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using this
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<a href="benchmarktemplate.xml">template</a>.
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</p>
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</blockquote>
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|
@ -153,57 +154,57 @@ using this
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<p>
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<b>Hardware Environment</b><br />
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<li><i>Dedicated machine for indexing</i>: Self-explanatory
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(yes/no)</li>
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(yes/no)</li>
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<li><i>CPU</i>: Self-explanatory (Type, Speed and Quantity)</li>
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<li><i>RAM</i>: Self-explanatory</li>
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<li><i>Drive configuration</i>: Self-explanatory (IDE, SCSI,
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RAID-1, RAID-5)</li>
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RAID-1, RAID-5)</li>
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</p>
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<p>
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<b>Software environment</b><br />
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<li><i>Java Version</i>: Version of Java SDK/JRE that is run
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</li>
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</li>
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<li><i>Java VM</i>: Server/client VM, Sun VM/JRockIt</li>
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<li><i>OS Version</i>: Self-explanatory</li>
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<li><i>Location of index</i>: Is the index stored in filesystem
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or database? Is it on the same server(local) or
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or database? Is it on the same server(local) or
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over the network?</li>
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</p>
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<p>
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<b>Lucene indexing variables</b><br />
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<li><i>Number of source documents</i>: Number of documents being
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indexed</li>
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indexed</li>
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<li><i>Total filesize of source documents</i>:
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Self-explanatory</li>
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Self-explanatory</li>
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<li><i>Average filesize of source documents</i>:
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Self-explanatory</li>
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Self-explanatory</li>
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<li><i>Source documents storage location</i>: Where are the
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documents being indexed located?
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documents being indexed located?
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Filesystem, DB, http,etc</li>
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<li><i>File type of source documents</i>: Types of files being
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indexed, e.g. HTML files, XML files, PDF files, etc.</li>
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indexed, e.g. HTML files, XML files, PDF files, etc.</li>
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<li><i>Parser(s) used, if any</i>: Parsers used for parsing the
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various files for indexing,
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various files for indexing,
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e.g. XML parser, HTML parser, etc.</li>
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<li><i>Analyzer(s) used</i>: Type of Lucene analyzer used</li>
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<li><i>Number of fields per document</i>: Number of Fields each
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Document contains</li>
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Document contains</li>
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<li><i>Type of fields</i>: Type of each field</li>
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<li><i>Index persistence</i>: Where the index is stored, e.g.
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FSDirectory, SqlDirectory, etc</li>
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FSDirectory, SqlDirectory, etc</li>
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</p>
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<p>
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<b>Figures</b><br />
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<li><i>Time taken (in ms/s as an average of at least 3 indexing
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runs)</i>: Time taken to index all files</li>
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runs)</i>: Time taken to index all files</li>
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<li><i>Time taken / 1000 docs indexed</i>: Time taken to index
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1000 files</li>
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1000 files</li>
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<li><i>Memory consumption</i>: Self-explanatory</li>
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</p>
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<p>
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<b>Notes</b><br />
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<li><i>Notes</i>: Any comments which don't belong in the above,
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special tuning/strategies, etc</li>
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special tuning/strategies, etc</li>
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</p>
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</ul>
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</p>
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@ -222,14 +223,14 @@ special tuning/strategies, etc</li>
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<blockquote>
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<p>
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These benchmarks have been kindly submitted by Lucene users for
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reference purposes.
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reference purposes.
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</p>
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<p><b>We make NO guarantees regarding their accuracy or
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validity.</b>
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validity.</b>
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</p>
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<p>We strongly recommend you conduct your own
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performance benchmarks before deciding on a particular
|
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hardware/software setup (and hopefully submit
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hardware/software setup (and hopefully submit
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these figures to us).
