diff options
Diffstat (limited to 'site/releases')
-rw-r--r-- | site/releases/spark-release-0-3.html | 2 | ||||
-rw-r--r-- | site/releases/spark-release-0-5-0.html | 8 | ||||
-rw-r--r-- | site/releases/spark-release-0-5-1.html | 2 | ||||
-rw-r--r-- | site/releases/spark-release-0-6-0.html | 6 | ||||
-rw-r--r-- | site/releases/spark-release-0-7-0.html | 4 | ||||
-rw-r--r-- | site/releases/spark-release-0-8-0.html | 138 | ||||
-rw-r--r-- | site/releases/spark-release-0-8-1.html | 86 | ||||
-rw-r--r-- | site/releases/spark-release-0-9-0.html | 162 | ||||
-rw-r--r-- | site/releases/spark-release-0-9-1.html | 8 | ||||
-rw-r--r-- | site/releases/spark-release-1-0-0.html | 238 |
10 files changed, 327 insertions, 327 deletions
diff --git a/site/releases/spark-release-0-3.html b/site/releases/spark-release-0-3.html index f4e8081e0..410991b3e 100644 --- a/site/releases/spark-release-0-3.html +++ b/site/releases/spark-release-0-3.html @@ -176,7 +176,7 @@ <h3>Native Types for SequenceFiles</h3> -<p>In working with SequenceFiles, which store objects that implement Hadoop’s Writable interface, Spark will now let you use native types for certain common Writable types, like IntWritable and Text. For example:</p> +<p>In working with SequenceFiles, which store objects that implement Hadoop’s Writable interface, Spark will now let you use native types for certain common Writable types, like IntWritable and Text. For example:</p> <div class="code"> <span class="comment">// Will read a SequenceFile of (IntWritable, Text)</span><br /> diff --git a/site/releases/spark-release-0-5-0.html b/site/releases/spark-release-0-5-0.html index 0852db1fd..58a9b3ec5 100644 --- a/site/releases/spark-release-0-5-0.html +++ b/site/releases/spark-release-0-5-0.html @@ -164,10 +164,10 @@ <h3>Mesos 0.9 Support</h3> -<p>This release runs on <a href="http://www.mesosproject.org/">Apache Mesos 0.9</a>, the first Apache Incubator release of Mesos, which contains significant usability and stability improvements. Most notable are better memory accounting for applications with long-term memory use, easier access of old jobs’ traces and logs (by keeping a history of executed tasks on the web UI), and simpler installation.</p> +<p>This release runs on <a href="http://www.mesosproject.org/">Apache Mesos 0.9</a>, the first Apache Incubator release of Mesos, which contains significant usability and stability improvements. Most notable are better memory accounting for applications with long-term memory use, easier access of old jobs’ traces and logs (by keeping a history of executed tasks on the web UI), and simpler installation.</p> <h3>Performance Improvements</h3> -<p>Spark’s scheduling is more communication-efficient when sending out operations on RDDs with large lineage graphs. In addition, the cache replacement policy has been improved to more smartly replace data when an RDD does not fit in the cache, shuffles are more efficient, and the serializer used for shipping closures is now configurable, making it possible to use faster libraries than Java serialization there.</p> +<p>Spark’s scheduling is more communication-efficient when sending out operations on RDDs with large lineage graphs. In addition, the cache replacement policy has been improved to more smartly replace data when an RDD does not fit in the cache, shuffles are more efficient, and the serializer used for shipping closures is now configurable, making it possible to use faster libraries than Java serialization there.</p> <h3>Debug Improvements</h3> @@ -179,11 +179,11 @@ <h3>EC2 Launch Script Improvements</h3> -<p>Spark’s EC2 launch scripts are now included in the main package, and have the ability to discover and use the latest Spark AMI automatically instead of launching a hardcoded machine image ID.</p> +<p>Spark’s EC2 launch scripts are now included in the main package, and have the ability to discover and use the latest Spark AMI automatically instead of launching a hardcoded machine image ID.</p> <h3>New Hadoop API Support</h3> -<p>You can now use Spark to read and write data to storage formats in the new <tt>org.apache.mapreduce</tt> packages (the “new Hadoop” API). In addition, this release fixes an issue caused by a HDFS initialization bug in some recent versions of HDFS.</p> +<p>You can now use Spark to read and write data to storage formats in the new <tt>org.apache.mapreduce</tt> packages (the “new Hadoop” API). In addition, this release fixes an issue caused by a HDFS initialization bug in some recent versions of HDFS.</p> <p> diff --git a/site/releases/spark-release-0-5-1.html b/site/releases/spark-release-0-5-1.html index 64d594846..864e066ef 100644 --- a/site/releases/spark-release-0-5-1.html +++ b/site/releases/spark-release-0-5-1.html @@ -193,7 +193,7 @@ <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> +<p>Spark’s EC2 launch script now configures Spark’s memory limit automatically based on the machine’s available RAM.</p> <p> diff --git a/site/releases/spark-release-0-6-0.html b/site/releases/spark-release-0-6-0.html index c764d7d98..08a1cbbe9 100644 --- a/site/releases/spark-release-0-6-0.html +++ b/site/releases/spark-release-0-6-0.html @@ -172,11 +172,11 @@ <h3>Java API</h3> -<p>Java programmers can now use Spark through a new <a href="/docs/0.6.0/java-programming-guide.html">Java API layer</a>. This layer makes available all of Spark’s features, including parallel transformations, distributed datasets, broadcast variables, and accumulators, in a Java-friendly manner.</p> +<p>Java programmers can now use Spark through a new <a href="/docs/0.6.0/java-programming-guide.html">Java API layer</a>. This layer makes available all of Spark’s features, including parallel transformations, distributed datasets, broadcast variables, and accumulators, in a Java-friendly manner.</p> <h3>Expanded Documentation</h3> -<p>Spark’s <a href="/docs/0.6.0/">documentation</a> has been expanded with a new <a href="/docs/0.6.0/quick-start.html">quick start guide</a>, additional deployment instructions, configuration guide, tuning guide, and improved <a href="/docs/0.6.0/api/core">Scaladoc</a> API documentation.</p> +<p>Spark’s <a href="/docs/0.6.0/">documentation</a> has been expanded with a new <a href="/docs/0.6.0/quick-start.html">quick start guide</a>, additional deployment instructions, configuration guide, tuning guide, and improved <a href="/docs/0.6.0/api/core">Scaladoc</a> API documentation.</p> <h3>Engine Changes</h3> @@ -199,7 +199,7 @@ <h3>Enhanced Debugging</h3> -<p>Spark’s log now prints which operation in your program each RDD and job described in your logs belongs to, making it easier to tie back to which parts of your code experience problems.</p> +<p>Spark’s log now prints which operation in your program each RDD and job described in your logs belongs to, making it easier to tie back to which parts of your code experience problems.