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743 lines
37 KiB
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<meta name="author" value="Kelvin Tan">
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<title>Jakarta Lucene - Resources - Performance Benchmarks</title>
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<a href="http://jakarta.apache.org/lucene/"><img src="./images/lucene_green_300.gif" alt="Jakarta Lucene" border="0"/></a>
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<p><strong>About</strong></p>
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<ul>
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<li> <a href="./index.html">Overview</a>
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<li> <a href="http://wiki.apache.org/jakarta-lucene/PoweredBy">Powered by Lucene</a>
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<li> <a href="./whoweare.html">Who We Are</a>
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<li> <a href="http://wiki.apache.org/jakarta-lucene">Wiki</a>
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<li> <a href="./benchmarks.html">Benchmarks</a>
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<li> <a href="http://issues.apache.org/bugzilla/buglist.cgi?bug_status=NEW&bug_status=ASSIGNED&bug_status=REOPENED&email1=&emailtype1=substring&emailassigned_to1=1&email2=&emailtype2=substring&emailreporter2=1&bugidtype=include&bug_id=&changedin=&votes=&chfieldfrom=&chfieldto=Now&chfieldvalue=&product=Lucene&short_desc=%5BPATCH%5D&short_desc_type=allwordssubstr&long_desc=&long_desc_type=allwordssubstr&bug_file_loc=&bug_file_loc_type=allwordssubstr&keywords=&keywords_type=anywords&field0-0-0=noop&type0-0-0=noop&value0-0-0=&cmdtype=doit&order=Importance">Patches</a>
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<li> <a href="./lucene-sandbox/">Lucene Sandbox</a>
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<p><strong>Download</strong></p>
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<li> <a href="http://www.apache.org/dyn/closer.cgi/jakarta/lucene/binaries/">Binaries</a>
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<li> <a href="http://www.apache.org/dyn/closer.cgi/jakarta/lucene/source/">Source Code</a>
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<li> <a href="http://jakarta.apache.org/site/cvsindex.html">CVS Repositories</a>
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<ul>
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<li> <a href="http://jakarta.apache.org/site/getinvolved.html">Get Involved</a>
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<li> <a href="http://jakarta.apache.org/site/acknowledgements.html">Acknowledgements</a>
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<li> <a href="http://jakarta.apache.org/site/contact.html">Contact</a>
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<td width="80%" align="left" valign="top">
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<table border="0" cellspacing="0" cellpadding="2" width="100%">
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<tr><td bgcolor="#525D76">
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<font color="#ffffff" face="arial,helvetica,sanserif">
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<a name="Performance Benchmarks"><strong>Performance Benchmarks</strong></a>
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</font>
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</td></tr>
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<tr><td>
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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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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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will also have something to work with when designing the system
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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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on this page. Post these figures to the lucene-user mailing list
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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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</p>
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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="#525D76">
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<font color="#ffffff" face="arial,helvetica,sanserif">
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<a name="Benchmark Variables"><strong>Benchmark Variables</strong></a>
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</font>
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</td></tr>
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<tr><td>
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<blockquote>
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<p>
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<ul>
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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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<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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</p>
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<p>
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<b>Software environment</b><br />
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<li><i>Lucene Version</i>: Self-explanatory</li>
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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><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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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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<li><i>Total filesize of source documents</i>:
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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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<li><i>Source documents storage location</i>: Where are the
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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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<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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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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<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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</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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<li><i>Time taken / 1000 docs indexed</i>: Time taken to index
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1000 files</li>
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<li><i>Memory consumption</i>: Self-explanatory</li>
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<li><i>Query speed</i>: average time a query takes, type
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of queries (e.g. simple one-term query, phrase query),
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not measuring any overhead outside Lucene</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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</p>
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</ul>
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</p>
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</blockquote>
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</p>
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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="#525D76">
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<font color="#ffffff" face="arial,helvetica,sanserif">
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<a name="User-submitted Benchmarks"><strong>User-submitted Benchmarks</strong></a>
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</font>
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</td></tr>
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<tr><td>
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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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</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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</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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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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<tr><td bgcolor="#828DA6">
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<font color="#ffffff" face="arial,helvetica,sanserif">
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<a name="Hamish Carpenter's benchmarks"><strong>Hamish Carpenter's benchmarks</strong></a>
