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| <p>Druid and Spark are complementary solutions as Druid can be used to accelerate OLAP queries in Spark.</p> |
| <p>Spark is a general cluster computing framework initially designed around the concept of Resilient Distributed Datasets (RDDs). |
| RDDs enable data reuse by persisting intermediate results |
| in memory and enable Spark to provide fast computations for iterative algorithms. |
| This is especially beneficial for certain work flows such as machine |
| learning, where the same operation may be applied over and over |
| again until some result is converged upon. The generality of Spark makes it very suitable as an engine to process (clean or transform) data. |
| Although Spark provides the ability to query data through Spark SQL, much like Hadoop, the query latencies are not specifically targeted to be interactive (sub-second).</p> |
| <p>Druid's focus is on extremely low latency queries, and is ideal for powering applications used by thousands of users, and where each query must |
| return fast enough such that users can interactively explore through data. Druid fully indexes all data, and can act as a middle layer between Spark and your application. |
| One typical setup seen in production is to process data in Spark, and load the processed data into Druid for faster access.</p> |
| <p>For more information about using Druid and Spark together, including benchmarks of the two systems, please see:</p> |
| <p><a href="https://www.linkedin.com/pulse/combining-druid-spark-interactive-flexible-analytics-scale-butani">https://www.linkedin.com/pulse/combining-druid-spark-interactive-flexible-analytics-scale-butani</a></p> |
| </span></div></article></div><div class="docs-prevnext"><a class="docs-prev button" href="/docs/0.20.0/comparisons/druid-vs-redshift.html"><span class="arrow-prev">← </span><span>Apache Druid vs Redshift</span></a><a class="docs-next button" href="/docs/0.20.0/comparisons/druid-vs-sql-on-hadoop.html"><span>Apache Druid vs SQL-on-Hadoop</span><span class="arrow-next"> →</span></a></div></div></div><nav class="onPageNav"></nav></div><footer class="nav-footer druid-footer" id="footer"><div class="container"><div class="text-center"><p><a href="/technology">Technology</a> · <a href="/use-cases">Use Cases</a> · <a href="/druid-powered">Powered by Druid</a> · <a href="/docs/0.20.0/latest">Docs</a> · <a href="/community/">Community</a> · <a href="/downloads.html">Download</a> · <a href="/faq">FAQ</a></p></div><div class="text-center"><a title="Join the user group" href="https://groups.google.com/forum/#!forum/druid-user" target="_blank"><span class="fa fa-comments"></span></a> · <a title="Follow Druid" href="https://twitter.com/druidio" target="_blank"><span class="fab fa-twitter"></span></a> · <a title="Download via Apache" href="https://www.apache.org/dyn/closer.cgi?path=/incubator/druid/{{ site.druid_versions[0].versions[0].version }}/apache-druid-{{ site.druid_versions[0].versions[0].version }}-bin.tar.gz" target="_blank"><span class="fas fa-feather"></span></a> · <a title="GitHub" href="https://github.com/apache/druid" target="_blank"><span class="fab fa-github"></span></a></div><div class="text-center license">Copyright © 2019 <a href="https://www.apache.org/" target="_blank">Apache Software Foundation</a>.<br/>Except where otherwise noted, licensed under <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA 4.0</a>.<br/>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></footer></div><script type="text/javascript" src="https://cdn.jsdelivr.net/docsearch.js/1/docsearch.min.js"></script><script> |
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