diff options
| author | Sean Owen <sowen@cloudera.com> | 2016-07-26 22:34:05 +0100 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-07-29 12:20:53 -0700 |
| commit | 7d3c47dd63fe3cb09a74505d860bcf5bc3967c6c (patch) | |
| tree | fd0c128b8a76bc7c1ae77dfdd4b53d122fc2a1d0 | |
| parent | 65ec30e24bc7f1f81b0767d11867c6611d28fc6f (diff) | |
| download | spark-website-7d3c47dd63fe3cb09a74505d860bcf5bc3967c6c.tar.gz spark-website-7d3c47dd63fe3cb09a74505d860bcf5bc3967c6c.tar.bz2 spark-website-7d3c47dd63fe3cb09a74505d860bcf5bc3967c6c.zip | |
Sync markdown with generated HTML according to what latest jekyll outputs; fix some markdown problems along the way
28 files changed, 110 insertions, 109 deletions
diff --git a/news/_posts/2015-05-15-one-month-to-spark-summit-2015.md b/news/_posts/2015-05-15-one-month-to-spark-summit-2015.md index f692ae4a4..8c0f35a99 100644 --- a/news/_posts/2015-05-15-one-month-to-spark-summit-2015.md +++ b/news/_posts/2015-05-15-one-month-to-spark-summit-2015.md @@ -1,7 +1,7 @@ --- layout: post title: One month to Spark Summit 2015 in San Francisco -date: 2015-05-16 00:00:10 +date: 2015-05-15 00:00:10 categories: - News tags: [] diff --git a/news/_posts/2015-05-15-spark-summit-europe.md b/news/_posts/2015-05-15-spark-summit-europe.md index c74eb5c2e..a30bcad2d 100644 --- a/news/_posts/2015-05-15-spark-summit-europe.md +++ b/news/_posts/2015-05-15-spark-summit-europe.md @@ -1,7 +1,7 @@ --- layout: post title: Announcing Spark Summit Europe -date: 2015-05-16 00:00:00 +date: 2015-05-15 00:00:00 categories: - News tags: [] diff --git a/releases/_posts/2013-02-07-spark-release-0-6-2.md b/releases/_posts/2013-02-07-spark-release-0-6-2.md index 0f983269e..07f57141c 100644 --- a/releases/_posts/2013-02-07-spark-release-0-6-2.md +++ b/releases/_posts/2013-02-07-spark-release-0-6-2.md @@ -1,15 +1,15 @@ ---- -layout: post -title: Spark Release 0.6.2 -categories: [] -tags: [] -status: publish -type: post -published: true -meta: - _edit_last: '4' - _wpas_done_all: '1' ---- +---
+layout: post
+title: Spark Release 0.6.2
+categories: []
+tags: []
+status: publish
+type: post
+published: true
+meta:
+ _edit_last: '4'
+ _wpas_done_all: '1'
+---
Spark 0.6.2 is a maintenance release that contains several bug fixes and usability improvements. You can download it as a <a href="http://spark-project.org/download/spark-0.6.2-sources.tgz">source package</a> (2.5 MB tar.gz) or <a href="http://spark-project.org/download/spark-0.6.2-prebuilt.tgz">prebuilt package</a> (48 MB tar.gz).
We recommend that all Spark 0.6 users update to this maintenance release.
@@ -21,7 +21,7 @@ The fixes and improvements in this version include: <li>A connection reuse bug fix that improves shuffle performance</li>
<li>Support for launching a cluster across multiple availability zones in the EC2 scripts</li>
<li>Support for deleting security groups when an EC2 cluster is terminated</li>
- <li>Improved memory configuration for the standalone deploy cluster daemons: instead of using <code>SPARK_MEM</code> for their memory, which often led people to give them much more memory than they intended, they now use a separate variable, <code>SPARK_DAEMON_MEMORY</code>, with a reasonable default of 512 MB
+ <li>Improved memory configuration for the standalone deploy cluster daemons: instead of using <code>SPARK_MEM</code> for their memory, which often led people to give them much more memory than they intended, they now use a separate variable, <code>SPARK_DAEMON_MEMORY</code>, with a reasonable default of 512 MB</li>
<li>Fixes to the Windows run scripts for Spark</li>
<li>Better detection of a machine's external IP address</li>
<li>Several small optimizations and bug fixes</li>
@@ -40,4 +40,4 @@ In total, eleven people contributed to this release: <li>Lee Moon Soo (bug fix)</li>
<li>Patrick Wendell (bugs, docs)</li>
<li>Matei Zaharia (fault recovery, UI, docs, bug fixes)</li>
-</ul> +</ul>
diff --git a/research.md b/research.md index 6d77f1eaf..41841a1c7 100644 --- a/research.md +++ b/research.md @@ -44,6 +44,7 @@ Spark offers an abstraction called <a href="http://www.cs.berkeley.edu/~matei/pa </li> <li> <a href="https://amplab.cs.berkeley.edu/wp-content/uploads/2014/02/graphx.pdf">GraphX: Unifying Data-Parallel and Graph-Parallel Analytics</a>. Reynold S. Xin, Daniel Crankshaw, Ankur Dave, Joseph E. Gonzalez, Michael J. Franklin, Ion Stoica. <em>OSDI 2014</em>. October 2014. + </li> <li> <a href="http://people.csail.mit.edu/matei/papers/2013/sosp_spark_streaming.pdf">Discretized Streams: Fault-Tolerant Streaming Computation at Scale</a>. Matei Zaharia, Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, Ion Stoica. <em>SOSP 2013</em>. November 2013. </li> diff --git a/site/documentation.html b/site/documentation.html index acf7f464e..4290b04bf 100644 --- a/site/documentation.html +++ b/site/documentation.html @@ -253,12 +253,13 @@ </ul> <h4><a name="meetup-videos"></a>Meetup Talk Videos</h4> -<p>In addition to the videos listed below, you can also view <a href="http://www.meetup.com/spark-users/files/">all slides from Bay Area meetups here</a>. +<p>In addition to the videos listed below, you can also view <a href="http://www.meetup.com/spark-users/files/">all slides from Bay Area meetups here</a>.</p> <style type="text/css"> .video-meta-info { font-size: 0.95em; } -</style></p> +</style> + <ul> <li><a href="http://www.youtube.com/watch?v=NUQ-8to2XAk&list=PL-x35fyliRwiP3YteXbnhk0QGOtYLBT3a">Spark 1.0 and Beyond</a> (<a href="http://files.meetup.com/3138542/Spark%201.0%20Meetup.ppt">slides</a>) <span class="video-meta-info">by Patrick Wendell, at Cisco in San Jose, 2014-04-23</span></li> diff --git a/site/news/index.html b/site/news/index.html index e97c7bf35..9f7582047 100644 --- a/site/news/index.html +++ b/site/news/index.html @@ -385,7 +385,7 @@ The Summit will contain <a href="https://spark-summit.org/2015/schedule/">presen <h3 class="entry-title"><a href="/news/spark-summit-east-2015-videos-posted.html">Spark Summit East 2015 Videos Posted</a></h3> <div class="entry-date">April 20, 2015</div> </header> - <div class="entry-content"><p>The videos and slides for Spark Summit East 2015 are now all <a href="http://spark-summit.org/east/2015">available online</a>. Watch them to get the latest news from the Spark community as well as use cases and applications built on top. </p> + <div class="entry-content"><p>The videos and slides for Spark Summit East 2015 are now all <a href="http://spark-summit.org/east/2015">available online</a>. Watch them to get the latest news from the Spark community as well as use cases and applications built on top.</p> </div> </article> @@ -395,7 +395,7 @@ The Summit will contain <a href="https://spark-summit.org/2015/schedule/">presen <h3 class="entry-title"><a href="/news/spark-1-2-2-released.html">Spark 1.2.2 and 1.3.1 released</a></h3> <div class="entry-date">April 17, 2015</div> </header> - <div class="entry-content"><p>We are happy to announce the availability of <a href="/releases/spark-release-1-2-2.html" title="Spark Release 1.2.2">Spark 1.2.2</a> and <a href="/releases/spark-release-1-3-1.html" title="Spark Release 1.3.1">Spark 1.3.1</a>! These are both maintenance releases that collectively feature the work of more than 90 developers. </p> + <div class="entry-content"><p>We are happy to announce the availability of <a href="/releases/spark-release-1-2-2.html" title="Spark Release 1.2.2">Spark 1.2.2</a> and <a href="/releases/spark-release-1-3-1.html" title="Spark Release 1.3.1">Spark 1.3.1</a>! These are both maintenance releases that collectively feature the work of more than 90 developers.</p> </div> </article> @@ -507,7 +507,7 @@ The Summit will contain <a href="https://spark-summit.org/2015/schedule/">presen </header> <div class="entry-content"><p>We are happy to announce the availability of <a href="/releases/spark-release-0-9-2.html" title="Spark Release 0.9.2"> Spark 0.9.2</a>! Apache Spark 0.9.2 is a maintenance release with bug fixes. We recommend all 0.9.x users to upgrade to this stable release. -Contributions to this release came from 28 developers. </p> +Contributions to this release came from 28 developers.