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</font>
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</td></tr>
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<tr><td>
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<blockquote>
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<ul>
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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>: yes</li>
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<li><i>CPU</i>: Intel x86 P4 1.5Ghz</li>
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<li><i>RAM</i>: 512 DDR</li>
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<li><i>Drive configuration</i>: IDE 7200rpm Raid-1</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>Lucene Version</i>: 1.3</li>
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<li><i>Java Version</i>: 1.3.1 IBM JITC Enabled</li>
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<li><i>Java VM</i>: </li>
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<li><i>OS Version</i>: Debian Linux 2.4.18-686</li>
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<li><i>Location of index</i>: local</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>: Random generator. Set
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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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<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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<li><i>Parser(s) used, if any</i>: </li>
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<li><i>Analyzer(s) used</i>: Default</li>
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<li><i>Number of fields per document</i>: 11</li>
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<li><i>Type of fields</i>: 1 date, 1 id, 9 text</li>
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<li><i>Index persistence</i>: FSDirectory</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
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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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<p>
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<b>Notes</b><br />
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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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documents based on some arrays of values and an excerpt
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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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</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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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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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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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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be a singleton returned cached searchers for a given
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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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linux handles for them.
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</p>
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<pre>
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Threads|Avg Time per query (ms)
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1 1009ms
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2 2043ms
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3 3087ms
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4 4045ms
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.. .
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.. .
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10 10091ms
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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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difference in performance. With 4 threads the avg time
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dropped to 900ms!
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</p>
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<p>Other query optimizations made little difference.</p>
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</p>
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</ul>
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<p>
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Hamish can be contacted at hamish at catalyst.net.nz.
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</p>
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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">
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<a name="Justin Greene's benchmarks"><strong>Justin Greene's benchmarks</strong></a>
|
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</font>
|
|
</td></tr>
|
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<tr><td>
|
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<blockquote>
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<ul>
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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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<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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</p>
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<p>
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<b>Software environment</b><br />
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<li><i>Java Version</i>: 1.3.1_06</li>
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<li><i>Java VM</i>: </li>
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<li><i>OS Version</i>: Winnt 4/Sp6</li>
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<li><i>Location of index</i>: local</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>: 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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<li><i>Source documents storage location</i>: filesystem on
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NTFS</li>
|
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<li><i>File type of source documents</i>: </li>
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<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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parser.</li>
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<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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<li><i>Index persistence</i>: FSDirectory</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
|
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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>
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<li><i>Memory consumption</i>: JVM is given 256MB and uses it
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all.</li>
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</p>
|
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<p>
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<b>Notes</b><br />
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<p>
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We have 10 threads reading files from the filesystem 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
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them from the queue and indexing. Note that we are indexing
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email messages
|
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and are storing the entire plaintext in of the message in the
|
|
index. If the
|
|
message contains attachment and we do not have a filter for
|
|
the attachment
|
|
(ie. we do not do PDFs yet), we discard the data.
|
|
</p>
|
|
</p>
|
|
</ul>
|
|
<p>
|
|
Justin can be contacted at tvxh-lw4x at spamex.com.
|
|
</p>
|
|
</blockquote>
|
|
</td></tr>
|
|
<tr><td><br/></td></tr>
|
|
</table>
|
|
<table border="0" cellspacing="0" cellpadding="2" width="100%">
|
|
<tr><td bgcolor="#828DA6">
|
|
<font color="#ffffff" face="arial,helvetica,sanserif">
|
|
<a name="Daniel Armbrust's benchmarks"><strong>Daniel Armbrust's benchmarks</strong></a>
|
|
</font>
|
|
</td></tr>
|
|
<tr><td>
|
|
<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
|
|
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>Lucene Version</i>: 1.2</li>
|
|
<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 />
|
|
<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>
|
|
</p>
|
|
</ul>
|
|
<p>
|
|
Daniel can be contacted at Armbrust.Daniel at mayo.edu.