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</p>
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<table border="0" cellspacing="0" cellpadding="2" width="100%">
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|
@ -258,10 +259,10 @@ hardware/software setup (and hopefully submit
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<p>
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<b>Lucene indexing variables</b><br />
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<li><i>Number of source documents</i>: Random generator. Set
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to make 1M documents
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in 2x500,000 batches.</li>
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to make 1M documents
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in 2x500,000 batches.</li>
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<li><i>Total filesize of source documents</i>: > 1GB if
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stored</li>
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stored</li>
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<li><i>Average filesize of source documents</i>: 1KB</li>
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<li><i>Source documents storage location</i>: Filesystem</li>
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<li><i>File type of source documents</i>: Generated</li>
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@ -274,7 +275,7 @@ stored</li>
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<p>
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<b>Figures</b><br />
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<li><i>Time taken (in ms/s as an average of at least 3
|
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indexing runs)</i>: </li>
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indexing runs)</i>: </li>
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<li><i>Time taken / 1000 docs indexed</i>: 49 seconds</li>
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<li><i>Memory consumption</i>:</li>
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</p>
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|
@ -283,43 +284,43 @@ indexing runs)</i>: </li>
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<li><i>Notes</i>:
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<p>
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A windows client ran a random document generator which
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created
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created
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documents based on some arrays of values and an excerpt
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(approx 1kb)
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(approx 1kb)
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from a text file of the bible (King James version).<br />
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These were submitted via a socket connection (open throughout
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indexing process).<br />
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The index writer was not closed between index calls.<br />
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This created a 400Mb index in 23 files (after
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optimization).<br />
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optimization).<br />
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</p>
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<p>
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<u>Query details</u>:<br />
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</p>
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<p>
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Set up a threaded class to start x number of simultaneous
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threads to
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threads to
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search the above created index.
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</p>
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<p>
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Query: +Domain:sos +(+((Name:goo*^2.0 Name:plan*^2.0)
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(Teaser:goo* Tea
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(Teaser:goo* Tea
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||||
ser:plan*) (Details:goo* Details:plan*)) -Cancel:y)
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+DisplayStartDate:[mkwsw2jk0
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-mq3dj1uq0] +EndDate:[mq3dj1uq0-ntlxuggw0]
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</p>
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<p>
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This query counted 34000 documents and I limited the returned
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documents
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documents
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to 5.
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</p>
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<p>
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This is using Peter Halacsy's IndexSearcherCache slightly
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modified to
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modified to
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be a singleton returned cached searchers for a given
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directory. This
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directory. This
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solved an initial problem with too many files open and
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running out of
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running out of
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linux handles for them.
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</p>
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<pre>
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|
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</pre>
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<p>
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I removed the two date range terms from the query and it made
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a HUGE
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a HUGE
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difference in performance. With 4 threads the avg time
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dropped to 900ms!
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dropped to 900ms!
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</p>
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<p>Other query optimizations made little difference.</p></li>
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</p>
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|
@ -360,11 +361,11 @@ dropped to 900ms!
