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Spark wins CloudSort Benchmark as the most efficient engine | Apache Spark
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<li><a href="/news/spark-wins-cloudsort-100tb-benchmark.html">Spark wins CloudSort Benchmark as the most efficient engine</a>
<span class="small">(Nov 15, 2016)</span></li>
<li><a href="/news/spark-2-0-2-released.html">Spark 2.0.2 released</a>
<span class="small">(Nov 14, 2016)</span></li>
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<span class="small">(Nov 07, 2016)</span></li>
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<span class="small">(Oct 03, 2016)</span></li>
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<h2>Spark wins CloudSort Benchmark as the most efficient engine</h2>
<p>We are proud to announce that Apache Spark won the <a href="http://sortbenchmark.org/">2016 CloudSort Benchmark</a> (both Daytona and Indy category). A joint team from Nanjing University, Alibaba Group, and Databricks Inc. entered the competition using NADSort, a distributed sorting program built on top of Spark, and set a new world record as the most cost-efficient way to sort 100TB of data.</p>
<p>They sorted 100TB of data using only $144 USD worth of public cloud resources, beating the previous record that cost $451 USD by the University of California, San Diego.</p>
<p>This adds to the 2014 GraySort record Spark won, and validates Spark as the most efficient data processing engine.</p>
<p>For more information, see the <a href="https://databricks.com/blog/2016/11/14/setting-new-world-record-apache-spark.html">Databricks blog article (in English)</a> written by Spark committer Reynold Xin, or the Nanjing University <a href="http://scit.nju.edu.cn/Item/1193.aspx">press release (in Chinese)</a>.</p>
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