</p> <h3>Maven Artifacts</h3> diff --git a/site/releases/spark-release-0-7-0.html b/site/releases/spark-release-0-7-0.html index 243b33ac9..619fe1125 100644 --- a/site/releases/spark-release-0-7-0.html +++ b/site/releases/spark-release-0-7-0.html @@ -186,7 +186,7 @@ <h3>New Operations</h3> -<p>This release adds several RDD transformations, including <tt>keys</tt>, <tt>values</tt>, <tt>keyBy</tt>, <tt>subtract</tt>, <tt>coalesce</tt>, <tt>zip</tt>. It also adds <tt>SparkContext.hadoopConfiguration</tt> to allow programs to configure Hadoop input/output settings globally across operations. Finally, it adds the <tt>RDD.toDebugString()</tt> method, which can be used to print an RDD’s lineage graph for troubleshooting.</p> +<p>This release adds several RDD transformations, including <tt>keys</tt>, <tt>values</tt>, <tt>keyBy</tt>, <tt>subtract</tt>, <tt>coalesce</tt>, <tt>zip</tt>. It also adds <tt>SparkContext.hadoopConfiguration</tt> to allow programs to configure Hadoop input/output settings globally across operations. Finally, it adds the <tt>RDD.toDebugString()</tt> method, which can be used to print an RDD’s lineage graph for troubleshooting.</p> <h3>EC2 Improvements</h3> @@ -223,7 +223,7 @@ <h3>Credits</h3> -<p>Spark 0.7 was the work of many contributors from Berkeley and outside—in total, 31 different contributors, of which 20 were from outside Berkeley. Here are the people who contributed, along with areas they worked on:</p> +<p>Spark 0.7 was the work of many contributors from Berkeley and outside—in total, 31 different contributors, of which 20 were from outside Berkeley. Here are the people who contributed, along with areas they worked on:</p> <ul> <li>Mikhail Bautin -- Maven build</li> diff --git a/site/releases/spark-release-0-8-0.html b/site/releases/spark-release-0-8-0.html index 665f2c22b..c64261455 100644 --- a/site/releases/spark-release-0-8-0.html +++ b/site/releases/spark-release-0-8-0.html @@ -204,13 +204,13 @@ <li>The examples build has been isolated from the core build, substantially reducing the potential for dependency conflicts.</li> <li>The Spark Streaming Twitter API has been updated to use OAuth authentication instead of the deprecated username/password authentication in Spark 0.7.0.</li> <li>Several new example jobs have been added, including PageRank implementations in Java, Scala and Python, examples for accessing HBase and Cassandra, and MLlib examples.</li> - <li>Support for running on Mesos has been improved – now you can deploy a Spark assembly JAR as part of the Mesos job, instead of having Spark pre-installed on each machine. The default Mesos version has also been updated to 0.13.</li> + <li>Support for running on Mesos has been improved – now you can deploy a Spark assembly JAR as part of the Mesos job, instead of having Spark pre-installed on each machine. The default Mesos version has also been updated to 0.13.</li> <li>This release includes various optimizations to PySpark and to the job scheduler.</li> </ul> <h3 id="compatibility">Compatibility</h3> <ul> - <li><strong>This release changes Spark’s package name to ‘org.apache.spark’</strong>, so those upgrading from Spark 0.7 will need to adjust their imports accordingly. In addition, we’ve moved the <code>RDD</code> class to the org.apache.spark.rdd package (it was previously in the top-level package). The Spark artifacts published through Maven have also changed to the new package name.</li> + <li><strong>This release changes Spark’s package name to ‘org.apache.spark’</strong>, so those upgrading from Spark 0.7 will need to adjust their imports accordingly. In addition, we’ve moved the <code>RDD</code> class to the org.apache.spark.rdd package (it was previously in the top-level package). The Spark artifacts published through Maven have also changed to the new package name.</li> <li>In the Java API, use of Scala’s <code>Option</code> class has been replaced with <code>Optional</code> from the Guava library.</li> <li>Linking against Spark for arbitrary Hadoop versions is now possible by specifying a dependency on <code>hadoop-client</code>, instead of rebuilding <code>spark-core</code> against your version of Hadoop. See the documentation <a href="http://spark.incubator.apache.org/docs/0.8.0/scala-programming-guide.html#linking-with-spark">here</a> for details.</li> <li>If you are building Spark, you’ll now need to run <code>sbt/sbt assembly</code> instead of <code>package</code>.</li> @@ -220,73 +220,73 @@ <p>Spark 0.8.0 was the result of the largest team of contributors yet. The following developers contributed to this release:</p> <ul> - <li>Andrew Ash – documentation, code cleanup and logging improvements</li> - <li>Mikhail Bautin – bug fix</li> - <li>Konstantin Boudnik – Maven build, bug fixes, and documentation</li> - <li>Ian Buss – sbt configuration improvement</li> - <li>Evan Chan – API improvement, bug fix, and documentation</li> - <li>Lian Cheng – bug fix</li> - <li>Tathagata Das – performance improvement in streaming receiver and streaming bug fix</li> - <li>Aaron Davidson – Python improvements, bug fix, and unit tests</li> - <li>Giovanni Delussu – coalesced RDD feature</li> - <li>Joseph E. Gonzalez – improvement to zipPartitions</li> - <li>Karen Feng – several improvements to web UI</li> - <li>Andy Feng – HDFS metrics</li> - <li>Ali Ghodsi – configuration improvements and locality-aware coalesce</li> - <li>Christoph Grothaus – bug fix</li> - <li>Thomas Graves – support for secure YARN cluster and various YARN-related improvements</li> - <li>Stephen Haberman – bug fix, documentation, and code cleanup</li> - <li>Mark Hamstra – bug fixes and Maven build</li> - <li>Benjamin Hindman – Mesos compatibility and documentation</li> - <li>Liang-Chi Hsieh – bug fixes in build and in YARN mode</li> - <li>Shane Huang – shuffle improvements, bug fix</li> - <li>Ethan Jewett – Spark/HBase example</li> - <li>Holden Karau – bug fix and EC2 improvement</li> - <li>Kody Koeniger – JDBV RDD implementation</li> - <li>Andy Konwinski – documentation</li> - <li>Jey Kottalam – PySpark optimizations, Hadoop agnostic build (lead), and bug fixes</li> - <li>Andrey Kouznetsov – Bug fix</li> - <li>S. Kumar – Spark Streaming example</li> - <li>Ryan LeCompte – topK method optimization and serialization improvements</li> - <li>Gavin Li – compression codecs and pipe support</li> - <li>Harold Lim – fair scheduler</li> - <li>Dmitriy Lyubimov – bug fix</li> - <li>Chris Mattmann – Apache mentor</li> - <li>David McCauley – JSON API improvement</li> - <li>Sean McNamara – added <code>takeOrdered</code> function, bug fixes, and a build fix</li> - <li>Mridul Muralidharan – YARN integration (lead) and scheduler improvements</li> - <li>Marc Mercer – improvements to UI json output</li> - <li>Christopher Nguyen – bug fixes</li> - <li>Erik van Oosten – example fix</li> - <li>Kay Ousterhout – fix for scheduler regression and bug fixes</li> - <li>Xinghao Pan – MLLib contributions</li> - <li>Hiral Patel – bug fix</li> - <li>James Phillpotts – updated Twitter API for Spark streaming</li> - <li>Nick Pentreath – scala pageRank example, bagel improvement, and several Java examples</li> - <li>Alexander Pivovarov – logging improvement and Maven build</li> - <li>Mike Potts – configuration improvement</li> - <li>Rohit Rai – Spark/Cassandra example</li> - <li>Imran Rashid – bug fixes and UI improvement</li> - <li>Charles Reiss – bug fixes, code