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<p>
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<b>Hardware Environment</b><br />
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<li><i>Dedicated machine for indexing</i>: No, but nominal
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usage at time of indexing.</li>
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usage at time of indexing.</li>
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<li><i>CPU</i>: Compaq Proliant 1850R/600 2 X pIII 600</li>
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<li><i>RAM</i>: 1GB, 256MB allocated to JVM.</li>
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<li><i>Drive configuration</i>: RAID 5 on Fibre Channel
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Array</li>
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Array</li>
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</p>
|
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<p>
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<b>Software environment</b><br />
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|
@ -378,43 +379,43 @@ Array</li>
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<li><i>Number of source documents</i>: about 60K</li>
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<li><i>Total filesize of source documents</i>: 6.5GB</li>
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<li><i>Average filesize of source documents</i>: 100K
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(6.5GB/60K documents)</li>
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(6.5GB/60K documents)</li>
|
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<li><i>Source documents storage location</i>: filesystem on
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NTFS</li>
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NTFS</li>
|
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<li><i>File type of source documents</i>: </li>
|
||||
<li><i>Parser(s) used, if any</i>: Currently the only parser
|
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used is the Quiotix html
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used is the Quiotix html
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parser.</li>
|
||||
<li><i>Analyzer(s) used</i>: SimpleAnalyzer</li>
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<li><i>Number of fields per document</i>: 8</li>
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<li><i>Type of fields</i>: All strings, and all are stored
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and indexed.</li>
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and indexed.</li>
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||||
<li><i>Index persistence</i>: FSDirectory</li>
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||||
</p>
|
||||
<p>
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||||
<b>Figures</b><br />
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||||
<li><i>Time taken (in ms/s as an average of at least 3
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indexing runs)</i>: 1 hour 12 minutes, 1 hour 14 minutes and 1 hour 17
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minutes. Note that the #
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indexing runs)</i>: 1 hour 12 minutes, 1 hour 14 minutes and 1 hour 17
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minutes. Note that the #
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||||
and size of documents changes daily.</li>
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<li><i>Time taken / 1000 docs indexed</i>: </li>
|
||||
<li><i>Memory consumption</i>: JVM is given 256MB and uses it
|
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all.</li>
|
||||
all.</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Notes</b><br />
|
||||
<li><i>Notes</i>:
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<p>
|
||||
We have 10 threads reading files from the filesystem and
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parsing and
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||||
parsing and
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analyzing them and the pushing them onto a queue and a single
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thread poping
|
||||
thread poping
|
||||
them from the queue and indexing. Note that we are indexing
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||||
email messages
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||||
email messages
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||||
and are storing the entire plaintext in of the message in the
|
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index. If the
|
||||
index. If the
|
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message contains attachment and we do not have a filter for
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||||
the attachment
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||||
the attachment
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||||
(ie. we do not do PDFs yet), we discard the data.
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</p></li>
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</p>
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|
@ -425,6 +426,81 @@ the attachment
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</blockquote>
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</td></tr>
|
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<tr><td><br/></td></tr>
|
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</table>
|
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<table border="0" cellspacing="0" cellpadding="2" width="100%">
|
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<tr><td bgcolor="#828DA6">
|
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<font color="#ffffff" face="arial,helvetica,sanserif">
|
||||
<a name="Daniel Armbrust's benchmarks"><strong>Daniel Armbrust's benchmarks</strong></a>
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</font>
|
||||
</td></tr>
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<tr><td>
|
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<blockquote>
|
||||
<p>
|
||||
My disclaimer is that this is a very poor "Benchmark". It was not done for raw speed,
|
||||
nor was the total index built in one shot. The index was created on several different
|
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machines (all with these specs, or very similar), with each machine indexing batches of 500,000 to
|
||||
1 million documents per batch. Each of these small indexes was then moved to a
|
||||
much larger drive, where they were all merged together into a big index.
|
||||
This process was done manually, over the course of several months, as the sources became available.
|
||||
</p>
|
||||
<ul>
|
||||
<p>
|
||||
<b>Hardware Environment</b><br />
|
||||
<li><i>Dedicated machine for indexing</i>: no - The machine had moderate to low load. However, the indexing process was built single
|
||||
threaded, so it only took advantage of 1 of the processors. It usually got 100% of this processor.</li>
|
||||
