<h1>Welcome to the pg_reorg Project Home Page</h1>
<hr/>
</center>
<p>
pg_reorg can re-organize tables on a postgres database without any locks so that you can retrieve or update rows in tables being reorganized.
The module is developed to be a better alternative of CLUSTER and VACUUM FULL.
</p>
<p>
The pg_reorg project is a <ahref="http://www.postgresql.org">PostgreSQL</a> Community project that is a part of the <ahref="http://pgfoundry.org">pgFoundry</a>.
</p>
<p>
The pgFoundry page for the project is at <ahref="http://pgfoundry.org/projects/reorg">http://pgfoundry.org/projects/reorg</a>,
where you can find <ahref="http://pgfoundry.org/frs/?group_id=1000411">downloads</a>, documentation, bug reports, mailing lists, and a whole lot more.
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<div>
<ahref="index-ja.html">日本語のページはこちら。</a>
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<h2>Documentation</h2>
<p>
<ahref="pg_reorg.html">Documentations here</a>.
</p>
<h2>Execution time</h2>
<p>
Here is a comparison between pg_reorg and clusterdb.
Clusterdb is faster on not fragmented conditions, but pg_reorg is faster on fully fragmented conditions.
Since reorganization is needed only if tables are fragmented, pg_reorg should be faster than clusterdb.
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<center>
<divstyle="margin: 2em">
<imgsrc="result.png"/>
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<tableborder="1">
<caption>Configuration</caption>
<tr>
<th>Category</th>
<th>Item</th>
<th>Details</th>
</tr>
<tr>
<tdrowspan="3">Hardware</td>
<td>CPU</td>
<td>2 * Xeon 5160 3.00GHz (Dual core)</td>
</tr>
<tr>
<td>Memory</td>
<td>2GB</td>
</tr>
<tr>
<td>Storage</td>
<td>Ultra320 SCSI, 15000rpm (220GB)</td>
</tr>
<tr>
<tdrowspan="4">Software</td>
<td>OS</td>
<td>RHEL 5.2 (64bit) 2.6.18-92.el5</td>
</tr>
<tr>
<td>DB</td>
<td>PostgreSQL 8.3.3</td>
</tr>
<tr>
<td>pg_reorg</td>
<td>1.0.0</td>
</tr>
<tr>
<td>clusterdb</td>
<td>clusterdb (PostgreSQL) 8.3.3</td>
</tr>
<tr>
<tdrowspan="2">Data</td>
<td>Scheme</td>
<td><code><pre>CREATE TABLE tbl (
id bigserial PRIMARY KEY,
seqkey timestamp NOT NULL,
rndkey timestamp NOT NULL,
filler char(75) NOT NULL
);
CREATE INDEX idx_seq ON tbl (seqkey);
CREATE INDEX idx_rnd ON tbl (rndkey);</pre></code></td>
</tr>
<tr>
<td>Rows</td>
<td>16.5 M rows (2GB)</td>
</tr>
</table>
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