cleanup, performance improvements</li> - <li>Josh Rosen – Python API improvements, Java API improvements, EC2 scripts and bug fixes</li> - <li>Henry Saputra – Apache mentor</li> - <li>Jerry Shao – bug fixes, metrics system</li> - <li>Prashant Sharma – documentation</li> - <li>Mingfei Shi – joblogger and bug fix</li> - <li>Andre Schumacher – several PySpark features</li> - <li>Ginger Smith – MLLib contribution</li> - <li>Evan Sparks – contributions to MLLib</li> - <li>Ram Sriharsha – bug fix and RDD removal feature</li> - <li>Ameet Talwalkar – MLlib contributions</li> - <li>Roman Tkalenko – code refactoring and cleanup</li> - <li>Chu Tong – Java PageRank algorithm and bug fix in bash scripts</li> - <li>Shivaram Venkataraman – bug fixes, contributions to MLLib, netty shuffle fixes, and Java API additions</li> - <li>Patrick Wendell – release manager, bug fixes, documentation, metrics system, and web UI</li> - <li>Andrew Xia – fair scheduler (lead), metrics system, and ui improvements</li> - <li>Reynold Xin – shuffle improvements, bug fixes, code refactoring, usability improvements, MLLib contributions</li> - <li>Matei Zaharia – MLLib contributions, documentation, examples, UI improvements, PySpark improvements, and bug fixes</li> - <li>Wu Zeming – bug fix in scheduler</li> - <li>Bill Zhao – log message improvement</li> + <li>Andrew Ash – documentation, code cleanup and logging improvements</li> + <li>Mikhail Bautin – bug fix</li> + <li>Konstantin Boudnik – Maven build, bug fixes, and documentation</li> + <li>Ian Buss – sbt configuration improvement</li> + <li>Evan Chan – API improvement, bug fix, and documentation</li> + <li>Lian Cheng – bug fix</li> + <li>Tathagata Das – performance improvement in streaming receiver and streaming bug fix</li> + <li>Aaron Davidson – Python improvements, bug fix, and unit tests</li> + <li>Giovanni Delussu – coalesced RDD feature</li> + <li>Joseph E. Gonzalez – improvement to zipPartitions</li> + <li>Karen Feng – several improvements to web UI</li> + <li>Andy Feng – HDFS metrics</li> + <li>Ali Ghodsi – configuration improvements and locality-aware coalesce</li> + <li>Christoph Grothaus – bug fix</li> + <li>Thomas Graves – support for secure YARN cluster and various YARN-related improvements</li> + <li>Stephen Haberman – bug fix, documentation, and code cleanup</li> + <li>Mark Hamstra – bug fixes and Maven build</li> + <li>Benjamin Hindman – Mesos compatibility and documentation</li> + <li>Liang-Chi Hsieh – bug fixes in build and in YARN mode</li> + <li>Shane Huang – shuffle improvements, bug fix</li> + <li>Ethan Jewett – Spark/HBase example</li> + <li>Holden Karau – bug fix and EC2 improvement</li> + <li>Kody Koeniger – JDBV RDD implementation</li> + <li>Andy Konwinski – documentation</li> + <li>Jey Kottalam – PySpark optimizations, Hadoop agnostic build (lead), and bug fixes</li> + <li>Andrey Kouznetsov – Bug fix</li> + <li>S. Kumar – Spark Streaming example</li> + <li>Ryan LeCompte – topK method optimization and serialization improvements</li> + <li>Gavin Li – compression codecs and pipe support</li> + <li>Harold Lim – fair scheduler</li> + <li>Dmitriy Lyubimov – bug fix</li> + <li>Chris Mattmann – Apache mentor</li> + <li>David McCauley – JSON API improvement</li> + <li>Sean McNamara – added <code>takeOrdered</code> function, bug fixes, and a build fix</li> + <li>Mridul Muralidharan – YARN integration (lead) and scheduler improvements</li> + <li>Marc Mercer – improvements to UI json output</li> + <li>Christopher Nguyen – bug fixes</li> + <li>Erik van Oosten – example fix</li> + <li>Kay Ousterhout – fix for scheduler regression and bug fixes</li> + <li>Xinghao Pan – MLLib contributions</li> + <li>Hiral Patel – bug fix</li> + <li>James Phillpotts – updated Twitter API for Spark streaming</li> + <li>Nick Pentreath – scala pageRank example, bagel improvement, and several Java examples</li> + <li>Alexander Pivovarov – logging improvement and Maven build</li> + <li>Mike Potts – configuration improvement</li> + <li>Rohit Rai – Spark/Cassandra example</li> + <li>Imran Rashid – bug fixes and UI improvement</li> + <li>Charles Reiss – bug fixes, code cleanup, performance improvements</li> + <li>Josh Rosen – Python API improvements, Java API improvements, EC2 scripts and bug fixes</li> + <li>Henry Saputra – Apache mentor</li> + <li>Jerry Shao – bug fixes, metrics system</li> + <li>Prashant Sharma – documentation</li> + <li>Mingfei Shi – joblogger and bug fix</li> + <li>Andre Schumacher – several PySpark features</li> + <li>Ginger Smith – MLLib contribution</li> + <li>Evan Sparks – contributions to MLLib</li> + <li>Ram Sriharsha – bug fix and RDD removal feature</li> + <li>Ameet Talwalkar – MLlib contributions</li> + <li>Roman Tkalenko – code refactoring and cleanup</li> + <li>Chu Tong – Java PageRank algorithm and bug fix in bash scripts</li> + <li>Shivaram Venkataraman – bug fixes, contributions to MLLib, netty shuffle fixes, and Java API additions</li> + <li>Patrick Wendell – release manager, bug fixes, documentation, metrics system, and web UI</li> + <li>Andrew Xia – fair scheduler (lead), metrics system, and ui improvements</li> + <li>Reynold Xin – shuffle improvements, bug fixes, code refactoring, usability improvements, MLLib contributions</li> + <li>Matei Zaharia – MLLib contributions, documentation, examples, UI improvements, PySpark improvements, and bug fixes</li> + <li>Wu Zeming – bug fix in scheduler</li> + <li>Bill Zhao – log message improvement</li> </ul> <p>Thanks to everyone who contributed! diff --git a/site/releases/spark-release-0-8-1.html b/site/releases/spark-release-0-8-1.html index 67e6cb7cf..5a09b6ede 100644 --- a/site/releases/spark-release-0-8-1.html +++ b/site/releases/spark-release-0-8-1.html @@ -163,7 +163,7 @@ <p>Apache Spark 0.8.1 is a maintenance and performance release for the Scala 2.9 version of Spark. It also adds several new features, such as standalone mode high availability, that will appear in Spark 0.9 but developers wanted to have in Scala 2.9. Contributions to 0.8.1 came from 41 developers.</p> <h3 id="yarn-22-support">YARN 2.2 Support</h3> -<p>Support has been added for running Spark on YARN 2.2 and newer. Due to a change in the YARN API between previous versions and 2.2+, this was not supported in Spark 0.8.0. See the <a href="/docs/0.8.1/running-on-yarn.html">YARN documentation</a> for specific instructions on how to build Spark for YARN 2.2+. We’ve also included a pre-compiled binary for YARN 2.2.</p> +<p>Support has been added for running Spark on YARN 2.2 and newer. Due to a change in the YARN API between previous versions and 2.2+, this was not supported in Spark 0.8.0. See the <a href="/docs/0.8.1/running-on-yarn.html">YARN documentation</a> for specific instructions on how to build Spark for YARN 2.2+. We’ve also included a pre-compiled binary for YARN 2.2.</p> <h3 id="high-availability-mode-for-standalone-cluster-manager">High Availability Mode for Standalone Cluster Manager</h3> <p>The standalone cluster manager now has a high availability (H/A) mode which can tolerate master failures. This is particularly useful for long-running applications such as streaming jobs and the shark server, where the scheduler master previously represented a single point of failure. Instructions for deploying H/A mode are included <a href="/docs/0.8.1/spark-standalone.html#high-availability">in the documentation</a>. The current implementation uses Zookeeper for coordination.