Author: matei
Date: Wed Jan 20 21:40:26 2016
New Revision: 1725819
URL: http://svn.apache.org/viewvc?rev=1725819&view=rev
Log:
Add TM symbol to download page
Modified:
spark/downloads.md
spark/site/documentation.html
spark/site/downloads.html
spark/site/news/index.html
spark/site/news/spark-0-9-1-released.html
spark/site/news/spark-0-9-2-released.html
spark/site/news/spark-1-1-0-released.html
spark/site/news/spark-1-2-2-released.html
spark/site/news/spark-and-shark-in-the-news.html
spark/site/news/spark-summit-east-2015-videos-posted.html
spark/site/releases/spark-release-0-8-0.html
spark/site/releases/spark-release-0-9-1.html
spark/site/releases/spark-release-1-0-1.html
spark/site/releases/spark-release-1-0-2.html
spark/site/releases/spark-release-1-1-0.html
spark/site/releases/spark-release-1-2-0.html
spark/site/releases/spark-release-1-3-0.html
spark/site/releases/spark-release-1-3-1.html
spark/site/releases/spark-release-1-4-0.html
spark/site/releases/spark-release-1-5-0.html
spark/site/releases/spark-release-1-6-0.html
Modified: spark/downloads.md
URL:
http://svn.apache.org/viewvc/spark/downloads.md?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/downloads.md (original)
+++ spark/downloads.md Wed Jan 20 21:40:26 2016
@@ -14,7 +14,7 @@ $(document).ready(function() {
});
</script>
-## Download Spark
+## Download Spark™
The latest release of Spark is Spark 1.6.0, released on January 4, 2016
<a href="{{site.url}}releases/spark-release-1-6-0.html">(release notes)</a>
Modified: spark/site/documentation.html
URL:
http://svn.apache.org/viewvc/spark/site/documentation.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/documentation.html (original)
+++ spark/site/documentation.html Wed Jan 20 21:40:26 2016
@@ -226,13 +226,12 @@
</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>
+<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>.
<style type="text/css">
.video-meta-info {
font-size: 0.95em;
}
-</style>
-
+</style></p>
<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>
Modified: spark/site/downloads.html
URL:
http://svn.apache.org/viewvc/spark/site/downloads.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/downloads.html (original)
+++ spark/site/downloads.html Wed Jan 20 21:40:26 2016
@@ -174,7 +174,7 @@ $(document).ready(function() {
});
</script>
-<h2 id="download-spark">Download Spark</h2>
+<h2 id="download-sparktrade">Download Spark™</h2>
<p>The latest release of Spark is Spark 1.6.0, released on January 4, 2016
<a href="/releases/spark-release-1-6-0.html">(release notes)</a>
Modified: spark/site/news/index.html
URL:
http://svn.apache.org/viewvc/spark/site/news/index.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/index.html (original)
+++ spark/site/news/index.html Wed Jan 20 21:40:26 2016
@@ -175,6 +175,7 @@
<div class="entry-date">January 14, 2016</div>
</header>
<div class="entry-content"><p>The <a
href="https://spark-summit.org/east-2016/schedule/";>agenda for Spark Summit
East</a> is now posted, with 60 talks from organizations including Netflix,
Comcast, Blackrock, Bloomberg and others. The 2nd annual Spark Summit East will
run February 16-18th in NYC and feature a full program of speakers along with
Spark training opportunities. More details are available on the <a
href="https://spark-summit.org/east-2016/schedule/";>Spark Summit East
website</a>, where you can also <a
href="http://www.prevalentdesignevents.com/sparksummit2016/east/registration.aspx?source=header";>register
to attend</a>.</p>
+
</div>
</article>
@@ -197,6 +198,7 @@ With this release the Spark community co
<div class="entry-date">November 19, 2015</div>
</header>
<div class="entry-content"><p>Call for presentations is closing soon for
<a href="https://spark-summit.org/east-2016/";>Spark Summit East</a>! The event
will take place on February 16th-18th in New York City. Submissions are welcome
across a variety of Spark-related topics, including applications, development,
data science, enterprise, and research. Please submit by November 22nd to be
considered.</p>
+
</div>
</article>
@@ -216,6 +218,7 @@ With this release the Spark community co
<div class="entry-date">October 14, 2015</div>
</header>
<div class="entry-content"><p>Abstract submissions are now open for the
2nd <a href="https://spark-summit.org/east-2016/";>Spark Summit East</a>! The
event will take place on February 16th-18th in New York City. Submissions are
welcome across a variety of Spark-related topics, including applications,
development, data science, enterprise, and research.</p>
+
</div>
</article>
@@ -245,6 +248,7 @@ With this release the Spark community co
<div class="entry-date">September 7, 2015</div>
</header>
<div class="entry-content"><p>The <a