<li><i>CPU</i>: Sun Ultra 80 4 x 64 bit processors</li>
|
||||
<li><i>RAM</i>: 4 GB Memory</li>
|
||||
<li><i>Drive configuration</i>: Ultra-SCSI Wide 10000 RPM 36GB Drive</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Software environment</b><br />
|
||||
<li><i>Java Version</i>: 1.3.1</li>
|
||||
<li><i>Java VM</i>: </li>
|
||||
<li><i>OS Version</i>: Sun 5.8 (64 bit)</li>
|
||||
<li><i>Location of index</i>: local</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Lucene indexing variables</b><br />
|
||||
<li><i>Number of source documents</i>: 13,820,517</li>
|
||||
<li><i>Total filesize of source documents</i>: 87.3 GB</li>
|
||||
<li><i>Average filesize of source documents</i>: 6.3 KB</li>
|
||||
<li><i>Source documents storage location</i>: Filesystem</li>
|
||||
<li><i>File type of source documents</i>: XML</li>
|
||||
<li><i>Parser(s) used, if any</i>: </li>
|
||||
<li><i>Analyzer(s) used</i>: A home grown analyzer that simply removes stopwords.</li>
|
||||
<li><i>Number of fields per document</i>: 1 - 31</li>
|
||||
<li><i>Type of fields</i>: All text, though 2 of them are dates (20001205) that we filter on</li>
|
||||
<li><i>Index persistence</i>: FSDirectory</li>
|
||||
<li><i>Index size</i>: 12.5 GB</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Figures</b><br />
|
||||
<li><i>Time taken (in ms/s as an average of at least 3
|
||||
indexing runs)</i>: For 617271 documents, 209698 seconds (or ~2.5 days)</li>
|
||||
<li><i>Time taken / 1000 docs indexed</i>: 340 Seconds</li>
|
||||
<li><i>Memory consumption</i>: (java executed with) java -Xmx1000m -Xss8192k so
|
||||
1 GB of memory was allotted to the indexer</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Notes</b><br />
|
||||
<li><i>Notes</i>:
|
||||
<p>
|
||||
The source documents were XML. The "indexer" opened each document one at a time, ran an
|
||||
XSL transformation on them, and then proceeded to index the stream. The indexer optimized
|
||||
the index every 50,000 documents (on this run) though previously, we optimized every
|
||||
300,000 documents. The performance didn't change much either way. We did no other
|
||||
tuning (RAM Directories, separate process to pretransform the source material, etc)
|
||||
to make it index faster. When all of these individual indexes were built, they were
|
||||
merged together into the main index. That process usually took ~ a day.
|
||||
</p></li>
|
||||
</p>
|
||||
</ul>
|
||||
<p>
|
||||
Daniel can be contacted at Armbrust.Daniel at mayo.edu.
|
||||
</p>
|
||||
</blockquote>
|
||||
</td></tr>
|
||||
<tr><td><br/></td></tr>
|
||||
</table>
|
||||
</blockquote>
|
||||
</p>
|
||||
|
|
|
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|
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|
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<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<!-- ====================================================================== -->
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<html>
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|
|
|
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<!-- start the processing -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<html>
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|
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|
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<!-- start the processing -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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||||
<!-- Main Page Section -->
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<!-- ====================================================================== -->
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<html>
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|
|
|
@ -5,6 +5,7 @@
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||||
<!-- start the processing -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<html>
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|
|
|
@ -5,6 +5,7 @@
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||||
<!-- start the processing -->
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||||
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||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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||||
<html>
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|
|
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@ -5,6 +5,7 @@
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<!-- start the processing -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<!-- ====================================================================== -->
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<html>
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|
|
|
@ -5,6 +5,7 @@
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<!-- start the processing -->
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<!-- ====================================================================== -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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||||
<!-- Main Page Section -->
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<!-- ====================================================================== -->
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<html>
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|
|
|
@ -5,6 +5,7 @@
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<!-- start the processing -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<html>
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|
|
|
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<!-- start the processing -->
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<!-- ====================================================================== -->
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<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
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<!-- Main Page Section -->
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<!-- ====================================================================== -->
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||||
<html>
|
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|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -5,6 +5,7 @@
|
|||
|
||||
<!-- start the processing -->
|
||||
<!-- ====================================================================== -->
|
||||
<!-- GENERATED FILE, DO NOT EDIT, EDIT THE XML FILE IN xdocs INSTEAD! -->
|
||||
<!-- Main Page Section -->
|
||||
<!-- ====================================================================== -->
|
||||
<html>
|
||||
|
|
|
@ -9,17 +9,17 @@
|
|||
<section name="Performance Benchmarks">
|
||||
<p>
|
||||
The purpose of these user-submitted performance figures is to
|
||||
give current and potential users of Lucene a sense
|
||||
give current and potential users of Lucene a sense
|
||||
of how well Lucene scales. If the requirements for an upcoming
|
||||
project is similar to an existing benchmark, you
|
||||
project is similar to an existing benchmark, you
|
||||
will also have something to work with when designing the system
|
||||
architecture for the application.