</p> @@ -174,7 +174,7 @@ <ul> <li>Optimized hashtables for shuffle data - reduces memory and CPU consumption</li> <li>Efficient encoding for JobConfs - improves latency for stages reading large numbers of blocks from HDFS, S3, and HBase</li> - <li>Shuffle file consolidation (off by default) - reduces the number of files created in large shuffles for better filesystem performance. This change works best on filesystems newer than ext3 (we recommend ext4 or XFS), and it will be the default in Spark 0.9, but we’ve left it off by default for compatibility. We recommend users turn this on unless they are using ext3 by setting <code>spark.shuffle.consolidateFiles</code> to “true”.</li> + <li>Shuffle file consolidation (off by default) - reduces the number of files created in large shuffles for better filesystem performance. This change works best on filesystems newer than ext3 (we recommend ext4 or XFS), and it will be the default in Spark 0.9, but we’ve left it off by default for compatibility. We recommend users turn this on unless they are using ext3 by setting <code>spark.shuffle.consolidateFiles</code> to “true”.</li> <li>Torrent broadcast (off by default) - a faster broadcast implementation for large objects.</li> <li>Support for fetching large result sets - allows tasks to return large results without tuning Akka buffer sizes.</li> </ul> @@ -211,47 +211,47 @@ <h3 id="credits">Credits</h3> <ul> - <li>Michael Armbrust – build fix</li> - <li>Pierre Borckmans – typo fix in documentation</li> - <li>Evan Chan – <code>local://</code> scheme for dependency jars</li> - <li>Ewen Cheslack-Postava – <code>add</code> method for python accumulators, support for setting config properties in python</li> - <li>Mosharaf Chowdhury – optimized broadcast implementation</li> - <li>Frank Dai – documentation fix</li> - <li>Aaron Davidson – shuffle file consolidation, H/A mode for standalone scheduler, cleaned up representation of block IDs, several improvements and bug fixes</li> - <li>Tathagata Das – new streaming operators, fix for kafka concurrency bug</li> - <li>Ankur Dave – support for pausing spot clusters on EC2</li> - <li>Harvey Feng – optimization to JobConf broadcasts, bug fixes, YARN 2.2 build</li> - <li>Ali Ghodsi – YARN 2.2 build</li> - <li>Thomas Graves – Spark YARN integration including secure HDFS access over YARN</li> - <li>Li Guoqiang – fix for Maven build</li> - <li>Stephen Haberman – bug fix</li> - <li>Haidar Hadi – documentation fix</li> - <li>Nathan Howell – bug fix relating to YARN</li> - <li>Holden Karau – Java version of <code>mapPartitionsWithIndex</code></li> - <li>Du Li – bug fix in make-distrubion.sh</li> - <li>Raymond Liu – work on YARN 2.2 build</li> - <li>Xi Liu – bug fix and code clean-up</li> - <li>David McCauley – bug fix in standalone mode JSON output</li> - <li>Michael (wannabeast) – bug fix in memory store</li> - <li>Fabrizio Milo – typos in documentation, clean-up in DAGScheduler, typo in scaladoc</li> - <li>Mridul Muralidharan – fixes to metadata cleaner and speculative execution</li> - <li>Sundeep Narravula – build fix, bug fixes in scheduler and tests, code clean-up</li> - <li>Kay Ousterhout – optimized result fetching, new information in UI, scheduler clean-up and bug fixes</li> - <li>Nick Pentreath – implicit feedback variant of ALS algorithm</li> - <li>Imran Rashid – improvement to executor launch</li> - <li>Ahir Reddy – spark support for SIMR</li> - <li>Josh Rosen – memory use optimization, clean up of BlockManager code, Java and Python clean-up/fixes</li> - <li>Henry Saputra – build fix</li> - <li>Jerry Shao – refactoring of fair scheduler, support for running Spark as a specific user, bug fix</li> - <li>Mingfei Shi – documentation for JobLogger</li> - <li>Andre Schumacher – sortByKey in PySpark and associated changes</li> - <li>Karthik Tunga – bug fix in launch script</li> - <li>Patrick Wendell – <code>repartition</code> operator, shuffle write metrics, various fixes and release management</li> - <li>Neal Wiggins – import clean-up, documentation fixes</li> - <li>Andrew Xia – bug fix in UI</li> - <li>Reynold Xin – task killing, support for setting job properties in Spark shell, logging improvements, Kryo improvements, several bug fixes</li> - <li>Matei Zaharia – optimized hashmap for shuffle data, PySpark documentation, optimizations to Kryo serializer</li> - <li>Wu Zeming – bug fix in executors UI</li> + <li>Michael Armbrust – build fix</li> + <li>Pierre Borckmans – typo fix in documentation</li> + <li>Evan Chan – <code>local://</code> scheme for dependency jars</li> + <li>Ewen Cheslack-Postava – <code>add</code> method for python accumulators, support for setting config properties in python</li> + <li>Mosharaf Chowdhury – optimized broadcast implementation</li> + <li>Frank Dai – documentation fix</li> + <li>Aaron Davidson – shuffle file consolidation, H/A mode for standalone scheduler, cleaned up representation of block IDs, several improvements and bug fixes</li> + <li>Tathagata Das – new streaming operators, fix for kafka concurrency bug</li> + <li>Ankur Dave – support for pausing spot clusters on EC2</li> + <li>Harvey Feng – optimization to JobConf broadcasts, bug fixes, YARN 2.2 build</li> + <li>Ali Ghodsi – YARN 2.2 build</li> + <li>Thomas Graves – Spark YARN integration including secure HDFS access over YARN</li> + <li>Li Guoqiang – fix for Maven build</li> + <li>Stephen Haberman – bug fix</li> + <li>Haidar Hadi – documentation fix</li> + <li>Nathan Howell – bug fix relating to YARN</li> + <li>Holden Karau – Java version of <code>mapPartitionsWithIndex</code></li> + <li>Du Li – bug fix in make-distrubion.sh</li> + <li>Raymond Liu – work on YARN 2.2 build</li> + <li>Xi Liu – bug fix and code clean-up</li> + <li>David McCauley – bug fix in standalone mode JSON output</li> + <li>Michael (wannabeast) – bug fix in memory store</li> + <li>Fabrizio Milo – typos in documentation, clean-up in DAGScheduler, typo in scaladoc</li> + <li>Mridul Muralidharan – fixes to metadata cleaner and speculative execution</li> + <li>Sundeep Narravula – build fix, bug fixes in scheduler and tests, code clean-up</li> + <li>Kay Ousterhout – optimized result fetching, new information in UI, scheduler clean-up and bug fixes</li> + <li>Nick Pentreath – implicit feedback variant of ALS algorithm</li> + <li>Imran Rashid – improvement to executor launch</li> + <li>Ahir Reddy – spark support for SIMR</li> + <li>Josh Rosen – memory use optimization, clean up of BlockManager code, Java and Python clean-up/fixes</li> + <li>Henry Saputra – build fix</li> + <li>Jerry Shao – refactoring of fair scheduler, support for running Spark as a specific user, bug fix</li> + <li>Mingfei Shi – documentation for JobLogger</li> + <li>Andre Schumacher – sortByKey in PySpark and associated changes</li> + <li>Karthik Tunga – bug fix in launch script</li> + <li>Patrick Wendell – <code>repartition</code> operator, shuffle write metrics, various fixes and release management</li> + <li>Neal Wiggins – import clean-up, documentation fixes</li> + <li>Andrew Xia – bug fix in UI</li> + <li>Reynold Xin – task killing, support for setting job properties in Spark shell, logging improvements, Kryo improvements, several bug fixes</li> + <li>Matei Zaharia – optimized hashmap for shuffle data, PySpark documentation, optimizations to Kryo serializer</li> + <li>Wu Zeming – bug fix in executors UI</li> </ul> <p>Thanks to everyone who contributed!