href="http://spark-summit.org/eu-2015/schedule";>agenda for Spark Summit
Europe</a> is now posted, with 38 talks from organizations including Barclays,
Netflix, Elsevier, Intel and others. This inaugural Spark conference in Europe
will run October 27th-29th 2015 in Amsterdam and feature a full program of
speakers along with Spark training opportunities. More details are available on
the <a href="https://spark-summit.org/eu-2015/";>Spark Summit Europe
website</a>, where you can also <a
href="https://www.prevalentdesignevents.com/sparksummit2015/europe/registration.aspx?source=header";>register</a>
to attend.</p>
+
</div>
</article>
@@ -264,6 +268,7 @@ With this release the Spark community co
<div class="entry-date">June 29, 2015</div>
</header>
<div class="entry-content"><p>The videos and slides for Spark Summit 2015
are now all <a href="http://spark-summit.org/2015/#day-1";>available online</a>!
The talks include technical roadmap discussions, deep dives on Spark
components, and use cases built on top of Spark.</p>
+
</div>
</article>
@@ -295,6 +300,7 @@ The Summit will contain <a href="https:/
<div class="entry-date">May 15, 2015</div>
</header>
<div class="entry-content"><p>Abstract submissions are now open for the
first ever <a
href="https://www.prevalentdesignevents.com/sparksummit2015/europe/speaker/";>Spark
Summit Europe</a>. The event will take place on October 27th to 29th in
Amsterdam. Submissions are welcome across a variety of Spark related topics,
including use cases and ongoing development.</p>
+
</div>
</article>
@@ -303,7 +309,7 @@ The Summit will contain <a href="https:/
<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>
@@ -313,7 +319,7 @@ The Summit will contain <a href="https:/
<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>
@@ -425,7 +431,7 @@ The Summit will contain <a href="https:/
</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>
@@ -496,7 +502,7 @@ 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>
@@ -544,6 +550,7 @@ hardened YARN support.</p>
<div class="entry-date">December 19, 2013</div>
</header>
<div class="entry-content"><p>We’ve just posted <a
href="/releases/spark-release-0-8-1.html" title="Spark Release 0.8.1">Spark
Release 0.8.1</a>, a maintenance and performance release for the Scala 2.9
version of Spark. 0.8.1 includes support for YARN 2.2, a high availability mode
for the standalone scheduler, optimizations to the shuffle, and many other
improvements. We recommend that all users update to this release. Visit the <a
href="/releases/spark-release-0-8-1.html" title="Spark Release 0.8.1">release
notes</a> to read about the new features, or <a
href="/downloads.html">download</a> the release today.</p>
+
</div>
</article>
@@ -574,6 +581,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">September 25, 2013</div>
</header>
<div class="entry-content"><p>We’re proud to announce the release of
<a href="/releases/spark-release-0-8-0.html" title="Spark Release 0.8.0">Apache
Spark 0.8.0</a>. Spark 0.8.0 is a major release that includes many new
capabilities and usability improvements. Itâs also our first release under
the Apache incubator. It is the largest Spark release yet, with contributions
from 67 developers and 24 companies. Major new features include an expanded
monitoring framework and UI, a machine learning library, and support for
running Spark inside of YARN.</p>
+
</div>
</article>
@@ -603,6 +611,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">July 23, 2013</div>
</header>
<div class="entry-content"><p>Want to learn how to use Spark, Shark,
GraphX, and related technologies in person? The AMP Lab is hosting a two-day
training workshop for them on August 29th and 30th in Berkeley. The workshop
will include tutorials, talks from users, and over four hours of hands-on
exercises. <a
href="http://ampcamp.berkeley.edu/amp-camp-three-berkeley-2013/";>Registration
is now open on the AMP Camp website</a>, for a price of $250 per person. We
recommend signing up early because last year’s workshop was sold out.</p>
+
</div>
</article>
@@ -623,6 +632,7 @@ Over 450 Spark developers and enthusiast
</ul>
<p>Most users will probably want the User list, but individuals interested in
contributing code to the project should also subscribe to the Dev list.</p>
+
</div>
</article>
@@ -632,6 +642,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">July 16, 2013</div>
</header>
<div class="entry-content"><p>We’ve just posted <a
href="/releases/spark-release-0-7-3.html" title="Spark Release 0.7.3">Spark
Release 0.7.3</a>, a maintenance release that contains several fixes, including
streaming API updates and new functionality for adding JARs to a
<code>spark-shell</code> session. We recommend that all users update to this