|
|
</p>
|
|
</blockquote>
|
|
</td></tr>
|
|
<tr><td><br/></td></tr>
|
|
</table>
|
|
<table border="0" cellspacing="0" cellpadding="2" width="100%">
|
|
<tr><td bgcolor="#828DA6">
|
|
<font color="#ffffff" face="arial,helvetica,sanserif">
|
|
<a name="Geoffrey Peddle's benchmarks"><strong>Geoffrey Peddle's benchmarks</strong></a>
|
|
</font>
|
|
</td></tr>
|
|
<tr><td>
|
|
<blockquote>
|
|
<p>
|
|
I'm doing a technical evaluation of search engines
|
|
for Ariba, an enterprise application software company.
|
|
I compared Lucene to a commercial C language based
|
|
search engine which I'll refer to as vendor A.
|
|
Overall Lucene's performance was similar to vendor A
|
|
and met our application's requirements. I've
|
|
summarized our results below.
|
|
</p>
|
|
<p>
|
|
Search scalability:<br />
|
|
We ran a set of 16 queries in a single thread for 20
|
|
iterations. We report below the times for the last 15
|
|
iterations (ie after the system was warmed up). The
|
|
4 sets of results below are for indexes with between
|
|
50,000 documents to 600,000 documents. Although the
|
|
times for Lucene grew faster with document count than
|
|
vendor A they were comparable.
|
|
</p>
|
|
<pre>
|
|
50K documents
|
|
Lucene 5.2 seconds
|
|
A 7.2
|
|
200K
|
|
Lucene 15.3
|
|
A 15.2
|
|
400K
|
|
Lucene 28.2
|
|
A 25.5
|
|
600K
|
|
Lucene 41
|
|
A 33
|
|
</pre>
|
|
<p>
|
|
Individual Query times:<br />
|
|
Total query times are very similar between the 2
|
|
systems but there were larger differences when you
|
|
looked at individual queries.
|
|
</p>
|
|
<p>
|
|
For simple queries with small result sets Vendor A was
|
|
consistently faster than Lucene. For example a
|
|
single query might take vendor A 32 thousands of a
|
|
second and Lucene 64 thousands of a second. Both
|
|
times are however well within acceptable response
|
|
times for our application.
|
|
</p>
|
|
<p>
|
|
For simple queries with large result sets Vendor A was
|
|
consistently slower than Lucene. For example a
|
|
single query might take vendor A 300 thousands of a
|
|
second and Lucene 200 thousands of a second.
|
|
For more complex queries of the form (term1 or term2
|
|
or term3) AND (term4 or term5 or term6) AND (term7 or
|
|
term8) the results were more divergent. For
|
|
queries with small result sets Vendor A generally had
|
|
very short response times and sometimes Lucene had
|
|
significantly larger response times. For example
|
|
Vendor A might take 16 thousands of a second and
|
|
Lucene might take 156. I do not consider it to be
|
|
the case that Lucene's response time grew unexpectedly
|
|
but rather that Vendor A appeared to be taking
|
|
advantage of an optimization which Lucene didn't have.
|
|
(I believe there's been discussions on the dev
|
|
mailing list on complex queries of this sort.)
|
|
</p>
|
|
<p>
|
|
Index Size:<br />
|
|
For our test data the size of both indexes grew
|
|
linearly with the number of documents. Note that
|
|
these sizes are compact sizes, not maximum size during
|
|
index loading. The numbers below are from running du
|
|
-k in the directory containing the index data. The
|
|
larger number's below for Vendor A may be because it
|
|
supports additional functionality not available in
|
|
Lucene. I think it's the constant rate of growth
|
|
rather than the absolute amount which is more
|
|
important.