</p> diff --git a/site/releases/spark-release-0-9-0.html b/site/releases/spark-release-0-9-0.html index e39fcd9e3..1575efcc5 100644 --- a/site/releases/spark-release-0-9-0.html +++ b/site/releases/spark-release-0-9-0.html @@ -265,87 +265,87 @@ <p>The following developers contributed to this release:</p> <ul> - <li>Andrew Ash – documentation improvements</li> - <li>Pierre Borckmans – documentation fix</li> - <li>Russell Cardullo – graphite sink for metrics</li> - <li>Evan Chan – local:// URI feature</li> - <li>Vadim Chekan – bug fix</li> - <li>Lian Cheng – refactoring and code clean-up in several locations, bug fixes</li> - <li>Ewen Cheslack-Postava – Spark EC2 and PySpark improvements</li> - <li>Mosharaf Chowdhury – optimized broadcast</li> - <li>Dan Crankshaw – GraphX contributions</li> - <li>Haider Haidi – documentation fix</li> - <li>Frank Dai – Naive Bayes classifier in MLlib, documentation improvements</li> - <li>Tathagata Das – new operators, fixes, and improvements to Spark Streaming (lead)</li> - <li>Ankur Dave – GraphX contributions</li> - <li>Henry Davidge – warning for large tasks</li> - <li>Aaron Davidson – shuffle file consolidation, H/A mode for standalone scheduler, various improvements and fixes</li> - <li>Kyle Ellrott – GraphX contributions</li> - <li>Hossein Falaki – new statistical operators, Scala and Python examples in MLlib</li> - <li>Harvey Feng – hadoop file optimizations and YARN integration</li> - <li>Ali Ghodsi – support for SIMR</li> - <li>Joseph E. Gonzalez – GraphX contributions</li> - <li>Thomas Graves – fixes and improvements for YARN support (lead)</li> - <li>Rong Gu – documentation fix</li> - <li>Stephen Haberman – bug fixes</li> - <li>Walker Hamilton – bug fix</li> - <li>Mark Hamstra – scheduler improvements and fixes, build fixes</li> - <li>Damien Hardy – Debian build fix</li> - <li>Nathan Howell – sbt upgrade</li> - <li>Grace Huang – improvements to metrics code</li> - <li>Shane Huang – separation of admin and user scripts:</li> - <li>Prabeesh K – MQTT integration for Spark Streaming and code fix</li> - <li>Holden Karau – sbt build improvements and Java API extensions</li> - <li>KarthikTunga – bug fix</li> - <li>Grega Kespret – bug fix</li> - <li>Marek Kolodziej – optimized random number generator</li> - <li>Jey Kottalam – EC2 script improvements</li> - <li>Du Li – bug fixes</li> - <li>Haoyuan Li – tachyon support in EC2</li> - <li>LiGuoqiang – fixes to build and YARN integration</li> - <li>Raymond Liu – build improvement and various fixes for YARN support</li> - <li>George Loentiev – Maven build fixes</li> - <li>Akihiro Matsukawa – GraphX contributions</li> - <li>David McCauley – improvements to json endpoint</li> - <li>Mike – bug fixes</li> - <li>Fabrizio (Misto) Milo – bug fix</li> - <li>Mridul Muralidharan – speculation improvements, several bug fixes</li> - <li>Tor Myklebust – Python mllib bindings, instrumentation for task serailization</li> - <li>Sundeep Narravula – bug fix</li> - <li>Binh Nguyen – Java API improvements and version upgrades</li> - <li>Adam Novak – bug fix</li> - <li>Andrew Or – external sorting</li> - <li>Kay Ousterhout – several bug fixes and improvements to Spark scheduler</li> - <li>Sean Owen – style fixes</li> - <li>Nick Pentreath – ALS implicit feedback algorithm</li> - <li>Pillis – <code>Vector.random()</code> method</li> - <li>Imran Rashid – bug fix</li> - <li>Ahir Reddy – support for SIMR</li> - <li>Luca Rosellini – script loading for Scala shell</li> - <li>Josh Rosen – fixes, clean-up, and extensions to scala and Java API’s</li> - <li>Henry Saputra – style improvements and clean-up</li> - <li>Andre Schumacher – Python improvements and bug fixes</li> - <li>Jerry Shao – multi-user support, various fixes and improvements</li> - <li>Prashant Sharma – Scala 2.10 support, configuration system, several smaller fixes</li> - <li>Shiyun – style fix</li> - <li>Wangda Tan – UI improvement and bug fixes</li> - <li>Matthew Taylor – bug fix</li> - <li>Jyun-Fan Tsai – documentation fix</li> - <li>Takuya Ueshin – bug fix</li> - <li>Shivaram Venkataraman – sbt build optimization, EC2 improvements, Java and Python API</li> - <li>Jianping J Wang – GraphX contributions</li> - <li>Martin Weindel – build fix</li> - <li>Patrick Wendell – standalone driver submission, various fixes, release manager</li> - <li>Neal Wiggins – bug fix</li> - <li>Andrew Xia – bug fixes and code cleanup</li> - <li>Reynold Xin – GraphX contributions, task killing, various fixes, improvements and optimizations</li> - <li>Dong Yan – bug fix</li> - <li>Haitao Yao – bug fix</li> - <li>Xusen Yin – bug fix</li> - <li>Fengdong Yu – documentation fixes</li> - <li>Matei Zaharia – new configuration system, Python MLlib bindings, scheduler improvements, various fixes and optimizations</li> - <li>Wu Zeming – bug fix</li> - <li>Nan Zhu – documentation improvements</li> + <li>Andrew Ash – documentation improvements</li> + <li>Pierre Borckmans – documentation fix</li> + <li>Russell Cardullo – graphite sink for metrics</li> + <li>Evan Chan – local:// URI feature</li> + <li>Vadim Chekan – bug fix</li> + <li>Lian Cheng – refactoring and code clean-up in several locations, bug fixes</li> + <li>Ewen Cheslack-Postava – Spark EC2 and PySpark improvements</li> + <li>Mosharaf Chowdhury – optimized broadcast</li> + <li>Dan Crankshaw – GraphX contributions</li> + <li>Haider Haidi – documentation fix</li> + <li>Frank Dai – Naive Bayes classifier in MLlib, documentation improvements</li> + <li>Tathagata Das – new operators, fixes, and improvements to Spark Streaming (lead)</li> + <li>Ankur Dave – GraphX contributions</li> + <li>Henry Davidge – warning for large tasks</li> + <li>Aaron Davidson – shuffle file consolidation, H/A mode for standalone scheduler, various improvements and fixes</li> + <li>Kyle Ellrott – GraphX contributions</li> + <li>Hossein Falaki – new statistical operators, Scala and Python examples in MLlib</li> + <li>Harvey Feng – hadoop file optimizations and YARN integration</li> + <li>Ali Ghodsi – support for SIMR</li> + <li>Joseph E. Gonzalez – GraphX contributions</li> + <li>Thomas Graves – fixes and improvements for YARN support (lead)</li> + <li>Rong Gu – documentation fix</li> + <li>Stephen Haberman – bug fixes</li> + <li>Walker Hamilton – bug fix</li> + <li>Mark Hamstra – scheduler improvements and fixes, build fixes</li> + <li>Damien Hardy – Debian build fix</li> + <li>Nathan Howell – sbt upgrade</li> + <li>Grace Huang – improvements to metrics code</li> + <li>Shane Huang – separation of admin and user scripts:</li> + <li>Prabeesh K – MQTT integration