release. Visit the <a href="/releases/spark-release-0-7-3.html" title="Spark
Release 0.7.3">release notes</a> to read about the new features, or <a
href="/downloads.html">download</a> the release today.</p>
+
</div>
</article>
@@ -641,6 +652,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">June 21, 2013</div>
</header>
<div class="entry-content"><p>Spark, its creators at the AMP Lab, and some
of its users were featured in a <a
href="http://www.wired.com/wiredenterprise/2013/06/yahoo-amazon-amplab-spark/all/";>Wired
Enterprise article</a> a few days ago. Read on to learn a little about how
Spark is being used in industry.</p>
+
</div>
</article>
@@ -650,6 +662,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">June 21, 2013</div>
</header>
<div class="entry-content"><p>Spark was recently <a
href="http://mail-archives.apache.org/mod_mbox/incubator-general/201306.mbox/%3CCDE7B773.E9A48%25chris.a.mattmann%40jpl.nasa.gov%3E";>accepted</a>
into the <a href="http://incubator.apache.org";>Apache Incubator</a>, which
will serve as the long-term home for the project. While moving the source code
and issue tracking to Apache will take some time, we are excited to be joining
the community at Apache. Stay tuned on this site for updates on how the project
hosting will change.</p>
+
</div>
</article>
@@ -659,6 +672,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">June 2, 2013</div>
</header>
<div class="entry-content"><p>We’re happy to announce the release of
<a href="/releases/spark-release-0-7-2.html" title="Spark Release 0.7.2">Spark
0.7.2</a>, a new maintenance release that includes several bug fixes and
improvements, as well as new code examples and API features. We recommend that
all users update to this release. Head over to the <a
href="/releases/spark-release-0-7-2.html" title="Spark Release 0.7.2">release
notes</a> to read about the new features, or <a
href="/downloads.html">download</a> the release today.</p>
+
</div>
</article>
@@ -674,6 +688,7 @@ Over 450 Spark developers and enthusiast
<p>The second screencast is a 2 minute <a
href="/screencasts/2-spark-documentation-overview.html">overview of the Spark
documentation</a>.</p>
<p>We hope you find these screencasts useful.</p>
+
</div>
</article>
@@ -683,6 +698,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">March 17, 2013</div>
</header>
<div class="entry-content"><p>At this year’s <a
href="http://strataconf.com/strata2013";>Strata</a> conference, the AMP Lab
hosted a full day of tutorials on Spark, Shark, and Spark Streaming, including
online exercises on Amazon EC2. Those exercises are now <a
href="http://ampcamp.berkeley.edu/big-data-mini-course/";>available online</a>,
letting you learn Spark and Shark at your own pace on an EC2 cluster with real
data. They are a great resource for learning the systems. You can also find <a
href="http://ampcamp.berkeley.edu/amp-camp-two-strata-2013/";>slides</a> from
the Strata tutorials online, as well as <a
href="http://ampcamp.berkeley.edu/amp-camp-one-berkeley-2012/";>videos</a> from
the AMP Camp workshop we held at Berkeley in August.</p>
+
</div>
</article>
@@ -692,6 +708,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">February 27, 2013</div>
</header>
<div class="entry-content"><p>We’re proud to announce the release of
<a href="/releases/spark-release-0-7-0.html" title="Spark Release 0.7.0">Spark
0.7.0</a>, a new major version of Spark that adds several key features,
including a <a href="/docs/latest/python-programming-guide.html">Python API</a>
for Spark and an <a href="/docs/latest/streaming-programming-guide.html">alpha
of Spark Streaming</a>. This release is the result of the largest group of
contributors yet behind a Spark release – 31 contributors from inside and
outside Berkeley. Head over to the <a href="/releases/spark-release-0-7-0.html"
title="Spark Release 0.7.0">release notes</a> to read more about the new
features, or <a href="/downloads.html">download</a> the release today.</p>
+
</div>
</article>
@@ -701,6 +718,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">February 24, 2013</div>
</header>
<div class="entry-content"><p>This weekend, Amazon posted an <a
href="http://aws.amazon.com/articles/Elastic-MapReduce/4926593393724923";>article</a>
and code that make it easy to launch Spark and Shark on Elastic MapReduce. The
article includes examples of how to run both interactive Scala commands and SQL
queries from Shark on data in S3. Head over to the <a
href="http://aws.amazon.com/articles/Elastic-MapReduce/4926593393724923";>Amazon
article</a> for details. We’re very excited because, to our knowledge,
this makes Spark the first non-Hadoop engine that you can launch with EMR.</p>
