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Spark Release 0.6.1 | Apache Spark
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<li><a href="/news/spark-1-6-2-released.html">Spark 1.6.2 released</a>
<span class="small">(Jun 25, 2016)</span></li>
<li><a href="/news/submit-talks-to-spark-summit-eu-2016.html">Call for Presentations for Spark Summit EU is Open</a>
<span class="small">(Jun 16, 2016)</span></li>
<li><a href="/news/spark-2.0.0-preview.html">Preview release of Spark 2.0</a>
<span class="small">(May 26, 2016)</span></li>
<li><a href="/news/spark-summit-june-2016-agenda-posted.html">Spark Summit (June 6, 2016, San Francisco) agenda posted</a>
<span class="small">(Apr 17, 2016)</span></li>
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<h2>Spark Release 0.6.1</h2>
<p>Spark 0.6.1 is a maintenance release that contains several important bug fixes and performance improvements. You can download it as a <a href="https://github.com/downloads/mesos/spark/spark-0.6.1-sources.tgz">source package</a> (2.4 MB tar.gz) or <a href="https://github.com/downloads/mesos/spark/spark-0.6.1-prebuilt.tgz">prebuilt package</a> (48 MB tar.gz).</p>
<p>The fixes and improvements in this version include:</p>
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<li>Fixed overly aggressive message timeouts that could cause workers to disconnect from the cluster</li>
<li>Fixed a bug in the standalone deploy mode that did not expose hostnames to scheduler, affecting HDFS locality</li>
<li>Improved connection reuse in shuffle, which can greatly speed up small shuffles (contributed by Reynold Xin)</li>
<li>Fixed some potential deadlocks in the block manager (contributed by Tathagata Das)</li>
<li>Fixed a bug getting IDs of failed hosts from Mesos (contributed by Imran Rashid)</li>
<li>Several EC2 script improvements, like better handling of spot instances (contributed by Josh Rosen)</li>
<li>Made the local IP address that Spark binds to customizable (contributed by Mikhail Bautin)</li>
<li>Support for Hadoop 2 distributions (contributed by Thomas Dudziak)</li>
<li>Support for locating Scala on Debian distributions (contributed by Thomas Dudziak)</li>
<li>Improved standalone cluster web UI to show more information about jobs</li>
<li>Added an option to spread out jobs over the standalone cluster instead of concentrating them on a small number of nodes (<code>spark.deploy.spreadOut</code>)</li>
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<p>We recommend that all Spark 0.6 users update to this maintenance release.</p>
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