</p> </div> </article> @@ -578,7 +578,7 @@ about the latest happenings in Spark.</p> <div class="entry-content"><p>We are happy to announce the availability of <a href="/releases/spark-release-0-9-1.html" title="Spark Release 0.9.1"> Spark 0.9.1</a>! Apache Spark 0.9.1 is a maintenance release with bug fixes, performance improvements, better stability with YARN and improved parity of the Scala and Python API. We recommend all 0.9.0 users to upgrade to this stable release. -Contributions to this release came from 37 developers. </p> +Contributions to this release came from 37 developers.</p> </div> </article> @@ -833,7 +833,7 @@ Over 450 Spark developers and enthusiasts from 13 countries and more than 180 co <li><a href="http://data-informed.com/spark-an-open-source-engine-for-iterative-data-mining/">DataInformed</a> interviewed two Spark users and wrote about their applications in anomaly detection, predictive analytics and data mining.</li> </ul> -<p>In other news, there will be a full day of tutorials on Spark and Shark at the <a href="http://strataconf.com/strata2013">O’Reilly Strata conference</a> in February. They include a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27438">introduction to Spark, Shark and BDAS</a> Tuesday morning, and a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27440">hands-on exercise session</a>. </p> +<p>In other news, there will be a full day of tutorials on Spark and Shark at the <a href="http://strataconf.com/strata2013">O’Reilly Strata conference</a> in February. They include a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27438">introduction to Spark, Shark and BDAS</a> Tuesday morning, and a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27440">hands-on exercise session</a>.</p> </div> </article> diff --git a/site/news/spark-0-9-1-released.html b/site/news/spark-0-9-1-released.html index 08f036b61..366609d14 100644 --- a/site/news/spark-0-9-1-released.html +++ b/site/news/spark-0-9-1-released.html @@ -189,7 +189,7 @@ <p>We are happy to announce the availability of <a href="/releases/spark-release-0-9-1.html" title="Spark Release 0.9.1"> Spark 0.9.1</a>! Apache Spark 0.9.1 is a maintenance release with bug fixes, performance improvements, better stability with YARN and improved parity of the Scala and Python API. We recommend all 0.9.0 users to upgrade to this stable release. -Contributions to this release came from 37 developers. </p> +Contributions to this release came from 37 developers.</p> <p>Visit the <a href="/releases/spark-release-0-9-1.html" title="Spark Release 0.9.1">release notes</a> to read about the new features, or <a href="/downloads.html">download</a> the release today.</p> diff --git a/site/news/spark-0-9-2-released.html b/site/news/spark-0-9-2-released.html index 4e9a4984c..f2a125e99 100644 --- a/site/news/spark-0-9-2-released.html +++ b/site/news/spark-0-9-2-released.html @@ -188,7 +188,7 @@ <p>We are happy to announce the availability of <a href="/releases/spark-release-0-9-2.html" title="Spark Release 0.9.2"> Spark 0.9.2</a>! Apache Spark 0.9.2 is a maintenance release with bug fixes. We recommend all 0.9.x users to upgrade to this stable release. -Contributions to this release came from 28 developers. </p> +Contributions to this release came from 28 developers.</p> <p>Visit the <a href="/releases/spark-release-0-9-2.html" title="Spark Release 0.9.2">release notes</a> to read about the new features, or <a href="/downloads.html">download</a> the release today.</p> diff --git a/site/news/spark-1-1-0-released.html b/site/news/spark-1-1-0-released.html index 1eef3d78d..db596e40e 100644 --- a/site/news/spark-1-1-0-released.html +++ b/site/news/spark-1-1-0-released.html @@ -188,7 +188,7 @@ <p>We are happy to announce the availability of <a href="/releases/spark-release-1-1-0.html" title="Spark Release 1.1.0">Spark 1.1.0</a>! Spark 1.1.0 is the second release on the API-compatible 1.X line. It is Spark’s largest release ever, with contributions from 171 developers!</p> -<p>This release brings operational and performance improvements in Spark core including a new implementation of the Spark shuffle designed for very large scale workloads. Spark 1.1 adds significant extensions to the newest Spark modules, MLlib and Spark SQL. Spark SQL introduces a JDBC server, byte code generation for fast expression evaluation, a public types API, JSON support, and other features and optimizations. MLlib introduces a new statistics libary along with several new algorithms and optimizations. Spark 1.1 also builds out Spark’s Python support and adds new components to the Spark Streaming module. </p> +<p>This release brings operational and performance improvements in Spark core including a new implementation of the Spark shuffle designed for very large scale workloads. Spark 1.1 adds significant extensions to the newest Spark modules, MLlib and Spark SQL. Spark SQL introduces a JDBC server, byte code generation for fast expression evaluation, a public types API, JSON support, and other features and optimizations. MLlib introduces a new statistics libary along with several new algorithms and optimizations. Spark 1.1 also builds out Spark’s Python support and adds new components to the Spark Streaming module.</p> <p>Visit the <a href="/releases/spark-release-1-1-0.html" title="Spark Release 1.1.0">release notes</a> to read about the new features, or <a href="/downloads.html">download</a> the release today.</p> diff --git a/site/news/spark-1-2-2-released.html b/site/news/spark-1-2-2-released.html index fce0fb718..ca2742d16 100644 --- a/site/news/spark-1-2-2-released.html +++ b/site/news/spark-1-2-2-released.html @@ -186,7 +186,7 @@ <h2>Spark 1.2.2 and 1.3.1 released</h2> -<p>We are happy to announce the availability of <a href="/releases/spark-release-1-2-2.html" title="Spark Release 1.2.2">Spark 1.2.2</a> and <a href="/releases/spark-release-1-3-1.html" title="Spark Release 1.3.1">Spark 1.3.1</a>! These are both maintenance releases that collectively feature the work of more than 90 developers. </p> +<p>We are happy to announce the availability of <a href="/releases/spark-release-1-2-2.html" title="Spark Release 1.2.2">Spark 1.2.2</a> and <a href="/releases/spark-release-1-3-1.html" title="Spark Release 1.3.1">Spark 1.3.1</a>! These are both maintenance releases that collectively feature the work of more than 90 developers.</p> <p>To download either release, visit the <a href="/downloads.html">downloads</a> page.</p> diff --git a/site/news/spark-and-shark-in-the-news.html b/site/news/spark-and-shark-in-the-news.html index 330fb8d65..97c8e1ed3 100644 --- a/site/news/spark-and-shark-in-the-news.html +++ b/site/news/spark-and-shark-in-the-news.html @@ -196,7 +196,7 @@ <li><a href="http://data-informed.com/spark-an-open-source-engine-for-iterative-data-mining/">DataInformed</a> interviewed two Spark users and wrote about their applications in anomaly detection, predictive analytics and data mining.</li> </ul> -<p>In other news, there will be a full day of tutorials on Spark and Shark at the <a href="http://strataconf.com/strata2013">O’Reilly Strata conference</a> in February. They include a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27438">introduction to Spark, Shark and BDAS</a> Tuesday morning, and a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27440">hands-on exercise session</a>. </p> +<p>In other news, there will be a full day of tutorials on Spark and Shark at the <a href="http://strataconf.com/strata2013">O’Reilly Strata conference</a> in February. They include a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27438">introduction to Spark, Shark and BDAS</a> Tuesday morning, and a three-hour <a href="http://strataconf.com/strata2013/public/schedule/detail/27440">hands-on exercise session</a>.