+
</div>
</article>
@@ -710,6 +728,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">February 7, 2013</div>
</header>
<div class="entry-content"><p>We recently released <a
href="/releases/spark-release-0-6-2.html" title="Spark Release 0.6.2">Spark
0.6.2</a>, a new version of Spark. This is a maintenance release that includes
several bug fixes and usability improvements (see the <a
href="/releases/spark-release-0-6-2.html" title="Spark Release 0.6.2">release
notes</a>). We recommend that all users upgrade to this release.</p>
+
</div>
</article>
@@ -724,6 +743,7 @@ Over 450 Spark developers and enthusiast
<li><a href="http://blog.quantifind.com/posts/logging-post/";>Configuring
Spark's logs</a></li>
</ul>
<p>Thanks for sharing this, and looking forward to see others!</p>
+
</div>
</article>
@@ -733,6 +753,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">December 21, 2012</div>
</header>
<div class="entry-content"><p>On December 18th, we held the first of a
series of Spark development meetups, for people interested in learning the
Spark codebase and contributing to the project. There was quite a bit more
demand than we anticipated, with over 80 people signing up and 64 attending.
The first meetup was an <a
href="http://www.meetup.com/spark-users/events/94101942/";>introduction to Spark
internals</a>. Thanks to one of the attendees, there’s now a <a
href="http://www.youtube.com/watch?v=49Hr5xZyTEA";>video of the meetup</a> on
YouTube. We’ve also posted the <a
href="http://files.meetup.com/3138542/dev-meetup-dec-2012.pptx";>slides</a>.
Look to see more development meetups on Spark and Shark in the future.</p>
+
</div>
</article>
@@ -751,7 +772,8 @@ Over 450 Spark developers and enthusiast
<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>
@@ -761,6 +783,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">November 22, 2012</div>
</header>
<div class="entry-content"><p>Today we’ve made available two
maintenance releases for Spark: <a href="/releases/spark-release-0-6-1.html"
title="Spark Release 0.6.1">0.6.1</a> and <a
href="/releases/spark-release-0-5-2.html" title="Spark Release
0.5.2">0.5.2</a>. They both contain important bug fixes as well as some new
features, such as the ability to build against Hadoop 2 distributions. We
recommend that users update to the latest version for their branch; for new
users, we recommend <a href="/releases/spark-release-0-6-1.html" title="Spark
Release 0.6.1">0.6.1</a>.</p>
+
</div>
</article>
@@ -770,6 +793,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">October 15, 2012</div>
</header>
<div class="entry-content"><p><a
href="/releases/spark-release-0-6-0.html">Spark version 0.6.0</a> was released
today, a major release that brings a wide range of performance improvements and
new features, including a simpler standalone deploy mode and a Java API. Read
more about it in the <a href="/releases/spark-release-0-6-0.html">release
notes</a>.</p>
+
</div>
</article>
@@ -779,6 +803,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">April 25, 2012</div>
</header>
<div class="entry-content"><p>Our <a
href="http://www.cs.berkeley.edu/~matei/papers/2012/nsdi_spark.pdf";>paper on
Spark</a> won the Best Paper Award at the <a
href="http://www.usenix.org/nsdi12/";>USENIX NSDI conference</a>. You can see a
video of the talk, as well as slides, online on the <a
href="https://www.usenix.org/conference/nsdi12/resilient-distributed-datasets-fault-tolerant-abstraction-memory-cluster-computing";>NSDI
website</a>.</p>
+
</div>
</article>
@@ -788,6 +813,7 @@ Over 450 Spark developers and enthusiast
<div class="entry-date">January 10, 2012</div>
</header>
<div class="entry-content"><p>We’ve started hosting a regular <a
href="http://www.meetup.com/spark-users/";>Bay Area Spark User Meetup</a>. Sign
up on the meetup.com page to be notified about events and meet other Spark
developers and users.</p>
+
</div>
</article>
Modified: spark/site/news/spark-0-9-1-released.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-0-9-1-released.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-0-9-1-released.html (original)
+++ spark/site/news/spark-0-9-1-released.html Wed Jan 20 21:40:26 2016
@@ -173,7 +173,7 @@
<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>
Modified: spark/site/news/spark-0-9-2-released.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-0-9-2-released.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-0-9-2-released.html (original)
+++ spark/site/news/spark-0-9-2-released.html Wed Jan 20 21:40:26 2016
@@ -172,7 +172,7 @@
<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>