for Spark Streaming and code fix</li> + <li>Holden Karau – sbt build improvements and Java API extensions</li> + <li>KarthikTunga – bug fix</li> + <li>Grega Kespret – bug fix</li> + <li>Marek Kolodziej – optimized random number generator</li> + <li>Jey Kottalam – EC2 script improvements</li> + <li>Du Li – bug fixes</li> + <li>Haoyuan Li – tachyon support in EC2</li> + <li>LiGuoqiang – fixes to build and YARN integration</li> + <li>Raymond Liu – build improvement and various fixes for YARN support</li> + <li>George Loentiev – Maven build fixes</li> + <li>Akihiro Matsukawa – GraphX contributions</li> + <li>David McCauley – improvements to json endpoint</li> + <li>Mike – bug fixes</li> + <li>Fabrizio (Misto) Milo – bug fix</li> + <li>Mridul Muralidharan – speculation improvements, several bug fixes</li> + <li>Tor Myklebust – Python mllib bindings, instrumentation for task serailization</li> + <li>Sundeep Narravula – bug fix</li> + <li>Binh Nguyen – Java API improvements and version upgrades</li> + <li>Adam Novak – bug fix</li> + <li>Andrew Or – external sorting</li> + <li>Kay Ousterhout – several bug fixes and improvements to Spark scheduler</li> + <li>Sean Owen – style fixes</li> + <li>Nick Pentreath – ALS implicit feedback algorithm</li> + <li>Pillis – <code>Vector.random()</code> method</li> + <li>Imran Rashid – bug fix</li> + <li>Ahir Reddy – support for SIMR</li> + <li>Luca Rosellini – script loading for Scala shell</li> + <li>Josh Rosen – fixes, clean-up, and extensions to scala and Java API’s</li> + <li>Henry Saputra – style improvements and clean-up</li> + <li>Andre Schumacher – Python improvements and bug fixes</li> + <li>Jerry Shao – multi-user support, various fixes and improvements</li> + <li>Prashant Sharma – Scala 2.10 support, configuration system, several smaller fixes</li> + <li>Shiyun – style fix</li> + <li>Wangda Tan – UI improvement and bug fixes</li> + <li>Matthew Taylor – bug fix</li> + <li>Jyun-Fan Tsai – documentation fix</li> + <li>Takuya Ueshin – bug fix</li> + <li>Shivaram Venkataraman – sbt build optimization, EC2 improvements, Java and Python API</li> + <li>Jianping J Wang – GraphX contributions</li> + <li>Martin Weindel – build fix</li> + <li>Patrick Wendell – standalone driver submission, various fixes, release manager</li> + <li>Neal Wiggins – bug fix</li> + <li>Andrew Xia – bug fixes and code cleanup</li> + <li>Reynold Xin – GraphX contributions, task killing, various fixes, improvements and optimizations</li> + <li>Dong Yan – bug fix</li> + <li>Haitao Yao – bug fix</li> + <li>Xusen Yin – bug fix</li> + <li>Fengdong Yu – documentation fixes</li> + <li>Matei Zaharia – new configuration system, Python MLlib bindings, scheduler improvements, various fixes and optimizations</li> + <li>Wu Zeming – bug fix</li> + <li>Nan Zhu – documentation improvements</li> </ul> <p><em>Thanks to everyone who contributed!</em></p> diff --git a/site/releases/spark-release-0-9-1.html b/site/releases/spark-release-0-9-1.html index 0160b0356..425b15c16 100644 --- a/site/releases/spark-release-0-9-1.html +++ b/site/releases/spark-release-0-9-1.html @@ -235,7 +235,7 @@ <li>Andrew Tulloch - Minor updates to MLLib</li> <li>Bijay Bisht - Fix for hadoop-client for Hadoop < 1.0.1 and for bug in Spark on Mesos + CDH4.5.0</li> <li>Bouke van der Bijl - Bug fix in Python depickling</li> - <li>Bryn Keller - Support for HBase’s TableOutputFormat</li> + <li>Bryn Keller - Support for HBase’s TableOutputFormat</li> <li>Chen Chao - Bug fix in spark-shell script, and improvements to streaming programming guide</li> <li>Christian Lundgren - Support for C3 EC2 instance type</li> <li>Diana Carroll - Improvements to PySpark programming guide</li> @@ -245,7 +245,7 @@ <li>jianghan - Bug fixes in Java examples</li> <li>Josh Rosen - Bug fix in PySpark string serialization and exception handling</li> <li>Jyotiska NK - Improvements to PySpark doc and examples</li> - <li>Kay Ousterhout - Multiple bug fixes in scheduler’s handling of task failures</li> + <li>Kay Ousterhout - Multiple bug fixes in scheduler’s handling of task failures</li> <li>Kousuke Saruta - Use of https to access github</li> <li>Mark Grover - Bug fix in distribution tar.gz</li> <li>Matei Zaharia - Bug fixes in handling of task failures due to NPE, and cleaning up of scheduler data structures </li> @@ -258,10 +258,10 @@ <li>Raymond Liu - Changed working directory in ZookeeperPersistenceEngine</li> <li>Reynold Xin - Improvements to docs and test infrastructure</li> <li>Sandy Ryza - Multiple important Yarn bug fixes and improvements</li> - <li>Sean Owen - Bug fixes and improvements for MLLib’s ALS</li> + <li>Sean Owen - Bug fixes and improvements for MLLib’s ALS</li> <li>Shixiong Zhu - Fixed thread-unsafe use of SimpleDateFormat</li> <li>shiyun.wxm - UI bug fix</li> - <li>Stevo Slavić - Bug fix in window’s run-example script</li> + <li>Stevo Slavić - Bug fix in window’s run-example script</li> <li>Tathagata Das - Improvements to streaming docs</li> <li>Tom Graves - Bug fixes in YARN deployment modes</li> <li>Xiangrui Meng - Improvements to ALS and GLM, and MLLib programming guide</li> diff --git a/site/releases/spark-release-1-0-0.html b/site/releases/spark-release-1-0-0.html index 22a3f534b..52e69271b 100644 --- a/site/releases/spark-release-1-0-0.html +++ b/site/releases/spark-release-1-0-0.html @@ -192,11 +192,11 @@ <p>Spark 1.0 adds support for Java 8 <a href="http://docs.oracle.com/javase/tutorial/java/javaOO/lambdaexpressions.html">new lambda syntax</a> in its Java bindings. Java 8 supports a concise syntax for writing anonymous functions, similar to the closure syntax in Scala and Python. This change requires small changes for users of the current Java API, which are noted in the documentation. Spark’s Python API has been extended to support several new functions. We’ve also included several stability improvements in the Python API, particularly for large datasets. PySpark now supports running on YARN as well.</p> <h3 id="documentation">Documentation</h3> -<p>Spark’s <a href="/docs/latest/programming-guide.html">programming guide</a> has been significantly expanded to centrally cover all supported languages and discuss more operators and aspects of the development life cycle. The <a href="/docs/latest/mllib-guide.html">MLlib guide</a> has also been expanded with significantly more detail and examples for each algorithm, while documents on configuration, YARN and Mesos have also been revamped.</p> +<p>Spark’s <a href="/docs/latest/programming-guide.html">programming guide</a> has been significantly expanded to centrally cover all supported languages and discuss more operators and aspects of the development life cycle. The <a href="/docs/latest/mllib-guide.html">MLlib guide</a> has also been expanded with significantly more detail and examples for each algorithm, while documents on configuration, YARN and Mesos have also been revamped.</p> <h3 id="smaller-changes">Smaller Changes</h3> <ul> - <li>PySpark now works with more Python versions than before – Python 2.6+ instead of 2.7+, and NumPy 1.4+ instead of 1.7+.</li> + <li>PySpark now works with more Python versions than before – Python 2.6+ instead of 2.7+, and NumPy 1.4+ instead of 1.7+.