|
|
</p>
|
|
<pre>
|
|
50K documents
|
|
Lucene 45516 K
|
|
A 63921
|
|
200K
|
|
Lucene 171565
|
|
A 228370
|
|
400K
|
|
Lucene 345717
|
|
A 457843
|
|
600K
|
|
Lucene 511338
|
|
A 684913
|
|
</pre>
|
|
<p>
|
|
Indexing Times:<br />
|
|
These times are for reading the documents from our
|
|
database, processing them, inserting them into the
|
|
document search product and index compacting. Our
|
|
data has a large number of fields/attributes. For
|
|
this test I restricted Lucene to 24 attributes to
|
|
reduce the number of files created. Doing this I was
|
|
able to specify a merge width for Lucene of 60. I
|
|
found in general that Lucene indexing performance to
|
|
be very sensitive to changes in the merge width.
|
|
Note also that our application does a full compaction
|
|
after inserting every 20,000 documents. These times
|
|
are just within our acceptable limits but we are
|
|
interested in alternatives to increase Lucene's
|
|
performance in this area.
|
|
</p>
|
|
<p>
|
|
<pre>
|
|
600K documents
|
|
Lucene 81 minutes
|
|
A 34 minutes
|
|
</pre>
|
|
</p>
|
|
<p>
|
|
(I don't have accurate results for all sizes on this
|
|
measure but believe that the indexing time for both
|
|
solutions grew essentially linearly with size. The
|
|
time to compact the index generally grew with index
|
|
size but it's a small percent of overall time at these
|
|
sizes.)
|
|
</p>
|
|
<ul>
|
|
<p>
|
|
<b>Hardware Environment</b><br />
|
|
<li><i>Dedicated machine for indexing</i>: yes</li>
|
|
<li><i>CPU</i>: Dell Pentium 4 CPU 2.00Ghz, 1cpu</li>
|
|
<li><i>RAM</i>: 1 GB Memory</li>
|
|
<li><i>Drive configuration</i>: Fujitsu MAM3367MP SCSI </li>
|
|
</p>
|
|
<p>
|
|
<b>Software environment</b><br />
|
|
<li><i>Java Version</i>: 1.4.2_02</li>
|
|
<li><i>Java VM</i>: JDK</li>
|
|
<li><i>OS Version</i>: Windows XP </li>
|
|
<li><i>Location of index</i>: local</li>
|
|
</p>
|
|
<p>
|
|
<b>Lucene indexing variables</b><br />
|
|
<li><i>Number of source documents</i>: 600,000</li>
|
|
<li><i>Total filesize of source documents</i>: from database</li>
|
|
<li><i>Average filesize of source documents</i>: from database</li>
|
|
<li><i>Source documents storage location</i>: from database</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>: small variation on WhitespaceAnalyzer</li>
|
|
<li><i>Number of fields per document</i>: 24</li>
|
|
<li><i>Type of fields</i>: A1 keyword, 1 big unindexed, rest are unstored and a mix of tokenized/untokenized</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>: 600,000 documents in 81 minutes (du -k = 511338)</li>
|
|
<li><i>Time taken / 1000 docs indexed</i>: 123 documents/second</li>
|
|
<li><i>Memory consumption</i>: -ms256m -mx512m -Xss4m -XX:MaxPermSize=512M</li>
|
|
</p>
|
|
<p>
|
|
<b>Notes</b><br />
|
|
<p>
|
|
<li>merge width of 60</li>
|
|
<li>did a compact every 20,000 documents</li>
|
|
</p>
|
|
</p>
|
|
</ul>
|
|
</blockquote>
|
|
</td></tr>
|
|
<tr><td><br/></td></tr>
|
|
</table>
|
|
</blockquote>
|
|
</p>
|
|
</td></tr>
|
|
<tr><td><br/></td></tr>
|
|
</table>
|
|
</td>
|
|
</tr>
|
|
|
|
<!-- FOOTER -->
|
|
<tr><td colspan="2">
|
|
<hr noshade="" size="1"/>
|
|
</td></tr>
|
|
<tr><td colspan="2">
|
|
<div align="center"><font color="#525D76" size="-1"><em>
|
|
Copyright © 1999-2004, The Apache Software Foundation
|
|
</em></font></div>
|
|
</td></tr>
|
|
</table>
|
|
</body>
|
|
</html>
|
|
<!-- end the processing -->
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