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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 itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item"><a class="breadcrumbs__link" itemprop="item" href="/docs/31.0.0/ingestion/"><span itemprop="name">Ingestion</span></a><meta itemprop="position" content="1"></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Ingestion concepts</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">Partitioning</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>Partitioning</h1></header><p>You can use segment partitioning and sorting within your Druid datasources to reduce the size of your data and increase performance.</p><p>One way to partition is to load data into separate datasources. This is a perfectly viable approach that works very well when the number of datasources does not lead to excessive per-datasource overheads.</p><p>This topic describes how to set up partitions within a single datasource. It does not cover how to use multiple datasources. See <a href="/docs/31.0.0/querying/multitenancy">Multitenancy considerations</a> for more details on splitting data into separate datasources and potential operational considerations.</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="time-chunk-partitioning">Time chunk partitioning<a href="#time-chunk-partitioning" class="hash-link" aria-label="Direct link to Time chunk partitioning" title="Direct link to Time chunk partitioning"></a></h2><p>Druid always partitions datasources by time into <em>time chunks</em>. Each time chunk contains one or more segments. This partitioning happens for all ingestion methods based on the <code>segmentGranularity</code> parameter in your ingestion spec <code>dataSchema</code> object.</p><p>Partitioning by time is important for two reasons:</p><ol><li>Queries that filter by <code>__time</code> (SQL) or <code>intervals</code> (native) are able to use time partitioning to prune the set of segments to consider.</li><li>Certain data management operations, such as overwriting and compacting existing data, acquire exclusive write locks on time partitions.</li><li>Each segment file is wholly contained within a time partition. Too-fine-grained partitioning may cause a large number |
| of small segments, which leads to poor performance.</li></ol><p>The most common choices to balance these considerations are <code>hour</code> and <code>day</code>. For streaming ingestion, <code>hour</code> is especially |
| common, because it allows compaction to follow ingestion with less of a time delay.</p><p>The following table describes how to configure time chunk partitioning.</p><table><thead><tr><th>Method</th><th>Configuration</th></tr></thead><tbody><tr><td><a href="/docs/31.0.0/multi-stage-query/">SQL</a></td><td><a href="/docs/31.0.0/multi-stage-query/concepts#partitioning"><code>PARTITIONED BY</code></a></td></tr><tr><td><a href="/docs/31.0.0/ingestion/kafka-ingestion">Kafka</a> or <a href="/docs/31.0.0/ingestion/kinesis-ingestion">Kinesis</a></td><td><code>segmentGranularity</code> inside the <a href="/docs/31.0.0/ingestion/ingestion-spec#granularityspec"><code>granularitySpec</code></a></td></tr><tr><td><a href="/docs/31.0.0/ingestion/native-batch">Native batch</a> or <a href="/docs/31.0.0/ingestion/hadoop">Hadoop</a></td><td><code>segmentGranularity</code> inside the <a href="/docs/31.0.0/ingestion/ingestion-spec#granularityspec"><code>granularitySpec</code></a></td></tr></tbody></table><h2 class="anchor anchorWithStickyNavbar_LWe7" id="secondary-partitioning">Secondary partitioning<a href="#secondary-partitioning" class="hash-link" aria-label="Direct link to Secondary partitioning" title="Direct link to Secondary partitioning"></a></h2><p>Druid further partitions each time chunk into immutable segments. Secondary partitioning on a particular dimension improves locality. This means that rows with the same value for that dimension are stored together, decreasing access time.</p><p>To achieve the best performance and smallest overall footprint, partition your data on a "natural" dimension that |
| you often use as a filter, or that achieves some alignment within your data. Such partitioning can improve compression |
