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| |
| <h1 id="segment-size-optimization">Segment Size Optimization</h1> |
| |
| <p>In Apache Druid (incubating), it's important to optimize the segment size because</p> |
| |
| <ol> |
| <li>Druid stores data in segments. If you're using the <a href="../design/index.html#roll-up-modes">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'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-optimzed size first and optimize them later.</p> |
| |
| <p>You may need to consider the followings to optimize your segments.</p> |
| |
| <ul> |
| <li>Number of rows per segment: it's generally recommended for each segment to have around 5 million rows. |
| This setting is usually <em>more</em> important than the below "segment byte size". |
| 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's recommended to set 300 ~ 700MB. If this value |
| doesn't match with the "number of rows per segment", please consider optimizing |
| number of rows per segment rather than this value.</li> |
| </ul> |
| |
| <div class="note"> |
| 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. |
| </div> |
| |
| <p>There might be several ways to check if the compaction is necessary. One way |
| is using the <a href="../querying/sql.html#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="highlight"><pre><code class="language-sql" data-lang="sql"><span></span><span class="k">SELECT</span> |
| <span class="ss">"start"</span><span class="p">,</span> |
| <span class="ss">"end"</span><span class="p">,</span> |
| <span class="k">version</span><span class="p">,</span> |
| <span class="k">COUNT</span><span class="p">(</span><span class="o">*</span><span class="p">)</span> <span class="k">AS</span> <span class="n">num_segments</span><span class="p">,</span> |
| <span class="k">AVG</span><span class="p">(</span><span class="ss">"num_rows"</span><span class="p">)</span> <span class="k">AS</span> <span class="n">avg_num_rows</span><span class="p">,</span> |
| <span class="k">SUM</span><span class="p">(</span><span class="ss">"num_rows"</span><span class="p">)</span> <span class="k">AS</span> <span class="n">total_num_rows</span><span class="p">,</span> |
| <span class="k">AVG</span><span class="p">(</span><span class="ss">"size"</span><span class="p">)</span> <span class="k">AS</span> <span class="n">avg_size</span><span class="p">,</span> |
| <span class="k">SUM</span><span class="p">(</span><span class="ss">"size"</span><span class="p">)</span> <span class="k">AS</span> <span class="n">total_size</span> |
| <span class="k">FROM</span> |
| <span class="n">sys</span><span class="p">.</span><span class="n">segments</span> <span class="n">A</span> |
| <span class="k">WHERE</span> |
| <span class="n">datasource</span> <span class="o">=</span> <span class="s1">'your_dataSource'</span> <span class="k">AND</span> |
| <span class="n">is_published</span> <span class="o">=</span> <span class="mi">1</span> |
| <span class="k">GROUP</span> <span class="k">BY</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span> |
| <span class="k">ORDER</span> <span class="k">BY</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span> <span class="k">DESC</span><span class="p">;</span> |
| </code></pre></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="../design/coordinator.html#compacting-segments">automatic compaction of Coordinators</a>. |
| The Coordinator periodically submits <a href="../ingestion/tasks.html#compaction-task">compaction tasks</a> to re-index small segments. |
| To enable the automatic compaction, you need to configure it for each dataSource via Coordinator's dynamic configuration. |
| See <a href="../operations/api-reference.html#compaction-configuration">Compaction Configuration API</a> |
| and <a href="../configuration/index.html#compaction-dynamic-configuration">Compaction Configuration</a> for details.</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 under <a href="../ingestion/update-existing-data.html">'Updating Existing Data'</a>.</li> |
| </ul> |
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