</p> <p> diff --git a/site/news/spark-summit-east-2015-videos-posted.html b/site/news/spark-summit-east-2015-videos-posted.html index 382530685..22de78966 100644 --- a/site/news/spark-summit-east-2015-videos-posted.html +++ b/site/news/spark-summit-east-2015-videos-posted.html @@ -186,7 +186,7 @@ <h2>Spark Summit East 2015 Videos Posted</h2> -<p>The videos and slides for Spark Summit East 2015 are now all <a href="http://spark-summit.org/east/2015">available online</a>. Watch them to get the latest news from the Spark community as well as use cases and applications built on top. </p> +<p>The videos and slides for Spark Summit East 2015 are now all <a href="http://spark-summit.org/east/2015">available online</a>. Watch them to get the latest news from the Spark community as well as use cases and applications built on top.</p> <p>If you like what you see, consider joining us at the <a href="http://spark-summit.org/2015/agenda">2015 Spark Summit</a> in San Francisco.</p> diff --git a/site/releases/spark-release-0-6-2.html b/site/releases/spark-release-0-6-2.html index 1a856675e..c5c0bd9d8 100644 --- a/site/releases/spark-release-0-6-2.html +++ b/site/releases/spark-release-0-6-2.html @@ -197,13 +197,13 @@ <li>A connection reuse bug fix that improves shuffle performance</li> <li>Support for launching a cluster across multiple availability zones in the EC2 scripts</li> <li>Support for deleting security groups when an EC2 cluster is terminated</li> - <li>Improved memory configuration for the standalone deploy cluster daemons: instead of using <code>SPARK_MEM</code> for their memory, which often led people to give them much more memory than they intended, they now use a separate variable, <code>SPARK_DAEMON_MEMORY</code>, with a reasonable default of 512 MB + <li>Improved memory configuration for the standalone deploy cluster daemons: instead of using <code>SPARK_MEM</code> for their memory, which often led people to give them much more memory than they intended, they now use a separate variable, <code>SPARK_DAEMON_MEMORY</code>, with a reasonable default of 512 MB</li> <li>Fixes to the Windows run scripts for Spark</li> <li>Better detection of a machine's external IP address</li> <li>Several small optimizations and bug fixes</li> +</ul> - -In total, eleven people contributed to this release: +<p>In total, eleven people contributed to this release:</p> <ul> <li>Stephen Haberman (bug fix)</li> <li>Shane Huang (shuffle fix)</li> @@ -217,7 +217,6 @@ In total, eleven people contributed to this release: <li>Patrick Wendell (bugs, docs)</li> <li>Matei Zaharia (fault recovery, UI, docs, bug fixes)</li> </ul> -</li></ul> <p> diff --git a/site/releases/spark-release-0-8-0.html b/site/releases/spark-release-0-8-0.html index ae67c9b10..b33e71f80 100644 --- a/site/releases/spark-release-0-8-0.html +++ b/site/releases/spark-release-0-8-0.html @@ -210,13 +210,13 @@ <p>Spark’s internal job scheduler has been refactored and extended to include more sophisticated scheduling policies. In particular, a <a href="http://spark.incubator.apache.org/docs/0.8.0/job-scheduling.html#scheduling-within-an-application">fair scheduler</a> implementation now allows multiple users to share an instance of Spark, which helps users running shorter jobs to achieve good performance, even when longer-running jobs are running in parallel. Support for topology-aware scheduling has been extended, including the ability to take into account rack locality and support for multiple executors on a single machine.</p> <h3 id="easier-deployment-and-linking">Easier Deployment and Linking</h3> -<p>User programs can now link to Spark no matter which Hadoop version they need, without having to publish a version of <code>spark-core</code> specifically for that Hadoop version. An explanation of how to link against different Hadoop versions is provided <a href="http://spark.incubator.apache.org/docs/0.8.0/scala-programming-guide.html#linking-with-spark">here</a>. </p> +<p>User programs can now link to Spark no matter which Hadoop version they need, without having to publish a version of <code>spark-core</code> specifically for that Hadoop version. An explanation of how to link against different Hadoop versions is provided <a href="http://spark.incubator.apache.org/docs/0.8.0/scala-programming-guide.html#linking-with-spark">here</a>.</p> <h3 id="expanded-ec2-capabilities">Expanded EC2 Capabilities</h3> <p>Spark’s EC2 scripts now support launching in any availability zone. Support has also been added for EC2 instance types which use the newer “HVM” architecture. This includes the cluster compute (cc1/cc2) family of instance types. We’ve also added support for running newer versions of HDFS alongside Spark. Finally, we’ve added the ability to launch clusters with maintenance releases of Spark in addition to launching the newest release.</p> <h3 id="improved-documentation">Improved Documentation</h3> -<p>This release adds documentation about cluster hardware provisioning and inter-operation with common Hadoop distributions. Docs are also included to cover the MLlib machine learning functions and new cluster monitoring features. Existing documentation has been updated to reflect changes in building and deploying Spark. </p> +<p>This release adds documentation about cluster hardware provisioning and inter-operation with common Hadoop distributions. Docs are also included to cover the MLlib machine learning functions and new cluster monitoring features. Existing documentation has been updated to reflect changes in building and deploying Spark.</p> <h3 id="other-improvements">Other Improvements</h3> <ul> diff --git a/site/releases/spark-release-0-9-1.html b/site/releases/spark-release-0-9-1.html index b0d489e07..60766b3eb 100644 --- a/site/releases/spark-release-0-9-1.html +++ b/site/releases/spark-release-0-9-1.html @@ -201,9 +201,9 @@ <li>Fixed hash collision bug in external spilling [<a href="https://issues.apache.org/jira/browse/SPARK-1113">SPARK-1113</a>]</li> <li>Fixed conflict with Spark’s log4j for users relying on other logging backends [<a href="https://issues.apache.org/jira/browse/SPARK-1190">SPARK-1190</a>]</li> <li>Fixed Graphx missing from Spark assembly jar in maven builds</li> - <li>Fixed silent failures due to map output status exceeding Akka frame size [<a href="https://issues.apache.org/jira/browse/SPARK-1244">SPARK-1244</a>] </li> - <li>Removed Spark’s unnecessary direct dependency on ASM [<a href="https://issues.apache.org/jira/browse/SPARK-782">SPARK-782</a>] </li> - <li>Removed metrics-ganglia from default build due to LGPL license conflict [<a href="https://issues.apache.org/jira/browse/SPARK-1167">SPARK-1167</a>] </li> + <li>Fixed silent failures due to map output status exceeding Akka frame size [<a href="https://issues.apache.org/jira/browse/SPARK-1244">SPARK-1244</a>]</li> + <li>Removed Spark’s unnecessary direct dependency on ASM [<a href="https://issues.apache.org/jira/browse/SPARK-782">SPARK-782</a>]</li> + <li>Removed metrics-ganglia from default build due to LGPL license conflict [<a href="https://issues.apache.org/jira/browse/SPARK-1167">SPARK-1167</a>]</li> <li>Fixed bug in distribution tarball not containing spark assembly jar [<a href="https://issues.apache.org/jira/browse/SPARK-1184">SPARK-1184</a>]</li> <li>Fixed bug causing infinite NullPointerException failures due to a null in map output locations [<a href="https://issues.apache.org/jira/browse/SPARK-1124">SPARK-1124</a>]</li> <li>Fixed bugs in post-job cleanup of scheduler’s data structures</li> @@ -219,7 +219,7 @@ <li>Fixed bug making Spark application stall when YARN registration fails [<a href="https://issues.apache.org/jira/browse/SPARK-1032">SPARK-1032</a>]</li> <li>Race condition in getting HDFS delegation tokens in yarn-client mode [<a href="https://issues.apache.org/jira/browse/SPARK-1203">SPARK-1203</a>]</li> <li>Fixed bug in