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aria-label="Breadcrumbs"><ul class="breadcrumbs" itemscope="" itemtype="https://schema.org/BreadcrumbList"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Operations</span><meta itemprop="position" content="1"></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Performance tuning</span><meta itemprop="position" content="2"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Segment size optimization</span><meta itemprop="position" content="3"></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Segment size optimization</h1></header><p>In Apache Druid, it&#x27;s important to optimize the segment size because</p><ol><li>Druid stores data in segments. If you&#x27;re using the <a href="/docs/latest/ingestion/rollup">best-effort roll-up</a> mode,
increasing the segment size might introduce further aggregation which reduces the dataSource size.</li><li>When a query is submitted, that query is distributed to all Historicals and realtime tasks
which hold the input segments of the query. Each process and task picks a thread from its own processing thread pool
to process a single segment. If segment sizes are too large, data might not be well distributed between data
servers, decreasing the degree of parallelism possible during query processing.
At the other extreme where segment sizes are too small, the scheduling
overhead of processing a larger number of segments per query can reduce
performance, as the threads that process each segment compete for the fixed
slots of the processing pool.</li></ol><p>It would be best if you can optimize the segment size at ingestion time, but sometimes it&#x27;s not easy
especially when it comes to stream ingestion because the amount of data ingested might vary over time. In this case,
you can create segments with a sub-optimized size first and optimize them later using <a href="/docs/latest/data-management/compaction">compaction</a>.</p><p>You may need to consider the followings to optimize your segments.</p><ul><li>Number of rows per segment: it&#x27;s generally recommended for each segment to have around 5 million rows.
This setting is usually <em>more</em> important than the below &quot;segment byte size&quot;.
This is because Druid uses a single thread to process each segment,
and thus this setting can directly control how many rows each thread processes,
which in turn means how well the query execution is parallelized.</li><li>Segment byte size: it&#x27;s recommended to set 300 ~ 700MB. If this value
doesn&#x27;t match with the &quot;number of rows per segment&quot;, please consider optimizing
number of rows per segment rather than this value.</li></ul><div class="theme-admonition theme-admonition-info alert alert--info admonition_LlT9"><div class="admonitionHeading_tbUL"><span class="admonitionIcon_kALy"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M7 2.3c3.14 0 5.7 2.56 5.7 5.7s-2.56 5.7-5.7 5.7A5.71 5.71 0 0 1 1.3 8c0-3.14 2.56-5.7 5.7-5.7zM7 1C3.14 1 0 4.14 0 8s3.14 7 7 7 7-3.14 7-7-3.14-7-7-7zm1 3H6v5h2V4zm0 6H6v2h2v-2z"></path></svg></span>info</div><div class="admonitionContent_S0QG"><p> The above recommendation works in general, but the optimal setting can
vary based on your workload. For example, if most of your queries
are heavy and take a long time to process each row, you may want to make
segments smaller so that the query processing can be more parallelized.
If you still see some performance issue after optimizing segment size,
you may need to find the optimal settings for your workload.</p></div></div><p>There might be several ways to check if the compaction is necessary. One way
is using the <a href="/docs/latest/querying/sql-metadata-tables#system-schema">System Schema</a>. The
system schema provides several tables about the current system status including the <code>segments</code> table.