Modified: spark/site/news/spark-1-1-0-released.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-1-1-0-released.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-1-1-0-released.html (original)
+++ spark/site/news/spark-1-1-0-released.html Wed Jan 20 21:40:26 2016
@@ -172,7 +172,7 @@
<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
Sparkâs 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
Sparkâs 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>
Modified: spark/site/news/spark-1-2-2-released.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-1-2-2-released.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-1-2-2-released.html (original)
+++ spark/site/news/spark-1-2-2-released.html Wed Jan 20 21:40:26 2016
@@ -170,7 +170,7 @@
<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>
Modified: spark/site/news/spark-and-shark-in-the-news.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-and-shark-in-the-news.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-and-shark-in-the-news.html (original)
+++ spark/site/news/spark-and-shark-in-the-news.html Wed Jan 20 21:40:26 2016
@@ -180,7 +180,7 @@
<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>
Modified: spark/site/news/spark-summit-east-2015-videos-posted.html
URL:
http://svn.apache.org/viewvc/spark/site/news/spark-summit-east-2015-videos-posted.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/news/spark-summit-east-2015-videos-posted.html (original)
+++ spark/site/news/spark-summit-east-2015-videos-posted.html Wed Jan 20
21:40:26 2016
@@ -170,7 +170,7 @@
<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>
Modified: spark/site/releases/spark-release-0-8-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-0-8-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-0-8-0.html (original)
+++ spark/site/releases/spark-release-0-8-0.html Wed Jan 20 21:40:26 2016
@@ -194,13 +194,13 @@
<p>Sparkâs 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>Sparkâs EC2 scripts now support launching in any availability zone.
Support has also been added for EC2 instance types which use the newer
âHVMâ architecture. This includes the cluster compute (cc1/cc2) family of
instance types. Weâve also added support for running newer versions of HDFS
alongside Spark. Finally, weâve 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>
Modified: spark/site/releases/spark-release-0-9-1.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-0-9-1.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-0-9-1.html (original)
+++ spark/site/releases/spark-release-0-9-1.html Wed Jan 20 21:40:26 2016
@@ -185,9 +185,9 @@
<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 Sparkâs 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 Sparkâs 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 Sparkâs 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 schedulerâs data structures</li>
@@ -203,7 +203,7 @@
<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>
@@ -214,19 +214,19 @@
<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 GLMâs 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>
@@ -258,13 +258,13 @@
<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>
Modified: spark/site/releases/spark-release-1-0-1.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-0-1.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-0-1.html (original)
+++ spark/site/releases/spark-release-1-0-1.html Wed Jan 20 21:40:26 2016
@@ -242,8 +242,8 @@
<li>Cheng Hao – SQL features</li>
<li>Cheng Lian – SQL features</li>
<li>Christian Tzolov – build improvmenet</li>
- <li>Cl̩ment MATHIEU Рdoc updates</li>
- <li>CodingCat – doc updates and bug fix</li>
+ <li>Cl̩ment MATHIEU Рdoc 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>
@@ -259,7 +259,7 @@
<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>
@@ -281,7 +281,7 @@
<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>
Modified: spark/site/releases/spark-release-1-0-2.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-0-2.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-0-2.html (original)
+++ spark/site/releases/spark-release-1-0-2.html Wed Jan 20 21:40:26 2016
@@ -252,7 +252,7 @@
<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>
Modified: spark/site/releases/spark-release-1-1-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-1-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-1-0.html (original)
+++ spark/site/releases/spark-release-1-1-0.html Wed Jan 20 21:40:26 2016
@@ -181,7 +181,7 @@
<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 Sparkâs 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 SchemaRDDâs 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>
@@ -199,7 +199,7 @@
<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>
@@ -259,7 +259,7 @@
<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>