yarn-client mode not exiting properly [<a href="https://issues.apache.org/jira/browse/SPARK-1049">SPARK-1049</a>]</li> - <li>Fixed regression bug in ADD_JAR environment variable not correctly adding custom jars [<a href="https://issues.apache.org/jira/browse/SPARK-1089">SPARK-1089</a>] </li> + <li>Fixed regression bug in ADD_JAR environment variable not correctly adding custom jars [<a href="https://issues.apache.org/jira/browse/SPARK-1089">SPARK-1089</a>]</li> </ul> <h3 id="improvements-to-other-deployment-scenarios">Improvements to other deployment scenarios</h3> @@ -230,19 +230,19 @@ <h3 id="optimizations-to-mllib">Optimizations to MLLib</h3> <ul> - <li>Optimized memory usage of ALS [<a href="https://issues.apache.org/jira/browse/MLLIB-25">MLLIB-25</a>] </li> + <li>Optimized memory usage of ALS [<a href="https://issues.apache.org/jira/browse/MLLIB-25">MLLIB-25</a>]</li> <li>Optimized computation of YtY for implicit ALS [<a href="https://issues.apache.org/jira/browse/SPARK-1237">SPARK-1237</a>]</li> <li>Support for negative implicit input in ALS [<a href="https://issues.apache.org/jira/browse/MLLIB-22">MLLIB-22</a>]</li> <li>Setting of a random seed in ALS [<a href="https://issues.apache.org/jira/browse/SPARK-1238">SPARK-1238</a>]</li> - <li>Faster construction of features with intercept [<a href="https://issues.apache.org/jira/browse/SPARK-1260">SPARK-1260</a>] </li> + <li>Faster construction of features with intercept [<a href="https://issues.apache.org/jira/browse/SPARK-1260">SPARK-1260</a>]</li> <li>Check for intercept and weight in GLM’s addIntercept [<a href="https://issues.apache.org/jira/browse/SPARK-1327">SPARK-1327</a>]</li> </ul> <h3 id="bug-fixes-and-better-api-parity-for-pyspark">Bug fixes and better API parity for PySpark</h3> <ul> <li>Fixed bug in Python de-pickling [<a href="https://issues.apache.org/jira/browse/SPARK-1135">SPARK-1135</a>]</li> - <li>Fixed bug in serialization of strings longer than 64K [<a href="https://issues.apache.org/jira/browse/SPARK-1043">SPARK-1043</a>] </li> - <li>Fixed bug that made jobs hang when base file is not available [<a href="https://issues.apache.org/jira/browse/SPARK-1025">SPARK-1025</a>] </li> + <li>Fixed bug in serialization of strings longer than 64K [<a href="https://issues.apache.org/jira/browse/SPARK-1043">SPARK-1043</a>]</li> + <li>Fixed bug that made jobs hang when base file is not available [<a href="https://issues.apache.org/jira/browse/SPARK-1025">SPARK-1025</a>]</li> <li>Added Missing RDD operations to PySpark - top, zip, foldByKey, repartition, coalesce, getStorageLevel, setName and toDebugString</li> </ul> @@ -274,13 +274,13 @@ <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> + <li>Matei Zaharia - Bug fixes in handling of task failures due to NPE, and cleaning up of scheduler data structures</li> <li>Nan Zhu - Bug fixes in PySpark RDD.takeSample and adding of JARs using ADD_JAR - and improvements to docs</li> <li>Nick Lanham - Added ability to make distribution tarballs with Tachyon</li> <li>Patrick Wendell - Bug fixes in ASM shading, fixes for log4j initialization, removing Ganglia due to LGPL license, and other miscallenous bug fixes</li> <li>Prabin Banka - RDD.zip and other missing RDD operations in PySpark</li> <li>Prashant Sharma - RDD.foldByKey in PySpark, and other PySpark doc improvements</li> - <li>Qiuzhuang - Bug fix in standalone worker </li> + <li>Qiuzhuang - Bug fix in standalone worker</li> <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> diff --git a/site/releases/spark-release-1-0-1.html b/site/releases/spark-release-1-0-1.html index 3ec4297ae..66b1dbfc2 100644 --- a/site/releases/spark-release-1-0-1.html +++ b/site/releases/spark-release-1-0-1.html @@ -258,8 +258,8 @@ <li>Cheng Hao – SQL features</li> <li>Cheng Lian – SQL features</li> <li>Christian Tzolov – build improvmenet</li> - <li>Clément MATHIEU – doc updates </li> - <li>CodingCat – doc updates and bug fix </li> + <li>Clément MATHIEU – doc updates</li> + <li>CodingCat – doc updates and bug fix</li> <li>Colin McCabe – bug fix</li> <li>Daoyuan – SQL joins</li> <li>David Lemieux – bug fix</li> @@ -275,7 +275,7 @@ <li>Kan Zhang – PySpark SQL features</li> <li>Kay Ousterhout – documentation fix</li> <li>LY Lai – bug fix</li> - <li>Lars Albertsson – bug fix </li> + <li>Lars Albertsson – bug fix</li> <li>Lei Zhang – SQL fix and feature</li> <li>Mark Hamstra – bug fix</li> <li>Matei Zaharia – doc updates and bug fix</li> @@ -297,7 +297,7 @@ <li>Shixiong Zhu – code clean-up</li> <li>Szul, Piotr – bug fix</li> <li>Takuya UESHIN – bug fixes and SQL features</li> - <li>Thomas Graves – bug fix </li> + <li>Thomas Graves – bug fix</li> <li>Uri Laserson – bug fix</li> <li>Vadim Chekan – bug fix</li> <li>Varakhedi Sujeet – ec2 r3 support</li> diff --git a/site/releases/spark-release-1-0-2.html b/site/releases/spark-release-1-0-2.html index 76f70ed94..8a6470f9b 100644 --- a/site/releases/spark-release-1-0-2.html +++ b/site/releases/spark-release-1-0-2.html @@ -268,7 +268,7 @@ <li>johnnywalleye - Bug fixes in MLlib</li> <li>joyyoj - Bug fix in Streaming</li> <li>kballou - Doc fix</li> - <li>lianhuiwang - Doc fix </li> + <li>lianhuiwang - Doc fix</li> <li>witgo - Bug fix in sbt</li> </ul> diff --git a/site/releases/spark-release-1-1-0.html b/site/releases/spark-release-1-1-0.html index 895522451..f2d1a6737 100644 --- a/site/releases/spark-release-1-1-0.html +++ b/site/releases/spark-release-1-1-0.html @@ -197,7 +197,7 @@ <p>Spark SQL adds a number of new features and performance improvements in this release. A <a href="http://spark.apache.org/docs/1.1.0/sql-programming-guide.html#running-the-thrift-jdbc-server">JDBC/ODBC server</a> allows users to connect to SparkSQL from many different applications and provides shared access to cached tables. A new module provides <a href="http://spark.apache.org/docs/1.1.0/sql-programming-guide.html#json-datasets">support for loading JSON data</a> directly into Spark’s SchemaRDD format, including automatic schema inference. Spark SQL introduces <a href="http://spark.apache.org/docs/1.1.0/sql-programming-guide.html#other-configuration-options">dynamic bytecode generation</a> in this release, a technique which significantly speeds up execution for queries that perform complex expression evaluation. This release also adds support for registering Python, Scala, and Java lambda functions as UDFs, which can then be called directly in SQL. Spark 1.1 adds a <a href="http://spark.apache.org/docs/1.1.0/sql-programming-guide.html#programmatically-specifying-the-schema">public types API to allow users to create SchemaRDD’s from custom data sources</a>. Finally, many optimizations have been added to the native Parquet support as well as throughout the engine.</p> <h3 id="mllib">MLlib</h3> -<p>MLlib adds several new algorithms and optimizations in this release. 1.1 introduces a <a href="https://issues.apache.org/jira/browse/SPARK-2359">new library of statistical packages</a> which provides exploratory analytic functions. These include stratified sampling, correlations, chi-squared tests and support for creating random datasets. This release adds utilities for feature extraction (<a href="https://issues.apache.org/jira/browse/SPARK-2510">Word2Vec</a> and <a href="https://issues.apache.org/jira/browse/SPARK-2511">TF-IDF</a>) and feature transformation (<a href="https://issues.apache.org/jira/browse/SPARK-2272">normalization and standard scaling</a>). Also new are support for <a href="https://issues.apache.org/jira/browse/SPARK-1553">nonnegative matrix factorization</a> and <a href="https://issues.apache.org/jira/browse/SPARK-1782">SVD via Lanczos</a>. The decision tree algorithm has been <a href="https://issues.apache.org/jira/browse/SPARK-2478">added in Python and Java</a>. A tree aggregation primitive has been added to help optimize many existing algorithms. Performance improves across the board in MLlib 1.1, with improvements of around 2-3X for many algorithms and up to 5X for large scale decision tree problems. </p> +<p>MLlib adds several new algorithms and optimizations in this release. 