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<h5>Latest News</h5>
<ul class="list-unstyled">
+ <li><a href="/news/spark-summit-2014-videos-posted.html">Spark Summit 2014 videos posted</a>
+ <span class="small">(Jul 18, 2014)</span></li>
+
<li><a href="/news/spark-1-0-1-released.html">Spark 1.0.1 released</a>
<span class="small">(Jul 11, 2014)</span></li>
@@ -133,9 +136,6 @@
<li><a href="/news/spark-1-0-0-released.html">Spark 1.0.0 released</a>
<span class="small">(May 30, 2014)</span></li>
- <li><a href="/news/spark-summit-agenda-posted.html">Spark Summit agenda posted</a>
- <span class="small">(May 11, 2014)</span></li>
-
</ul>
<p class="small" style="text-align: right;"><a href="/news/index.html">Archive</a></p>
</div>
@@ -160,8 +160,8 @@
<h2>Spark 1.0.0 released</h2>
-<p>We are happy to announce the availability of <a href="/releases/spark-release-1-0-0.html" title="Spark Release 1.0.0">Spark 1.0.0</a>! Spark 1.0.0 is the first in the 1.X line of releases, providing API stability for Spark&#8217;s core interfaces. It is Spark&#8217;s largest release ever, with contributions from 117 developers.
-This release expands Spark&#8217;s standard libraries, introducing a new SQL package (Spark SQL) that lets users integrate SQL queries into existing Spark workflows. MLlib, Spark&#8217;s machine learning library, is expanded with sparse vector support and several new algorithms. The GraphX and Streaming libraries also introduce new features and optimizations. Spark&#8217;s core engine adds support for secured YARN clusters, a unified tool for submitting Spark applications, and several performance and stability improvements.</p>
+<p>We are happy to announce the availability of <a href="/releases/spark-release-1-0-0.html" title="Spark Release 1.0.0">Spark 1.0.0</a>! Spark 1.0.0 is the first in the 1.X line of releases, providing API stability for Spark’s core interfaces. It is Spark’s largest release ever, with contributions from 117 developers.
+This release expands Spark’s standard libraries, introducing a new SQL package (Spark SQL) that lets users integrate SQL queries into existing Spark workflows. MLlib, Spark’s machine learning library, is expanded with sparse vector support and several new algorithms. The GraphX and Streaming libraries also introduce new features and optimizations. Spark’s core engine adds support for secured YARN clusters, a unified tool for submitting Spark applications, and several performance and stability improvements.</p>
<p>Visit the <a href="/releases/spark-release-1-0-0.html" title="Spark Release 1.0.0">release notes</a> to read about the new features, or <a href="/downloads.html">download</a> the release today.</p>