|
||||
architecture for the application.
|
||||
</p>
|
||||
<p>
|
||||
If you've conducted performance tests with Lucene, we'd
|
||||
appreciate if you can submit these figures for display
|
||||
appreciate if you can submit these figures for display
|
||||
on this page. Post these figures to the lucene-user mailing list
|
||||
using this
|
||||
using this
|
||||
<a href="benchmarktemplate.xml">template</a>.
|
||||
</p>
|
||||
</section>
|
||||
|
@ -30,57 +30,57 @@ using this
|
|||
<p>
|
||||
<b>Hardware Environment</b><br/>
|
||||
<li><i>Dedicated machine for indexing</i>: Self-explanatory
|
||||
(yes/no)</li>
|
||||
(yes/no)</li>
|
||||
<li><i>CPU</i>: Self-explanatory (Type, Speed and Quantity)</li>
|
||||
<li><i>RAM</i>: Self-explanatory</li>
|
||||
<li><i>Drive configuration</i>: Self-explanatory (IDE, SCSI,
|
||||
RAID-1, RAID-5)</li>
|
||||
RAID-1, RAID-5)</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Software environment</b><br/>
|
||||
<li><i>Java Version</i>: Version of Java SDK/JRE that is run
|
||||
</li>
|
||||
</li>
|
||||
<li><i>Java VM</i>: Server/client VM, Sun VM/JRockIt</li>
|
||||
<li><i>OS Version</i>: Self-explanatory</li>
|
||||
<li><i>Location of index</i>: Is the index stored in filesystem
|
||||
or database? Is it on the same server(local) or
|
||||
or database? Is it on the same server(local) or
|
||||
over the network?</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Lucene indexing variables</b><br/>
|
||||
<li><i>Number of source documents</i>: Number of documents being
|
||||
indexed</li>
|
||||
indexed</li>
|
||||
<li><i>Total filesize of source documents</i>:
|
||||
Self-explanatory</li>
|
||||
Self-explanatory</li>
|
||||
<li><i>Average filesize of source documents</i>:
|
||||
Self-explanatory</li>
|
||||
Self-explanatory</li>
|
||||
<li><i>Source documents storage location</i>: Where are the
|
||||
documents being indexed located?
|
||||
documents being indexed located?
|
||||
Filesystem, DB, http,etc</li>
|
||||
<li><i>File type of source documents</i>: Types of files being
|
||||
indexed, e.g. HTML files, XML files, PDF files, etc.</li>
|
||||
indexed, e.g. HTML files, XML files, PDF files, etc.</li>
|
||||
<li><i>Parser(s) used, if any</i>: Parsers used for parsing the
|
||||
various files for indexing,
|
||||
various files for indexing,
|
||||
e.g. XML parser, HTML parser, etc.</li>
|
||||
<li><i>Analyzer(s) used</i>: Type of Lucene analyzer used</li>
|
||||
<li><i>Number of fields per document</i>: Number of Fields each
|
||||
Document contains</li>
|
||||
Document contains</li>
|
||||
<li><i>Type of fields</i>: Type of each field</li>
|
||||
<li><i>Index persistence</i>: Where the index is stored, e.g.
|
||||
FSDirectory, SqlDirectory, etc</li>
|
||||
FSDirectory, SqlDirectory, etc</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Figures</b><br/>
|
||||
<li><i>Time taken (in ms/s as an average of at least 3 indexing
|
||||
runs)</i>: Time taken to index all files</li>
|
||||
runs)</i>: Time taken to index all files</li>
|
||||
<li><i>Time taken / 1000 docs indexed</i>: Time taken to index
|
||||
1000 files</li>
|
||||
1000 files</li>
|
||||
<li><i>Memory consumption</i>: Self-explanatory</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Notes</b><br/>
|
||||
<li><i>Notes</i>: Any comments which don't belong in the above,
|
||||
special tuning/strategies, etc</li>
|
||||
special tuning/strategies, etc</li>
|
||||
</p>
|
||||
</ul>
|
||||
</p>
|
||||
|
@ -89,14 +89,14 @@ special tuning/strategies, etc</li>
|
|||
<section name="User-submitted Benchmarks">
|
||||
<p>
|
||||
These benchmarks have been kindly submitted by Lucene users for
|
||||
reference purposes.