</li> <li>Spark has upgraded to Avro 1.7.6, adding support for Avro specific types.</li> <li>Internal instrumentation has been added to allow applications to monitor and instrument Spark jobs.</li> <li>Support for off-heap storage in Tachyon has been added via a special build target.</li> @@ -213,123 +213,123 @@ <p>The following developers contributed to this release:</p> <ul> - <li>Aaron Davidson – packaging and deployment improvements, several bug fixes, local[*] mode</li> - <li>Aaron Kimball – documentation improvements</li> - <li>Abhishek Kumar – Python configuration fixes</li> - <li>Ahir Reddy – PySpark build, fixes, and cancellation support</li> - <li>Allan Douglas R. de Oliveira – Improvements to spark-ec2 scripts</li> - <li>Andre Schumacher – Parquet support and optimizations</li> - <li>Andrew Ash – Mesos documentation and other doc improvements, bug fixes</li> - <li>Andrew Or – history server (lead), garbage collection (lead), spark-submit, PySpark and YARN improvements</li> - <li>Andrew Tulloch – MLlib contributions and code clean-up</li> - <li>Andy Konwinski – documentation fix</li> - <li>Anita Tailor – Cassandra example</li> - <li>Ankur Dave – GraphX (lead) optimizations, documentation, and usability</li> - <li>Archer Shao – bug fixes</li> - <li>Arun Ramakrishnan – improved random sampling</li> - <li>Baishuo – test improvements</li> - <li>Bernardo Gomez Palacio – spark-shell improvements and Mesos updates</li> - <li>Bharath Bhushan – bug fix</li> - <li>Bijay Bisht – bug fixes</li> - <li>Binh Nguyen – dependency fix</li> - <li>Bouke van der Bijl – fixes for PySpark on Mesos and other Mesos fixes</li> - <li>Bryn Keller – improvement to HBase support and unit tests</li> - <li>Chen Chao – documentation, bug fix, and code clean-up</li> - <li>Cheng Hao – performance and feature improvements in Spark SQL</li> - <li>Cheng Lian – column storage and other improvements in Spark SQL</li> - <li>Christian Lundgren – improvement to spark-ec2 scripts</li> - <li>DB Tsai – L-BGFS optimizer in MLlib, MLlib documentation and fixes</li> - <li>Dan McClary – Improvement to stats counter</li> - <li>Daniel Darabos – GraphX performance improvement</li> - <li>Davis Shepherd – bug fix</li> - <li>Diana Carroll – documentation and bug fix</li> - <li>Egor Pakhomov – local iterator for RDD’s</li> - <li>Emtiaz Ahmed – bug fix</li> - <li>Erik Selin – bug fix</li> - <li>Ethan Jewett – documentation improvement</li> - <li>Evan Chan – automatic clean-up of application data</li> - <li>Evan Sparks – MLlib optimizations and doc improvement</li> - <li>Frank Dai – code clean-up in MLlib</li> - <li>Guoquiang Li – build improvements and several bug fixes</li> - <li>Ghidireac – bug fix</li> - <li>Haoyuan Li – Tachyon storage level for RDD’s</li> - <li>Harvey Feng – spark-ec2 update</li> - <li>Henry Saputra – code clean-up</li> - <li>Henry Cook – Spark SQL improvements</li> - <li>Holden Karau – cross validation in MLlib, Python and core engine improvements</li> - <li>Ivan Wick – Mesos bug fix</li> - <li>Jey Kottalam – sbt build improvement</li> - <li>Jerry Shao – Spark metrics and Spark SQL improvements</li> - <li>Jiacheng Guo – bug fix</li> - <li>Jianghan – bug fix</li> - <li>Jianping J Wang – JBLAS support in MLlib</li> - <li>Joseph E. Gonzalez – GraphX improvements, fixes, and documentation</li> - <li>Josh Rosen – PySpark improvements and bug fixes</li> - <li>Jyotiska NK – documentation, test improvements, and bug fix</li> - <li>Kan Zhang – bug fixes in Spark core, SQL, and PySpark</li> - <li>Kay Ousterhout – bug fixes and code refactoring in scheduler</li> - <li>Kelvin Chu – automatic clean-up of application data</li> - <li>Kevin Mader – example fix</li> - <li>Koert Kuipers – code visibility fix</li> - <li>Kousuke Saruta – documentation and build fixes</li> - <li>Kyle Ellrott – improved memory usage for DISK_ONLY persistence</li> - <li>Larva Boy – approximate counts in Spark SQL</li> - <li>Madhu Siddalingaiah – ec2 fixes</li> - <li>Manish Amde – decision trees in MLlib</li> - <li>Marcelo Vanzin – improvements and fixes to YARN support, dependency clean-up</li> - <li>Mark Grover – build fixes</li> - <li>Mark Hamstra – build and dependency improvements, scheduler bug fixes</li> - <li>Margin Jaggi – MLlib documentation improvements</li> - <li>Matei Zaharia – Python versions of several MLlib algorithms, spark-submit improvements, bug fixes, and documentation improvements</li> - <li>Michael Armbrust – Spark SQL (lead), including schema support for RDD’s, catalyst optimizer, and Hive support</li> - <li>Mridul Muralidharan – code visibility changes and bug fixes</li> - <li>Nan Zhu – bug and stability fixes, code clean-up, documentation, and new features</li> - <li>Neville Li – bug fix</li> - <li>Nick Lanham – Tachyon bundling in distribution script</li> - <li>Nirmal Reddy – code clean-up</li> - <li>OuYang Jin – local mode and json improvements</li> - <li>Patrick Wendell – release manager, build improvements, bug fixes, and code clean-up</li> - <li>Petko Nikolov – new utility functions</li> - <li>Prabeesh K – typo fix</li> - <li>Prabin Banka – new PySpark API’s</li> - <li>Prashant Sharma – PySpark improvements, Java 8 lambda support, and build improvements</li> - <li>Punya Biswal – Java API improvements</li> - <li>Qiuzhuang Lian – bug fixes</li> - <li>Rahul Singhal – build improvements, bug fixes</li> - <li>Raymond Liu – YARN build fixes and UI improvements</li> - <li>Reynold Xin – bug fixes, internal changes, Spark SQL improvements, build fixes, and style improvements</li> - <li>Reza Zadeh – SVD implementation in MLlib and other MLlib contributions</li> - <li>Roman Pastukhov – clean-up of broadcast files</li> - <li>Rong Gu – Tachyon storage level for RDD’s</li> - <li>Sandeep Sing – several bug fixes, MLLib improvements and fixes to Spark examples</li> - <li>Sandy Ryza – spark-submit script and several YARN improvements</li> - <li>Saurabh Rawat – Java API improvements</li> - <li>Sean Owen – several build improvements, code clean-up, and MLlib fixes</li> - <li>Semih Salihoglu – GraphX improvements</li> - <li>Shaocun Tian – bug fix in MLlib</li> - <li>Shivaram Venkataraman – bug fixes</li> - <li>Shixiong Zhu – code style and correctness fixes</li> - <li>Shiyun Wxm – typo fix</li> - <li>Stevo Slavic – bug fix</li> - <li>Sumedh Mungee – documentation fix</li> - <li>Sundeep Narravula – “cancel” button in Spark UI</li> - <li>Takayu Ueshin – bug fixes and improvements to Spark SQL</li> - <li>Tathagata Das – web UI and other improvements to Spark Streaming (lead), bug fixes, state clean-up, and release manager</li> - <li>Timothy Chen – Spark SQL improvements</li> - <li>Ted Malaska – improved Flume support</li> - <li>Tom Graves – Hadoop security integration (lead) and YARN support</li> - <li>Tianshuo Deng – Bug fix</li> - <li>Tor Myklebust – improvements to ALS</li> - <li>Wangfei – Spark SQL docs</li> - <li>Wang Tao – code clean-up</li> - <li>William Bendon – JSON support changes and bug fixes</li> - <li>Xiangrui Meng – several improvements to MLlib (lead)</li> - <li>Xuan Nguyen – build fix</li> - <li>Xusen Yin – MLlib contributions and bug fix</li> - <li>Ye Xianjin – test fixes</li> - <li>Yinan Li – addFile improvement</li> - <li>Yin Hua – Spark SQL improvements</li> - <li>Zheng Peng – bug fixes</li> + <li>Aaron Davidson – packaging and deployment improvements, several bug fixes, local[*] mode</li> + <li>Aaron Kimball – documentation improvements</li> + <li>Abhishek Kumar – Python configuration fixes</li> + <li>Ahir Reddy – PySpark build, fixes, and cancellation support</li> + <li>Allan Douglas R. de Oliveira – Improvements to spark-ec2 scripts</li> + <li>Andre Schumacher – Parquet support and optimizations</li> + <li>Andrew Ash – Mesos documentation and other doc improvements, bug fixes</li> + <li>Andrew Or – history server (lead), garbage collection (lead), spark-submit, PySpark and YARN improvements</li> + <li>Andrew Tulloch – MLlib contributions and code clean-up</li> + <li>Andy Konwinski – documentation fix</li> + <li>Anita Tailor – Cassandra example</li> + <li>Ankur Dave – GraphX (lead) optimizations, documentation, and usability</li> + <li>Archer Shao – bug fixes</li> + <li>Arun Ramakrishnan – improved random sampling</li> + <li>Baishuo – test improvements</li> + <li>Bernardo Gomez Palacio – spark-shell improvements and Mesos updates</li> + <li>Bharath Bhushan – bug fix</li> + <li>Bijay Bisht – bug fixes</li> + <li>Binh Nguyen – dependency fix</li> + <li>Bouke van der Bijl – fixes for PySpark on Mesos and other Mesos fixes</li> + <li>Bryn Keller – improvement to HBase support and unit tests</li> + <li>Chen Chao – documentation, bug fix, and code clean-up</li> + <li>Cheng Hao – performance and feature improvements in Spark SQL</li> + <li>Cheng Lian – column storage and other improvements in Spark SQL</li> + <li>Christian Lundgren – improvement to spark-ec2 scripts</li> + <li>DB Tsai – L-BGFS optimizer in MLlib, MLlib documentation and fixes</li> + <li>Dan McClary – Improvement to stats counter</li> + <li>Daniel Darabos – GraphX performance improvement</li> + <li>Davis Shepherd – bug fix</li> + <li>Diana Carroll – documentation and bug fix</li> + <li>Egor Pakhomov – local iterator for RDD’s</li> + <li>Emtiaz Ahmed – bug fix</li> + <li>Erik Selin – bug fix</li> + <li>Ethan Jewett – documentation improvement</li> + <li>Evan Chan – automatic clean-up of application data</li> + <li>Evan Sparks – MLlib optimizations and doc improvement</li> + <li>Frank Dai – code clean-up in MLlib</li> + <li>Guoquiang Li – build improvements and several bug fixes</li> + <li>Ghidireac – bug fix</li> + <li>Haoyuan Li – Tachyon storage level for RDD’s</li> + <li>Harvey Feng – spark-ec2 update</li> + <li>Henry Saputra – code clean-up</li> + <li>Henry Cook – Spark SQL improvements</li> + <li>Holden Karau – cross validation in MLlib, Python and core engine improvements</li> + <li>Ivan Wick – Mesos bug fix</li> + <li>Jey Kottalam – sbt build improvement</li> + <li>Jerry Shao – Spark metrics and Spark SQL improvements</li> + <li>Jiacheng Guo – bug fix</li> + <li>Jianghan – bug fix</li> + <li>Jianping J Wang – JBLAS support in MLlib</li> + <li>Joseph E. Gonzalez – GraphX improvements, fixes, and documentation</li> + <li>Josh Rosen – PySpark improvements and bug fixes</li> + <li>Jyotiska NK – documentation, test improvements, and bug fix</li> + <li>Kan Zhang – bug fixes in Spark core, SQL, and PySpark</li> + <li>Kay Ousterhout – bug fixes and code refactoring in scheduler</li> + <li>Kelvin Chu – automatic clean-up of application data</li> + <li>Kevin Mader – example fix</li> + <li>Koert Kuipers – code visibility fix</li> + <li>Kousuke Saruta – documentation and build fixes</li> + <li>Kyle Ellrott – improved memory usage for DISK_ONLY persistence</li> + <li>Larva Boy – approximate counts in Spark SQL</li> + <li>Madhu Siddalingaiah – ec2 fixes</li> + <li>Manish Amde – decision trees in MLlib</li> + <li>Marcelo Vanzin – improvements and fixes to YARN support, dependency clean-up</li> + <li>Mark Grover – build fixes</li> + <li>Mark Hamstra – build and dependency improvements, scheduler bug fixes</li> + <li>Margin Jaggi – MLlib documentation improvements</li> + <li>Matei Zaharia – Python versions of several MLlib algorithms, spark-submit improvements, bug fixes, and documentation improvements</li> + <li>Michael Armbrust – Spark SQL (lead), including schema support for RDD’s, catalyst optimizer, and Hive support</li> + <li>Mridul Muralidharan – code visibility changes and bug fixes</li> + <li>Nan Zhu – bug and stability fixes, code clean-up, documentation, and new features</li> + <li>Neville Li – bug fix</li> + <li>Nick Lanham – Tachyon bundling in distribution script</li> + <li>Nirmal Reddy – code clean-up</li> + <li>OuYang Jin – local mode and json improvements</li> + <li>Patrick Wendell – release manager, build improvements, bug fixes, and code clean-up</li> + <li>Petko Nikolov – new utility functions</li> + <li>Prabeesh K – typo fix</li> + <li>Prabin Banka – new PySpark API’s</li> + <li>Prashant Sharma – PySpark improvements, Java 8 lambda support, and build improvements</li> + <li>Punya Biswal – Java API improvements</li> + <li>Qiuzhuang Lian – bug fixes</li> + <li>Rahul Singhal – build improvements, bug fixes</li> + <li>Raymond Liu – YARN build fixes and UI improvements</li> + <li>Reynold Xin – bug fixes, internal changes, Spark SQL improvements, build fixes, and style improvements</li> + <li>Reza Zadeh – SVD implementation in MLlib and other MLlib contributions</li> + <li>Roman Pastukhov – clean-up of broadcast files</li> + <li>Rong Gu – Tachyon storage level for RDD’s</li> + <li>Sandeep Sing – several bug fixes, MLLib improvements and fixes to Spark examples</li> + <li>Sandy Ryza – spark-submit script and several YARN improvements</li> + <li>Saurabh Rawat – Java API improvements</li> + <li>Sean Owen – several build improvements, code clean-up, and MLlib fixes</li> + <li>Semih Salihoglu – GraphX improvements</li> + <li>Shaocun Tian – bug fix in MLlib</li> + <li>Shivaram Venkataraman – bug fixes</li> + <li>Shixiong Zhu – code style and correctness fixes</li> + <li>Shiyun Wxm – typo fix</li> + <li>Stevo Slavic – bug fix</li> + <li>Sumedh Mungee – documentation fix</li> + <li>Sundeep Narravula – “cancel” button in Spark UI</li> + <li>Takayu Ueshin – bug fixes and improvements to Spark SQL</li> + <li>Tathagata Das – web UI and other improvements to Spark Streaming (lead), bug fixes, state clean-up, and release manager</li> + <li>Timothy Chen – Spark SQL improvements</li> + <li>Ted Malaska – improved Flume support</li> + <li>Tom Graves – Hadoop security integration (lead) and YARN support</li> + <li>Tianshuo Deng – Bug fix</li> + <li>Tor Myklebust – improvements to ALS</li> + <li>Wangfei – Spark SQL docs</li> + <li>Wang Tao – code clean-up</li> + <li>William Bendon – JSON support changes and bug fixes</li> + <li>Xiangrui Meng – several improvements to MLlib (lead)</li> + <li>Xuan Nguyen – build fix</li> + <li>Xusen Yin – MLlib contributions and bug fix</li> + <li>Ye Xianjin – test fixes</li> + <li>Yinan Li – addFile improvement</li> + <li>Yin Hua – Spark SQL improvements</li> + <li>Zheng Peng – bug fixes</li> </ul> <p><em>Thanks to everyone who contributed!</em></p> |