1.1 introduces a <a href="https://issues.apache.org/jira/browse/SPARK-2359">new library of statistical packages</a> which provides exploratory analytic functions. These include stratified sampling, correlations, chi-squared tests and support for creating random datasets. This release adds utilities for feature extraction (<a href="https://issues.apache.org/jira/browse/SPARK-2510">Word2Vec</a> and <a href="https://issues.apache.org/jira/browse/SPARK-2511">TF-IDF</a>) and feature transformation (<a href="https://issues.apache.org/jira/browse/SPARK-2272">normalization and standard scaling</a>). Also new are support for <a href="https://issues.apache.org/jira/browse/SPARK-1553">nonnegative matrix factorization</a> and <a href="https://issues.apache.org/jira/browse/SPARK-1782">SVD via Lanczos</a>. The decision tree algorithm has been <a href="https://issues.apache.org/jira/browse/SPARK-2478">added in Python and Java</a>. A tree aggregation primitive has been added to help optimize many existing algorithms. Performance improves across the board in MLlib 1.1, with improvements of around 2-3X for many algorithms and up to 5X for large scale decision tree problems.</p> <h3 id="graphx-and-spark-streaming">GraphX and Spark Streaming</h3> <p>Spark streaming adds a new data source <a href="https://issues.apache.org/jira/browse/SPARK-1981">Amazon Kinesis</a>. For the Apache Flume, a new mode is supported which <a href="https://issues.apache.org/jira/browse/SPARK-1729">pulls data from Flume</a>, simplifying deployment and providing high availability. The first of a set of <a href="https://issues.apache.org/jira/browse/SPARK-2438">streaming machine learning algorithms</a> is introduced with streaming linear regression. Finally, <a href="https://issues.apache.org/jira/browse/SPARK-1341">rate limiting</a> has been added for streaming inputs. GraphX adds <a href="https://issues.apache.org/jira/browse/SPARK-1991">custom storage levels for vertices and edges</a> along with <a href="https://issues.apache.org/jira/browse/SPARK-2748">improved numerical precision</a> across the board. Finally, GraphX adds a new label propagation algorithm.</p> @@ -215,7 +215,7 @@ <ul> <li>The default value of <code>spark.io.compression.codec</code> is now <code>snappy</code> for improved memory usage. Old behavior can be restored by switching to <code>lzf</code>.</li> - <li>The default value of <code>spark.broadcast.factory</code> is now <code>org.apache.spark.broadcast.TorrentBroadcastFactory</code> for improved efficiency of broadcasts. Old behavior can be restored by switching to <code>org.apache.spark.broadcast.HttpBroadcastFactory</code>. </li> + <li>The default value of <code>spark.broadcast.factory</code> is now <code>org.apache.spark.broadcast.TorrentBroadcastFactory</code> for improved efficiency of broadcasts. Old behavior can be restored by switching to <code>org.apache.spark.broadcast.HttpBroadcastFactory</code>.</li> <li>PySpark now performs external spilling during aggregations. Old behavior can be restored by setting <code>spark.shuffle.spill</code> to <code>false</code>.</li> <li>PySpark uses a new heuristic for determining the parallelism of shuffle operations. Old behavior can be restored by setting <code>spark.default.parallelism</code> to the number of cores in the cluster.</li> </ul> @@ -275,7 +275,7 @@ <li>Daneil Darabos – bug fixes and UI enhancements</li> <li>Daoyuan Wang – SQL fixes</li> <li>David Lemieux – bug fix</li> - <li>Davies Liu – PySpark fixes and spilling </li> + <li>Davies Liu – PySpark fixes and spilling</li> <li>DB Tsai – online summaries in MLlib and other MLlib features</li> <li>Derek Ma – bug fix</li> <li>Doris Xin – MLlib stats library and several fixes</li> diff --git a/site/releases/spark-release-1-2-0.html b/site/releases/spark-release-1-2-0.html index 894ad737a..020984f9c 100644 --- a/site/releases/spark-release-1-2-0.html +++ b/site/releases/spark-release-1-2-0.html @@ -194,7 +194,7 @@ <p>In 1.2 Spark core upgrades two major subsystems to improve the performance and stability of very large scale shuffles. The first is Spark’s communication manager used during bulk transfers, which upgrades to a <a href="https://issues.apache.org/jira/browse/SPARK-2468">netty-based implementation</a>. The second is Spark’s shuffle mechanism, which upgrades to the <a href="https://issues.apache.org/jira/browse/SPARK-3280">“sort based” shuffle initially released in Spark 1.1</a>. These both improve the performance and stability of very large scale shuffles. Spark also adds an <a href="https://issues.apache.org/jira/browse/SPARK-3174">elastic scaling mechanism</a> designed to improve cluster utilization during long running ETL-style jobs. This is currently supported on YARN and will make its way to other cluster managers in future versions. Finally, Spark 1.2 adds support for Scala 2.11. For instructions on building for Scala 2.11 see the <a href="/docs/1.2.0/building-spark.html#building-for-scala-211">build documentation</a>.</p> <h3 id="spark-streaming">Spark Streaming</h3> -<p>This release includes two major feature additions to Spark’s streaming library, a Python API and a write ahead log for full driver H/A. The <a href="https://issues.apache.org/jira/browse/SPARK-2377">Python API</a> covers almost all the DStream transformations and output operations. Input sources based on text files and text over sockets are currently supported. Support for Kafka and Flume input streams in Python will be added in the next release. Second, Spark streaming now features H/A driver support through a <a href="https://issues.apache.org/jira/browse/SPARK-3129">write ahead log (WAL)</a>. In Spark 1.1 and earlier, some buffered (received but not yet processed) data can be lost during driver restarts. To prevent this Spark 1.2 adds an optional WAL, which buffers received data into a fault-tolerant file system (e.g. HDFS). See the <a href="/docs/1.2.0/streaming-programming-guide.html">streaming programming guide</a> for more details. </p> +<p>This release includes two major feature additions to Spark’s streaming library, a Python API and a write ahead log for full driver H/A. The <a href="https://issues.apache.org/jira/browse/SPARK-2377">Python API</a> covers almost all the DStream transformations and output operations. Input sources based on text files and text over sockets are currently supported. Support for Kafka and Flume input streams in Python will be added in the next release. Second, Spark streaming now features H/A driver support through a <a href="https://issues.apache.org/jira/browse/SPARK-3129">write ahead log (WAL)</a>. In Spark 1.1 and earlier, some buffered (received but not yet processed) data can be lost during driver restarts. To prevent this Spark 1.2 adds an optional WAL, which buffers received data into a fault-tolerant file system (e.g. HDFS). See the <a href="/docs/1.2.0/streaming-programming-guide.html">streaming programming guide</a> for more details.</p> <h3 id="mllib">MLLib</h3> <p>Spark 1.2 previews a new set of machine learning API’s in a package called spark.ml that <a href="https://issues.apache.org/jira/browse/SPARK-3530">supports learning pipelines</a>, where multiple algorithms are run in sequence with varying parameters. This type of pipeline is common in practical machine learning deployments. The new ML package uses Spark’s SchemaRDD to represent <a href="https://issues.apache.org/jira/browse/SPARK-3573">ML datasets</a>, providing direct interoperability with Spark SQL. In addition to the new API, Spark 1.2 extends decision trees with two tree ensemble methods: <a href="https://issues.apache.org/jira/browse/SPARK-1545">random forests</a> and <a href="https://issues.apache.org/jira/browse/SPARK-1547">gradient-boosted trees</a>, among the most successful tree-based models for classification and regression. Finally, MLlib’s Python implementation receives a major update in 1.2 to simplify the process of adding Python APIs, along with better Python API coverage.