| and query performance by significant multiples.</p><p>The following table describes how to configure secondary partitioning.</p><table><thead><tr><th>Method</th><th>Configuration</th></tr></thead><tbody><tr><td><a href="/docs/31.0.0/multi-stage-query/">SQL</a></td><td><a href="/docs/31.0.0/multi-stage-query/concepts#clustering"><code>CLUSTERED BY</code></a></td></tr><tr><td><a href="/docs/31.0.0/ingestion/kafka-ingestion">Kafka</a> or <a href="/docs/31.0.0/ingestion/kinesis-ingestion">Kinesis</a></td><td>Upstream partitioning defines how Druid partitions the datasource. You can also alter clustering using <a href="/docs/31.0.0/multi-stage-query/concepts#replace"><code>REPLACE</code></a> (with <code>CLUSTERED BY</code>) or <a href="/docs/31.0.0/data-management/compaction">compaction</a> after initial ingestion.</td></tr><tr><td><a href="/docs/31.0.0/ingestion/native-batch">Native batch</a> or <a href="/docs/31.0.0/ingestion/hadoop">Hadoop</a></td><td><a href="/docs/31.0.0/ingestion/native-batch#partitionsspec"><code>partitionsSpec</code></a> inside the <code>tuningConfig</code></td></tr></tbody></table><h2 class="anchor anchorWithStickyNavbar_LWe7" id="sorting">Sorting<a href="#sorting" class="hash-link" aria-label="Direct link to Sorting" title="Direct link to Sorting"></a></h2><p>Each segment is internally sorted to promote compression and locality.</p><p>Partitioning and sorting work well together. If you do have a "natural" partitioning dimension, consider placing it |
| first in your sort order as well. This way, Druid sorts rows within each segment by that column. This sorting configuration |
| frequently improves compression and performance more than using partitioning alone.</p><p>The following table describes how to configure sorting.</p><table><thead><tr><th>Method</th><th>Configuration</th></tr></thead><tbody><tr><td><a href="/docs/31.0.0/multi-stage-query/">SQL</a></td><td>Uses order of fields in <a href="/docs/31.0.0/multi-stage-query/concepts#clustering"><code>CLUSTERED BY</code></a> or <a href="/docs/31.0.0/multi-stage-query/reference#context"><code>segmentSortOrder</code></a> in the query context</td></tr><tr><td><a href="/docs/31.0.0/ingestion/kafka-ingestion">Kafka</a> or <a href="/docs/31.0.0/ingestion/kinesis-ingestion">Kinesis</a></td><td>Uses order of fields in <a href="/docs/31.0.0/ingestion/ingestion-spec#granularityspec"><code>dimensionsSpec</code></a></td></tr><tr><td><a href="/docs/31.0.0/ingestion/native-batch">Native batch</a> or <a href="/docs/31.0.0/ingestion/hadoop">Hadoop</a></td><td>Uses order of fields in <a href="/docs/31.0.0/ingestion/ingestion-spec#granularityspec"><code>dimensionsSpec</code></a></td></tr></tbody></table><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>Druid implicitly sorts rows within a segment by <code>__time</code> first before any <code>dimensions</code> or <code>CLUSTERED BY</code> fields, unless |
| you set <code>forceSegmentSortByTime</code> to <code>false</code> in your |
| <a href="/docs/31.0.0/multi-stage-query/reference#context-parameters">query context</a> (for SQL) or in your |
| <a href="/docs/31.0.0/ingestion/ingestion-spec#dimensionsspec"><code>dimensionsSpec</code></a> (for other ingestion forms).</p><p>Setting <code>forceSegmentSortByTime</code> to <code>false</code> is an experimental feature. Segments created with sort orders that |
| do not start with <code>__time</code> can only be read by Druid 31 or later. Additionally, at this time, certain queries are not |
| supported on such segments, including:</p><ul><li>Native queries with <code>granularity</code> other than <code>all</code>.</li><li>Native <code>scan</code> query with ascending or descending time order.</li><li>SQL queries that plan into an unsupported native query.</li></ul></div></div><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><p>See the following topics for more information:</p><ul><li><a href="/docs/31.0.0/ingestion/native-batch#partitionsspec"><code>partitionsSpec</code></a> for more detail on partitioning with Native Batch ingestion.</li><li><a href="/docs/31.0.0/data-management/update#reindex">Reindexing</a> and <a href="/docs/31.0.0/data-management/compaction">Compaction</a> for information on how to repartition existing data in Druid.</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/31.0.0/ingestion/rollup"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Rollup</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/docs/31.0.0/ingestion/tasks"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Task reference</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="#time-chunk-partitioning" class="table-of-contents__link toc-highlight">Time chunk partitioning</a></li><li><a href="#secondary-partitioning" class="table-of-contents__link toc-highlight">Secondary partitioning</a></li><li><a href="#sorting" class="table-of-contents__link toc-highlight">Sorting</a></li><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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