By running the below query, you can get the average number of rows and average size for published segments.</p><div class="language-sql codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#bfc7d5;--prism-background-color:#292d3e"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-sql codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#bfc7d5"><span class="token keyword" style="font-style:italic">SELECT</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token string" style="color:rgb(195, 232, 141)">&quot;start&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token string" style="color:rgb(195, 232, 141)">&quot;end&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  version</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token function" style="color:rgb(130, 170, 255)">COUNT</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token operator" style="color:rgb(137, 221, 255)">*</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> num_segments</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token function" style="color:rgb(130, 170, 255)">AVG</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">&quot;num_rows&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> avg_num_rows</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token function" style="color:rgb(130, 170, 255)">SUM</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">&quot;num_rows&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> total_num_rows</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token function" style="color:rgb(130, 170, 255)">AVG</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">&quot;size&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> avg_size</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  </span><span class="token function" style="color:rgb(130, 170, 255)">SUM</span><span class="token punctuation" style="color:rgb(199, 146, 234)">(</span><span class="token string" style="color:rgb(195, 232, 141)">&quot;size&quot;</span><span class="token punctuation" style="color:rgb(199, 146, 234)">)</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">AS</span><span class="token plain"> total_size</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">FROM</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  sys</span><span class="token punctuation" style="color:rgb(199, 146, 234)">.</span><span class="token plain">segments A</span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">WHERE</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  datasource </span><span class="token operator" style="color:rgb(137, 221, 255)">=</span><span class="token plain"> </span><span class="token string" style="color:rgb(195, 232, 141)">&#x27;your_dataSource&#x27;</span><span class="token plain"> </span><span class="token operator" style="color:rgb(137, 221, 255)">AND</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain">  is_published </span><span class="token operator" style="color:rgb(137, 221, 255)">=</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">GROUP</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">BY</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">2</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">3</span><span class="token plain"></span><br></span><span class="token-line" style="color:#bfc7d5"><span class="token plain"></span><span class="token keyword" style="font-style:italic">ORDER</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">BY</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">1</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">2</span><span class="token punctuation" style="color:rgb(199, 146, 234)">,</span><span class="token plain"> </span><span class="token number" style="color:rgb(247, 140, 108)">3</span><span class="token plain"> </span><span class="token keyword" style="font-style:italic">DESC</span><span class="token punctuation" style="color:rgb(199, 146, 234)">;</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="Copy code to clipboard" title="Copy" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>Please note that the query result might include overshadowed segments.
In this case, you may want to see only rows of the max version per interval (pair of <code>start</code> and <code>end</code>).</p><p>Once you find your segments need compaction, you can consider the below two options:</p><ul><li>Turning on the <a href="/docs/latest/design/coordinator#automatic-compaction">automatic compaction of Coordinators</a>.
The Coordinator periodically submits <a href="/docs/latest/ingestion/tasks#compact">compaction tasks</a> to re-index small segments.
To enable the automatic compaction, you need to configure it for each dataSource via Coordinator&#x27;s dynamic configuration.
For more information, see <a href="/docs/latest/data-management/automatic-compaction">Automatic compaction</a>.</li><li>Running periodic Hadoop batch ingestion jobs and using a <code>dataSource</code>
inputSpec to read from the segments generated by the Kafka indexing tasks. This might be helpful if you want to compact a lot of segments in parallel.
Details on how to do this can be found on the <a href="/docs/latest/data-management/update">Updating existing data</a> section
of the data management page.</li></ul><h2 class="anchor anchorWithStickyNavbar_LWe7" id="learn-more">Learn more<a href="#learn-more" class="hash-link" aria-label="Direct link to Learn more" title="Direct link to Learn more">​</a></h2><ul><li>For an overview of compaction and how to submit a manual compaction task, see <a href="/docs/latest/data-management/compaction">Compaction</a>.</li><li>To learn how to enable and configure automatic compaction, see <a href="/docs/latest/data-management/automatic-compaction">Automatic compaction</a>.</li></ul></div></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/docs/latest/operations/basic-cluster-tuning"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Basic cluster tuning</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/docs/latest/operations/mixed-workloads"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Mixed workloads</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#learn-more" class="table-of-contents__link toc-highlight">Learn more</a></li></ul></div></div></div></div></main></div></div><footer class="footer"><div class="container container-fluid"><div class="footer__bottom text--center"><div class="margin-bottom--sm"><img src="/img/favicon.png" class="themedImage_ToTc themedImage--light_HNdA footer__logo"><img src="/img/favicon.png" class="themedImage_ToTc themedImage--dark_i4oU footer__logo"></div><div class="footer__copyright">Copyright © 2023 Apache Software Foundation. Except where otherwise noted, licensed under CC BY-SA 4.0. Apache Druid, Druid, and the Druid logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.</div></div></div></footer></div>
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