</p> diff --git a/site/releases/spark-release-1-3-0.html b/site/releases/spark-release-1-3-0.html index ad212445d..aaf84868f 100644 --- a/site/releases/spark-release-1-3-0.html +++ b/site/releases/spark-release-1-3-0.html @@ -191,7 +191,7 @@ <p>To download Spark 1.3 visit the <a href="/downloads.html">downloads</a> page.</p> <h3 id="spark-core">Spark Core</h3> -<p>Spark 1.3 sees a handful of usability improvements in the core engine. The core API now supports <a href="https://issues.apache.org/jira/browse/SPARK-5430">multi level aggregation trees</a> to help speed up expensive reduce operations. <a href="https://issues.apache.org/jira/browse/SPARK-5063">Improved error reporting</a> has been added for certain gotcha operations. Spark’s Jetty dependency is <a href="https://issues.apache.org/jira/browse/SPARK-3996">now shaded</a> to help avoid conflicts with user programs. Spark now supports <a href="https://issues.apache.org/jira/browse/SPARK-3883">SSL encryption</a> for some communication endpoints. Finaly, realtime <a href="https://issues.apache.org/jira/browse/SPARK-3428">GC metrics</a> and <a href="https://issues.apache.org/jira/browse/SPARK-4874">record counts</a> have been added to the UI. </p> +<p>Spark 1.3 sees a handful of usability improvements in the core engine. The core API now supports <a href="https://issues.apache.org/jira/browse/SPARK-5430">multi level aggregation trees</a> to help speed up expensive reduce operations. <a href="https://issues.apache.org/jira/browse/SPARK-5063">Improved error reporting</a> has been added for certain gotcha operations. Spark’s Jetty dependency is <a href="https://issues.apache.org/jira/browse/SPARK-3996">now shaded</a> to help avoid conflicts with user programs. Spark now supports <a href="https://issues.apache.org/jira/browse/SPARK-3883">SSL encryption</a> for some communication endpoints. Finaly, realtime <a href="https://issues.apache.org/jira/browse/SPARK-3428">GC metrics</a> and <a href="https://issues.apache.org/jira/browse/SPARK-4874">record counts</a> have been added to the UI.</p> <h3 id="dataframe-api">DataFrame API</h3> <p>Spark 1.3 adds a new <a href="/docs/1.3.0/sql-programming-guide.html#dataframes">DataFrames API</a> that provides powerful and convenient operators when working with structured datasets. The DataFrame is an evolution of the base RDD API that includes named fields along with schema information. It’s easy to construct a DataFrame from sources such as Hive tables, JSON data, a JDBC database, or any implementation of Spark’s new data source API. Data frames will become a common interchange format between Spark components and when importing and exporting data to other systems. Data frames are supported in Python, Scala, and Java.</p> @@ -203,7 +203,7 @@ <p>In this release Spark MLlib introduces several new algorithms: latent Dirichlet allocation (LDA) for <a href="https://issues.apache.org/jira/browse/SPARK-1405">topic modeling</a>, <a href="https://issues.apache.org/jira/browse/SPARK-2309">multinomial logistic regression</a> for multiclass classification, <a href="https://issues.apache.org/jira/browse/SPARK-5012">Gaussian mixture model (GMM)</a> and <a href="https://issues.apache.org/jira/browse/SPARK-4259">power iteration clustering</a> for clustering, <a href="https://issues.apache.org/jira/browse/SPARK-4001">FP-growth</a> for frequent pattern mining, and <a href="https://issues.apache.org/jira/browse/SPARK-4409">block matrix abstraction</a> for distributed linear algebra. Initial support has been added for <a href="https://issues.apache.org/jira/browse/SPARK-4587">model import/export</a> in exchangeable format, which will be expanded in future versions to cover more model types in Java/Python/Scala. The implementations of k-means and ALS receive <a href="https://issues.apache.org/jira/browse/SPARK-3424, https://issues.apache.org/jira/browse/SPARK-3541">updates</a> that lead to significant performance gain. PySpark now supports the <a href="https://issues.apache.org/jira/browse/SPARK-4586">ML pipeline API</a> added in Spark 1.2, and <a href="https://issues.apache.org/jira/browse/SPARK-5094">gradient boosted trees</a> and <a href="https://issues.apache.org/jira/browse/SPARK-5012">Gaussian mixture model</a>. Finally, the ML pipeline API has been ported to support the new DataFrames abstraction.</p> <h3 id="spark-streaming">Spark Streaming</h3> -<p>Spark 1.3 introduces a new <a href="https://issues.apache.org/jira/browse/SPARK-4964"><em>direct</em> Kafka API</a> (<a href="http://spark.apache.org/docs/1.3.0/streaming-kafka-integration.html">docs</a>) which enables exactly-once delivery without the use of write ahead logs. It also adds a <a href="https://issues.apache.org/jira/browse/SPARK-5047">Python Kafka API</a> along with infrastructure for additional Python API’s in future releases. An online version of <a href="https://issues.apache.org/jira/browse/SPARK-4979">logistic regression</a> and the ability to read <a href="https://issues.apache.org/jira/browse/SPARK-4969">binary records</a> have also been added. For stateful operations, support has been added for loading of an <a href="https://issues.apache.org/jira/browse/SPARK-3660">initial state RDD</a>. Finally, the streaming programming guide has been updated to include information about SQL and DataFrame operations within streaming applications, and important clarifications to the fault-tolerance semantics. </p> +<p>Spark 1.3 introduces a new <a href="https://issues.apache.org/jira/browse/SPARK-4964"><em>direct</em> Kafka API</a> (<a href="http://spark.apache.org/docs/1.3.0/streaming-kafka-integration.html">docs</a>) which enables exactly-once delivery without the use of write ahead logs. It also adds a <a href="https://issues.apache.org/jira/browse/SPARK-5047">Python Kafka API</a> along with infrastructure for additional Python API’s in future releases. An online version of <a href="https://issues.apache.org/jira/browse/SPARK-4979">logistic regression</a> and the ability to read <a href="https://issues.apache.org/jira/browse/SPARK-4969">binary records</a> have also been added. For stateful operations, support has been added for loading of an <a href="https://issues.apache.org/jira/browse/SPARK-3660">initial state RDD</a>. Finally, the streaming programming guide has been updated to include information about SQL and DataFrame operations within streaming applications, and important clarifications to the fault-tolerance semantics.</p> <h3 id="graphx">GraphX</h3> <p>GraphX adds a handful of utility functions in this release, including conversion into a <a href="https://issues.apache.org/jira/browse/SPARK-4917">canonical edge graph</a>.</p> @@ -219,7 +219,7 @@ <ul> <li><a href="https://issues.apache.org/jira/browse/SPARK-6194">SPARK-6194</a>: A memory leak in PySPark’s <code>collect()</code>.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-6222">SPARK-6222</a>: An issue with failure recovery in Spark Streaming.</li> - <li><a href="https://issues.apache.org/jira/browse/SPARK-6315">SPARK-6315</a>: Spark SQL can’t read parquet data generated with Spark 1.1. </li> + <li><a href="https://issues.apache.org/jira/browse/SPARK-6315">SPARK-6315</a>: Spark SQL can’t read parquet data generated with Spark 1.1.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-6247">SPARK-6247</a>: Errors analyzing certain join types in Spark SQL.