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| <h2>Spark Release 0.5.1</h2> |
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| <p>Spark 0.5.1 is a maintenance release that adds several important bug fixes and usability features. You can download it as a <a href="http://github.com/downloads/mesos/spark/spark-0.5.1.tgz">tar.gz file</a>.</p> |
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| <h3>Maven Publishing</h3> |
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| <p>Spark is now available in Maven Central, making it easier to link into your programs without having to build it as a JAR. Use the following Maven identifiers to add it to a project:</p> |
| <ul> |
| <li>groupId: org.spark-project</li> |
| <li>artifactId: spark-core_2.9.2</li> |
| <li>version: 0.5.1</li> |
| </ul> |
| |
| <h3>Scala 2.9.2</h3> |
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| <p>Spark now builds against Scala 2.9.2 by default.</p> |
| |
| <h3>Improved Accumulators</h3> |
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| <p>The new Accumulable class generalizes Accumulators for the case when the type being accumulated is not the same as the types of elements being added (e.g. you wish to accumulate a collection, such as a Set, by adding individual elements). This interface is also more efficient in avoiding the creation of temporary objects. (Contributed by Imran Rashid.)</p> |
| |
| <h3>Bug Fixes</h3> |
| |
| <ul> |
| <li>Spark's algorithm for estimating the sizes of objects (in order to manage memory correctly) has been improved |
| to handle JVMs with 32- vs 64-bit pointers and to measure objects more accurately. (Contributed by Shivaram Venkataraman.)</li> |
| <li>Improved algorithms for taking random samples out of datasets to avoid biases that could occur in the previous ones. (Suggested by Henry Milner.)</li> |
| <li>Improved load balancing across nodes in sort operations.</li> |
| <li>Fixed a shuffle bug that could cause reduce tasks to fail to receive a map task's full output.</li> |
| <li>Fixed a bug with locating custom KryoSerializers.</li> |
| <li>Reduced memory consumption of <tt>saveAsObjectFile</tt> when objects are large.</li> |
| </ul> |
| |
| <h3>EC2 Improvements</h3> |
| |
| <p>Spark’s EC2 launch script now configures Spark’s memory limit automatically based on the machine’s available RAM.</p> |
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| <li><a href="/news/spark-3-4-3-released.html">Spark 3.4.3 released</a> |
| <span class="small">(Apr 18, 2024)</span></li> |
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| <li><a href="/news/spark-3-5-1-released.html">Spark 3.5.1 released</a> |
| <span class="small">(Feb 23, 2024)</span></li> |
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| <li><a href="/news/spark-3-3-4-released.html">Spark 3.3.4 released</a> |
| <span class="small">(Dec 16, 2023)</span></li> |
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| <li><a href="/news/spark-3-4-2-released.html">Spark 3.4.2 released</a> |
| <span class="small">(Nov 30, 2023)</span></li> |
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