|
||||
reference purposes.
|
||||
</p>
|
||||
<p><b>We make NO guarantees regarding their accuracy or
|
||||
validity.</b>
|
||||
validity.</b>
|
||||
</p>
|
||||
<p>We strongly recommend you conduct your own
|
||||
performance benchmarks before deciding on a particular
|
||||
hardware/software setup (and hopefully submit
|
||||
hardware/software setup (and hopefully submit
|
||||
these figures to us).
|
||||
</p>
|
||||
|
||||
|
@ -119,10 +119,10 @@ hardware/software setup (and hopefully submit
|
|||
<p>
|
||||
<b>Lucene indexing variables</b><br/>
|
||||
<li><i>Number of source documents</i>: Random generator. Set
|
||||
to make 1M documents
|
||||
in 2x500,000 batches.</li>
|
||||
to make 1M documents
|
||||
in 2x500,000 batches.</li>
|
||||
<li><i>Total filesize of source documents</i>: > 1GB if
|
||||
stored</li>
|
||||
stored</li>
|
||||
<li><i>Average filesize of source documents</i>: 1KB</li>
|
||||
<li><i>Source documents storage location</i>: Filesystem</li>
|
||||
<li><i>File type of source documents</i>: Generated</li>
|
||||
|
@ -135,7 +135,7 @@ stored</li>
|
|||
<p>
|
||||
<b>Figures</b><br/>
|
||||
<li><i>Time taken (in ms/s as an average of at least 3
|
||||
indexing runs)</i>: </li>
|
||||
indexing runs)</i>: </li>
|
||||
<li><i>Time taken / 1000 docs indexed</i>: 49 seconds</li>
|
||||
<li><i>Memory consumption</i>:</li>
|
||||
</p>
|
||||
|
@ -144,43 +144,43 @@ indexing runs)</i>: </li>
|
|||
<li><i>Notes</i>:
|
||||
<p>
|
||||
A windows client ran a random document generator which
|
||||
created
|
||||
created
|
||||
documents based on some arrays of values and an excerpt
|
||||
(approx 1kb)
|
||||
(approx 1kb)
|
||||
from a text file of the bible (King James version).<br/>
|
||||
These were submitted via a socket connection (open throughout
|
||||
indexing process).<br/>
|
||||
The index writer was not closed between index calls.<br/>
|
||||
This created a 400Mb index in 23 files (after
|
||||
optimization).<br/>
|
||||
optimization).<br/>
|
||||
</p>
|
||||
<p>
|
||||
<u>Query details</u>:<br/>
|
||||
</p>
|
||||
<p>
|
||||
Set up a threaded class to start x number of simultaneous
|
||||
threads to
|
||||
threads to
|
||||
search the above created index.
|
||||
</p>
|
||||
<p>
|
||||
Query: +Domain:sos +(+((Name:goo*^2.0 Name:plan*^2.0)
|
||||
(Teaser:goo* Tea
|
||||
(Teaser:goo* Tea
|
||||
ser:plan*) (Details:goo* Details:plan*)) -Cancel:y)
|
||||
+DisplayStartDate:[mkwsw2jk0
|
||||
-mq3dj1uq0] +EndDate:[mq3dj1uq0-ntlxuggw0]
|
||||
</p>
|
||||
<p>
|
||||
This query counted 34000 documents and I limited the returned
|
||||
documents
|
||||
documents
|
||||
to 5.
|
||||
</p>
|
||||
<p>
|
||||
This is using Peter Halacsy's IndexSearcherCache slightly
|
||||
modified to
|
||||
modified to
|
||||
be a singleton returned cached searchers for a given
|
||||
directory. This
|
||||
directory. This
|
||||
solved an initial problem with too many files open and
|
||||
running out of
|
||||
running out of
|
||||
linux handles for them.