</li> </ul> diff --git a/site/releases/spark-release-1-3-1.html b/site/releases/spark-release-1-3-1.html index 2e5b80494..e13b6acf5 100644 --- a/site/releases/spark-release-1-3-1.html +++ b/site/releases/spark-release-1-3-1.html @@ -196,10 +196,10 @@ <h4 id="spark-sql">Spark SQL</h4> <ul> <li>Unable to use reserved words in DDL (<a href="http://issues.apache.org/jira/browse/SPARK-6250">SPARK-6250</a>)</li> - <li>Parquet no longer caches metadata (<a href="http://issues.apache.org/jira/browse/SPARK-6575">SPARK-6575</a>) </li> + <li>Parquet no longer caches metadata (<a href="http://issues.apache.org/jira/browse/SPARK-6575">SPARK-6575</a>)</li> <li>Bug when joining two Parquet tables (<a href="http://issues.apache.org/jira/browse/SPARK-6851">SPARK-6851</a>)</li> - <li>Unable to read parquet data generated by Spark 1.1.1 (<a href="http://issues.apache.org/jira/browse/SPARK-6315">SPARK-6315</a>) </li> - <li>Parquet data source may use wrong Hadoop FileSystem (<a href="http://issues.apache.org/jira/browse/SPARK-6330">SPARK-6330</a>) </li> + <li>Unable to read parquet data generated by Spark 1.1.1 (<a href="http://issues.apache.org/jira/browse/SPARK-6315">SPARK-6315</a>)</li> + <li>Parquet data source may use wrong Hadoop FileSystem (<a href="http://issues.apache.org/jira/browse/SPARK-6330">SPARK-6330</a>)</li> </ul> <h4 id="spark-streaming">Spark Streaming</h4> diff --git a/site/releases/spark-release-1-4-0.html b/site/releases/spark-release-1-4-0.html index 55d051c81..c5ba82024 100644 --- a/site/releases/spark-release-1-4-0.html +++ b/site/releases/spark-release-1-4-0.html @@ -250,7 +250,7 @@ Python coverage. MLlib also adds several new algorithms.</p> </ul> <h3 id="spark-streaming">Spark Streaming</h3> -<p>Spark streaming adds visual instrumentation graphs and significantly improved debugging information in the UI. It also enhances support for both Kafka and Kinesis. </p> +<p>Spark streaming adds visual instrumentation graphs and significantly improved debugging information in the UI. It also enhances support for both Kafka and Kinesis.</p> <ul> <li><a href="https://issues.apache.org/jira/browse/SPARK-7602">SPARK-7602</a>: Visualization and monitoring in the streaming UI including batch drill down (<a href="https://issues.apache.org/jira/browse/SPARK-6796">SPARK-6796</a>, <a href="https://issues.apache.org/jira/browse/SPARK-6862">SPARK-6862</a>)</li> @@ -276,7 +276,7 @@ Python coverage. MLlib also adds several new algorithms.</p> <h4 id="test-partners">Test Partners</h4> -<p>Thanks to The following organizations, who helped benchmark or integration test release candidates: <br /> Intel, Palantir, Cloudera, Mesosphere, Huawei, Shopify, Netflix, Yahoo, UC Berkeley and Databricks. </p> +<p>Thanks to The following organizations, who helped benchmark or integration test release candidates: <br /> Intel, Palantir, Cloudera, Mesosphere, Huawei, Shopify, Netflix, Yahoo, UC Berkeley and Databricks.</p> <h4 id="contributors">Contributors</h4> <ul> diff --git a/site/releases/spark-release-1-5-0.html b/site/releases/spark-release-1-5-0.html index e193ee91a..41985153c 100644 --- a/site/releases/spark-release-1-5-0.html +++ b/site/releases/spark-release-1-5-0.html @@ -191,25 +191,25 @@ <p>You can consult JIRA for the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315420&version=12332078">detailed changes</a>. We have curated a list of high level changes here:</p> <ul id="markdown-toc"> - <li><a href="#apis-rdd-dataframe-and-sql">APIs: RDD, DataFrame and SQL</a></li> - <li><a href="#backend-execution-dataframe-and-sql">Backend Execution: DataFrame and SQL</a></li> - <li><a href="#integrations-data-sources-hive-hadoop-mesos-and-cluster-management">Integrations: Data Sources, Hive, Hadoop, Mesos and Cluster Management</a></li> - <li><a href="#r-language">R Language</a></li> - <li><a href="#machine-learning-and-advanced-analytics">Machine Learning and Advanced Analytics</a></li> - <li><a href="#spark-streaming">Spark Streaming</a></li> - <li><a href="#deprecations-removals-configs-and-behavior-changes">Deprecations, Removals, Configs, and Behavior Changes</a> <ul> - <li><a href="#spark-core">Spark Core</a></li> - <li><a href="#spark-sql--dataframes">Spark SQL & DataFrames</a></li> - <li><a href="#spark-streaming-1">Spark Streaming</a></li> - <li><a href="#mllib">MLlib</a></li> + <li><a href="#apis-rdd-dataframe-and-sql" id="markdown-toc-apis-rdd-dataframe-and-sql">APIs: RDD, DataFrame and SQL</a></li> + <li><a href="#backend-execution-dataframe-and-sql" id="markdown-toc-backend-execution-dataframe-and-sql">Backend Execution: DataFrame and SQL</a></li> + <li><a href="#integrations-data-sources-hive-hadoop-mesos-and-cluster-management" id="markdown-toc-integrations-data-sources-hive-hadoop-mesos-and-cluster-management">Integrations: Data Sources, Hive, Hadoop, Mesos and Cluster Management</a></li> + <li><a href="#r-language" id="markdown-toc-r-language">R Language</a></li> + <li><a href="#machine-learning-and-advanced-analytics" id="markdown-toc-machine-learning-and-advanced-analytics">Machine Learning and Advanced Analytics</a></li> + <li><a href="#spark-streaming" id="markdown-toc-spark-streaming">Spark Streaming</a></li> + <li><a href="#deprecations-removals-configs-and-behavior-changes" id="markdown-toc-deprecations-removals-configs-and-behavior-changes">Deprecations, Removals, Configs, and Behavior Changes</a> <ul> + <li><a href="#spark-core" id="markdown-toc-spark-core">Spark Core</a></li> + <li><a href="#spark-sql--dataframes" id="markdown-toc-spark-sql--dataframes">Spark SQL & DataFrames</a></li> + <li><a href="#spark-streaming-1" id="markdown-toc-spark-streaming-1">Spark Streaming</a></li> + <li><a href="#mllib" id="markdown-toc-mllib">MLlib</a></li> </ul> </li> - <li><a href="#known-issues">Known Issues</a> <ul> - <li><a href="#sqldataframe">SQL/DataFrame</a></li> - <li><a href="#streaming">Streaming</a></li> + <li><a href="#known-issues" id="markdown-toc-known-issues">Known Issues</a> <ul> + <li><a href="#sqldataframe" id="markdown-toc-sqldataframe">SQL/DataFrame</a></li> + <li><a href="#streaming" id="markdown-toc-streaming">Streaming</a></li> </ul> </li> - <li><a href="#credits">Credits</a></li> + <li><a href="#credits" id="markdown-toc-credits">Credits</a></li> </ul> <h3 id="apis-rdd-dataframe-and-sql">APIs: RDD, DataFrame and SQL</h3> diff --git a/site/releases/spark-release-1-6-0.html b/site/releases/spark-release-1-6-0.html index 5711fe305..225c109c1 100644 --- a/site/releases/spark-release-1-6-0.html +++ b/site/releases/spark-release-1-6-0.html @@ -191,13 +191,13 @@ <p>You can consult JIRA for the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?version=12333083&projectId=12315420">detailed changes</a>. We have curated a list of high level changes here:</p> <ul id="markdown-toc"> - <li><a href="#spark-coresql">Spark Core/SQL</a></li> - <li><a href="#spark-streaming">Spark Streaming</a></li> - <li><a href="#mllib">MLlib</a></li> - <li><a href="#deprecations">Deprecations</a></li> - <li><a href="#changes-of-behavior">Changes of behavior</a></li> - <li><a href="#known-issues">Known issues</a></li> - <li><a href="#credits">Credits</a></li> + <li><a href="#spark-coresql" id="markdown-toc-spark-coresql">Spark Core/SQL</a></li> + <li><a href="#spark-streaming" id="markdown-toc-spark-streaming">Spark Streaming</a></li> + <li><a href="#mllib" id="markdown-toc-mllib">MLlib</a></li> + <li><a href="#deprecations" id="markdown-toc-deprecations">Deprecations</a></li> + <li><a href="#changes-of-behavior" id="markdown-toc-changes-of-behavior">Changes of behavior</a></li> + <li><a href="#known-issues" id="markdown-toc-known-issues">Known issues</a></li> + <li><a href="#credits" id="markdown-toc-credits">Credits</a></li> </ul> <h3 id="spark-coresql">Spark Core/SQL</h3> @@ -220,7 +220,7 @@ <ul> <li><a href="https://issues.apache.org/jira/browse/SPARK-10000">SPARK-10000</a> <strong>Unified Memory Management</strong> - Shared memory for execution and caching instead of exclusive division of the regions.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-11787">SPARK-11787</a> <strong>Parquet Performance</strong> - Improve Parquet scan performance when using flat schemas.