Modified: spark/site/releases/spark-release-1-2-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-2-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-2-0.html (original)
+++ spark/site/releases/spark-release-1-2-0.html Wed Jan 20 21:40:26 2016
@@ -178,7 +178,7 @@
<p>In 1.2 Spark core upgrades two major subsystems to improve the performance
and stability of very large scale shuffles. The first is Sparkâs
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 Sparkâs shuffle mechanism, which upgrades
to the <a href="https://issues.apache.org/jira/browse/SPARK-3280";>âsort
basedâ 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/build
ing-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 Sparkâs 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 Sparkâs 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 APIâs 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 Sparkâs 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 b
etter Python API coverage.</p>
Modified: spark/site/releases/spark-release-1-3-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-3-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-3-0.html (original)
+++ spark/site/releases/spark-release-1-3-0.html Wed Jan 20 21:40:26 2016
@@ -175,7 +175,7 @@
<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. Itâs easy to construct a DataFrame from
sources such as Hive tables, JSON data, a JDBC database, or any implementation
of Sparkâs 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>
@@ -187,7 +187,7 @@
<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-mea
ns 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 APIâs 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 clari
fications 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 APIâs 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 clari
fications 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>
@@ -203,7 +203,7 @@
<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>
Modified: spark/site/releases/spark-release-1-3-1.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-3-1.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-3-1.html (original)
+++ spark/site/releases/spark-release-1-3-1.html Wed Jan 20 21:40:26 2016
@@ -180,10 +180,10 @@
<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>
Modified: spark/site/releases/spark-release-1-4-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-4-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-4-0.html (original)
+++ spark/site/releases/spark-release-1-4-0.html Wed Jan 20 21:40:26 2016
@@ -234,7 +234,7 @@ Python coverage. MLlib also adds several
</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>
@@ -260,7 +260,7 @@ Python coverage. MLlib also adds several
<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>
Modified: spark/site/releases/spark-release-1-5-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-5-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-5-0.html (original)
+++ spark/site/releases/spark-release-1-5-0.html Wed Jan 20 21:40:26 2016
@@ -175,25 +175,25 @@
<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"
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>
+ <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>
</ul>
</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>
+ <li><a href="#known-issues">Known Issues</a> <ul>
+ <li><a href="#sqldataframe">SQL/DataFrame</a></li>
+ <li><a href="#streaming">Streaming</a></li>
</ul>
</li>
- <li><a href="#credits" id="markdown-toc-credits">Credits</a></li>
+ <li><a href="#credits">Credits</a></li>
</ul>
<h3 id="apis-rdd-dataframe-and-sql">APIs: RDD, DataFrame and SQL</h3>
Modified: spark/site/releases/spark-release-1-6-0.html
URL:
http://svn.apache.org/viewvc/spark/site/releases/spark-release-1-6-0.html?rev=1725819&r1=1725818&r2=1725819&view=diff
==============================================================================
--- spark/site/releases/spark-release-1-6-0.html (original)
+++ spark/site/releases/spark-release-1-6-0.html Wed Jan 20 21:40:26 2016
@@ -175,13 +175,13 @@
<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" 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>
+ <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>
</ul>
<h3 id="spark-coresql">Spark Core/SQL</h3>
@@ -204,7 +204,7 @@
<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>
@@ -217,7 +217,7 @@
<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>
@@ -228,7 +228,7 @@
<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>
---------------------------------------------------------------------
To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org
For additional commands, e-mail: commits-h...@spark.apache.org