|
||||
</p>
|
||||
<pre>
|
||||
|
@ -195,9 +195,9 @@ running out of
|
|||
</pre>
|
||||
<p>
|
||||
I removed the two date range terms from the query and it made
|
||||
a HUGE
|
||||
a HUGE
|
||||
difference in performance. With 4 threads the avg time
|
||||
dropped to 900ms!
|
||||
dropped to 900ms!
|
||||
</p>
|
||||
<p>Other query optimizations made little difference.</p></li>
|
||||
</p>
|
||||
|
@ -212,11 +212,11 @@ dropped to 900ms!
|
|||
<p>
|
||||
<b>Hardware Environment</b><br/>
|
||||
<li><i>Dedicated machine for indexing</i>: No, but nominal
|
||||
usage at time of indexing.</li>
|
||||
usage at time of indexing.</li>
|
||||
<li><i>CPU</i>: Compaq Proliant 1850R/600 2 X pIII 600</li>
|
||||
<li><i>RAM</i>: 1GB, 256MB allocated to JVM.</li>
|
||||
<li><i>Drive configuration</i>: RAID 5 on Fibre Channel
|
||||
Array</li>
|
||||
Array</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Software environment</b><br/>
|
||||
|
@ -230,43 +230,43 @@ Array</li>
|
|||
<li><i>Number of source documents</i>: about 60K</li>
|
||||
<li><i>Total filesize of source documents</i>: 6.5GB</li>
|
||||
<li><i>Average filesize of source documents</i>: 100K
|
||||
(6.5GB/60K documents)</li>
|
||||
(6.5GB/60K documents)</li>
|
||||
<li><i>Source documents storage location</i>: filesystem on
|
||||
NTFS</li>
|
||||
NTFS</li>
|
||||
<li><i>File type of source documents</i>: </li>
|
||||
<li><i>Parser(s) used, if any</i>: Currently the only parser
|
||||
used is the Quiotix html
|
||||
used is the Quiotix html
|
||||
parser.</li>
|
||||
<li><i>Analyzer(s) used</i>: SimpleAnalyzer</li>
|
||||
<li><i>Number of fields per document</i>: 8</li>
|
||||
<li><i>Type of fields</i>: All strings, and all are stored
|
||||
and indexed.</li>
|
||||
and indexed.</li>
|
||||
<li><i>Index persistence</i>: FSDirectory</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Figures</b><br/>
|
||||
<li><i>Time taken (in ms/s as an average of at least 3
|
||||
indexing runs)</i>: 1 hour 12 minutes, 1 hour 14 minutes and 1 hour 17
|
||||
minutes. Note that the #
|
||||
indexing runs)</i>: 1 hour 12 minutes, 1 hour 14 minutes and 1 hour 17
|
||||
minutes. Note that the #
|
||||
and size of documents changes daily.</li>
|
||||
<li><i>Time taken / 1000 docs indexed</i>: </li>
|
||||
<li><i>Memory consumption</i>: JVM is given 256MB and uses it
|
||||
all.</li>
|
||||
all.</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Notes</b><br/>
|
||||
<li><i>Notes</i>:
|
||||
<p>
|
||||
We have 10 threads reading files from the filesystem and
|
||||
parsing and
|
||||
parsing and
|
||||
analyzing them and the pushing them onto a queue and a single
|
||||
thread poping
|
||||
thread poping
|
||||
them from the queue and indexing. Note that we are indexing
|
||||
email messages
|
||||
email messages
|
||||
and are storing the entire plaintext in of the message in the
|
||||
index. If the
|
||||
index. If the
|
||||
message contains attachment and we do not have a filter for
|
||||
the attachment
|
||||
the attachment
|
||||
(ie. we do not do PDFs yet), we discard the data.