</li> - <li><a href="https://issues.apache.org/jira/browse/SPARK-9241">SPARK-9241 </a> <strong>Improved query planner for queries having distinct aggregations</strong> - Query plans of distinct aggregations are more robust when distinct columns have high cardinality. </li> + <li><a href="https://issues.apache.org/jira/browse/SPARK-9241">SPARK-9241 </a> <strong>Improved query planner for queries having distinct aggregations</strong> - Query plans of distinct aggregations are more robust when distinct columns have high cardinality.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-9858">SPARK-9858 </a> <strong>Adaptive query execution</strong> - Initial support for automatically selecting the number of reducers for joins and aggregations.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-10978">SPARK-10978</a> <strong>Avoiding double filters in Data Source API</strong> - When implementing a data source with filter pushdown, developers can now tell Spark SQL to avoid double evaluating a pushed-down filter.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-11111">SPARK-11111</a> <strong>Fast null-safe joins</strong> - Joins using null-safe equality (<code><=></code>) will now execute using SortMergeJoin instead of computing a cartisian product.</li> @@ -233,7 +233,7 @@ <h3 id="spark-streaming">Spark Streaming</h3> <ul> - <li><strong>API Updates</strong> + <li><strong>API Updates</strong> <ul> <li><a href="https://issues.apache.org/jira/browse/SPARK-2629">SPARK-2629 </a> <strong>New improved state management</strong> - <code>mapWithState</code> - a DStream transformation for stateful stream processing, supercedes <code>updateStateByKey</code> in functionality and performance.</li> <li><a href="https://issues.apache.org/jira/browse/SPARK-11198">SPARK-11198</a> <strong>Kinesis record deaggregation</strong> - Kinesis streams have been upgraded to use KCL 1.4.0 and supports transparent deaggregation of KPL-aggregated records.</li> @@ -244,7 +244,7 @@ <li><strong>UI Improvements</strong> <ul> <li>Made failures visible in the streaming tab, in the timelines, batch list, and batch details page.</li> - <li>Made output operations visible in the streaming tab as progress bars. </li> + <li>Made output operations visible in the streaming tab as progress bars.</li> </ul> </li> </ul> diff --git a/site/releases/spark-release-2-0-0.html b/site/releases/spark-release-2-0-0.html index 5922281d5..5ee4cbb65 100644 --- a/site/releases/spark-release-2-0-0.html +++ b/site/releases/spark-release-2-0-0.html @@ -191,30 +191,30 @@ <p>To download Apache Spark 2.0.0, visit the <a href="http://spark.apache.org/downloads.html">downloads</a> page. You can consult JIRA for the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315420&version=12329449">detailed changes</a>. We have curated a list of high level changes here, grouped by major modules.</p> <ul id="markdown-toc"> - <li><a href="#api-stability">API Stability</a></li> - <li><a href="#core-and-spark-sql">Core and Spark SQL</a> <ul> - <li><a href="#programming-apis">Programming APIs</a></li> - <li><a href="#sql">SQL</a></li> - <li><a href="#new-features">New Features</a></li> - <li><a href="#performance-and-runtime">Performance and Runtime</a></li> + <li><a href="#api-stability" id="markdown-toc-api-stability">API Stability</a></li> + <li><a href="#core-and-spark-sql" id="markdown-toc-core-and-spark-sql">Core and Spark SQL</a> <ul> + <li><a href="#programming-apis" id="markdown-toc-programming-apis">Programming APIs</a></li> + <li><a href="#sql" id="markdown-toc-sql">SQL</a></li> + <li><a href="#new-features" id="markdown-toc-new-features">New Features</a></li> + <li><a href="#performance-and-runtime" id="markdown-toc-performance-and-runtime">Performance and Runtime</a></li> </ul> </li> - <li><a href="#mllib">MLlib</a> <ul> - <li><a href="#new-features-1">New features</a></li> - <li><a href="#speedscaling">Speed/scaling</a></li> + <li><a href="#mllib" id="markdown-toc-mllib">MLlib</a> <ul> + <li><a href="#new-features-1" id="markdown-toc-new-features-1">New features</a></li> + <li><a href="#speedscaling" id="markdown-toc-speedscaling">Speed/scaling</a></li> </ul> </li> - <li><a href="#sparkr">SparkR</a></li> - <li><a href="#streaming">Streaming</a></li> - <li><a href="#dependency-packaging-and-operations">Dependency, Packaging, and Operations</a></li> - <li><a href="#removals-behavior-changes-and-deprecations">Removals, Behavior Changes and Deprecations</a> <ul> - <li><a href="#removals">Removals</a></li> - <li><a href="#behavior-changes">Behavior Changes</a></li> - <li><a href="#deprecations">Deprecations</a></li> + <li><a href="#sparkr" id="markdown-toc-sparkr">SparkR</a></li> + <li><a href="#streaming" id="markdown-toc-streaming">Streaming</a></li> + <li><a href="#dependency-packaging-and-operations" id="markdown-toc-dependency-packaging-and-operations">Dependency, Packaging, and Operations</a></li> + <li><a href="#removals-behavior-changes-and-deprecations" id="markdown-toc-removals-behavior-changes-and-deprecations">Removals, Behavior Changes and Deprecations</a> <ul> + <li><a href="#removals" id="markdown-toc-removals">Removals</a></li> + <li><a href="#behavior-changes" id="markdown-toc-behavior-changes">Behavior Changes</a></li> + <li><a href="#deprecations" id="markdown-toc-deprecations">Deprecations</a></li> </ul> </li> - <li><a href="#known-issues">Known Issues</a></li> - <li><a href="#credits">Credits</a></li> + <li><a href="#known-issues" id="markdown-toc-known-issues">Known Issues</a></li> + <li><a href="#credits" id="markdown-toc-credits">Credits</a></li> </ul> <h3 id="api-stability">API Stability</h3> diff --git a/site/research.html b/site/research.html index ffffbf2fe..e8730425a 100644 --- a/site/research.html +++ b/site/research.html @@ -221,6 +221,7 @@ Spark offers an abstraction called <a href="http://www.cs.berkeley.edu/~matei/pa </li> <li> <a href="https://amplab.cs.berkeley.edu/wp-content/uploads/2014/02/graphx.pdf">GraphX: Unifying Data-Parallel and Graph-Parallel Analytics</a>. Reynold S. Xin, Daniel Crankshaw, Ankur Dave, Joseph E. Gonzalez, Michael J. Franklin, Ion Stoica. <em>OSDI 2014</em>. October 2014. + </li> <li> <a href="http://people.csail.mit.edu/matei/papers/2013/sosp_spark_streaming.pdf">Discretized Streams: Fault-Tolerant Streaming Computation at Scale</a>. Matei Zaharia, Tathagata Das, Haoyuan Li, Timothy Hunter, Scott Shenker, Ion Stoica. <em>SOSP 2013</em>. November 2013. </li> @@ -239,8 +240,7 @@ Spark offers an abstraction called <a href="http://www.cs.berkeley.edu/~matei/pa <li> <a href="http://people.csail.mit.edu/matei/papers/2010/hotcloud_spark.pdf">Spark: Cluster Computing with Working Sets</a>. Matei Zaharia, Mosharaf Chowdhury, Michael J. Franklin, Scott Shenker, Ion Stoica. <em>HotCloud 2010</em>. June 2010. </li> - -</li></ul> +</ul> </div> </div> diff --git a/site/sql/index.html b/site/sql/index.html index 76f9dcd6f..eb9eb5206 100644 --- a/site/sql/index.html +++ b/site/sql/index.html @@ -206,7 +206,7 @@ <div class="code"> context = <span class="sparkop">HiveContext</span>(sc)<br /> results = context.<span class="sparkop">sql</span>(<br /> <span class="closure">"SELECT * FROM people"</span>)<br /> - names = results.<span class="sparkop">map</span>(<span class="closure">lambda p: p.name</span>) + names = results.<span class="sparkop">map</span>(<span class="closure">lambda p: p.name</span>)<br /> </div> <div class="caption">Apply functions to results of SQL queries.</div> </div> diff --git a/sql/index.md b/sql/index.md index 19b28b041..6978863ac 100644 --- a/sql/index.md +++ b/sql/index.md @@ -28,7 +28,7 @@ subproject: SQL <div class="code"> context = <span class="sparkop">HiveContext</span>(sc)<br/> results = context.<span class="sparkop">sql</span>(<br/> <span class="closure">"SELECT * FROM people"</span>)<br/> - names = results.<span class="sparkop">map</span>(<span class="closure">lambda p: p.name</span>)</br> + names = results.<span class="sparkop">map</span>(<span class="closure">lambda p: p.name</span>)<br/> </div> <div class="caption">Apply functions to results of SQL queries.</div> </div> |