|
||||
</p></li>
|
||||
</p>
|
||||
|
@ -276,8 +276,74 @@ the attachment
|
|||
</p>
|
||||
</subsection>
|
||||
|
||||
|
||||
<subsection name="Daniel Armbrust's benchmarks">
|
||||
<p>
|
||||
My disclaimer is that this is a very poor "Benchmark". It was not done for raw speed,
|
||||
nor was the total index built in one shot. The index was created on several different
|
||||
machines (all with these specs, or very similar), with each machine indexing batches of 500,000 to
|
||||
1 million documents per batch. Each of these small indexes was then moved to a
|
||||
much larger drive, where they were all merged together into a big index.
|
||||
This process was done manually, over the course of several months, as the sources became available.
|
||||
</p>
|
||||
<ul>
|
||||
<p>
|
||||
<b>Hardware Environment</b><br/>
|
||||
<li><i>Dedicated machine for indexing</i>: no - The machine had moderate to low load. However, the indexing process was built single
|
||||
threaded, so it only took advantage of 1 of the processors. It usually got 100% of this processor.</li>
|
||||
<li><i>CPU</i>: Sun Ultra 80 4 x 64 bit processors</li>
|
||||
<li><i>RAM</i>: 4 GB Memory</li>
|
||||
<li><i>Drive configuration</i>: Ultra-SCSI Wide 10000 RPM 36GB Drive</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Software environment</b><br/>
|
||||
<li><i>Java Version</i>: 1.3.1</li>
|
||||
<li><i>Java VM</i>: </li>
|
||||
<li><i>OS Version</i>: Sun 5.8 (64 bit)</li>
|
||||
<li><i>Location of index</i>: local</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Lucene indexing variables</b><br/>
|
||||
<li><i>Number of source documents</i>: 13,820,517</li>
|
||||
<li><i>Total filesize of source documents</i>: 87.3 GB</li>
|
||||
<li><i>Average filesize of source documents</i>: 6.3 KB</li>
|
||||
<li><i>Source documents storage location</i>: Filesystem</li>
|
||||
<li><i>File type of source documents</i>: XML</li>
|
||||
<li><i>Parser(s) used, if any</i>: </li>
|
||||
<li><i>Analyzer(s) used</i>: A home grown analyzer that simply removes stopwords.</li>
|
||||
<li><i>Number of fields per document</i>: 1 - 31</li>
|
||||
<li><i>Type of fields</i>: All text, though 2 of them are dates (20001205) that we filter on</li>
|
||||
<li><i>Index persistence</i>: FSDirectory</li>
|
||||
<li><i>Index size</i>: 12.5 GB</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Figures</b><br/>
|
||||
<li><i>Time taken (in ms/s as an average of at least 3
|
||||
indexing runs)</i>: For 617271 documents, 209698 seconds (or ~2.5 days)</li>
|
||||
<li><i>Time taken / 1000 docs indexed</i>: 340 Seconds</li>
|
||||
<li><i>Memory consumption</i>: (java executed with) java -Xmx1000m -Xss8192k so
|
||||
1 GB of memory was allotted to the indexer</li>
|
||||
</p>
|
||||
<p>
|
||||
<b>Notes</b><br/>
|
||||
<li><i>Notes</i>:
|
||||
<p>
|
||||
The source documents were XML. The "indexer" opened each document one at a time, ran an
|
||||
XSL transformation on them, and then proceeded to index the stream. The indexer optimized
|
||||
the index every 50,000 documents (on this run) though previously, we optimized every
|
||||
300,000 documents. The performance didn't change much either way. We did no other
|
||||
tuning (RAM Directories, separate process to pretransform the source material, etc)
|
||||
to make it index faster. When all of these individual indexes were built, they were
|
||||
merged together into the main index. That process usually took ~ a day.
|
||||
</p></li>
|
||||
</p>
|
||||
</ul>
|
||||
<p>
|
||||
Daniel can be contacted at Armbrust.Daniel at mayo.edu.
|
||||
</p>
|
||||
</subsection>
|
||||
|
||||
</section>
|
||||
|
||||
</body>
|
||||
</document>
|
||||
|
||||
|
|
Loading…
Reference in New Issue