Just FYI, the svnpubsub for the website is currently not working. This is the respective issue for the website migration: https://issues.apache.org/jira/browse/INFRA-8915
On Wed, Jan 7, 2015 at 11:40 AM, <ktzou...@apache.org> wrote: > Author: ktzoumas > Date: Wed Jan 7 10:40:31 2015 > New Revision: 1650029 > > URL: http://svn.apache.org/r1650029 > Log: > Added blog post - December 2014 in the Flink community > > Added: > flink/_posts/2015-01-06-december-in-flink.md > flink/site/news/2015/ > flink/site/news/2015/01/ > flink/site/news/2015/01/06/ > flink/site/news/2015/01/06/december-in-flink.html > Modified: > flink/site/blog/index.html > flink/site/blog/page2/index.html > flink/site/blog/page3/index.html > > Added: flink/_posts/2015-01-06-december-in-flink.md > URL: > http://svn.apache.org/viewvc/flink/_posts/2015-01-06-december-in-flink.md?rev=1650029&view=auto > > ============================================================================== > --- flink/_posts/2015-01-06-december-in-flink.md (added) > +++ flink/_posts/2015-01-06-december-in-flink.md Wed Jan 7 10:40:31 2015 > @@ -0,0 +1,62 @@ > +--- > +layout: post > +title: 'December 2014 in the Flink community' > +date: 2015-01-06 10:00:00 > +categories: news > +--- > + > +This is the first blog post of a “newsletter†like series where we > give a summary of the monthly activity in the Flink community. As the Flink > project grows, this can serve as a "tl;dr" for people that are not > following the Flink dev and user mailing lists, or those that are simply > overwhelmed by the traffic. > + > + > +###Flink graduation > + > +The biggest news is that the Apache board approved Flink as a top-level > Apache project! The Flink team is working closely with the Apache press > team for an official announcement, so stay tuned for details! > + > +###New Flink website > + > +The [Flink website](http://flink.apache.org) got a total make-over, both > in terms of appearance and content. > + > +###Flink IRC channel > + > +A new IRC channel called #flink was created at irc.freenode.org. An easy > way to access the IRC channel is through the [web client]( > http://webchat.freenode.net/). Feel free to stop by to ask anything or > share your ideas about Apache Flink! > + > +###Meetups and Talks > + > +Apache Flink was presented in the [Amsterdam Hadoop User Group]( > http://www.meetup.com/Netherlands-Hadoop-User-Group/events/218635152) > + > +##Notable code contributions > + > +**Note:** Code contributions listed here may not be part of a release or > even the current snapshot yet. > + > +###[Streaming Scala API]( > https://github.com/apache/incubator-flink/pull/275) > + > +The Flink Streaming Java API recently got its Scala counterpart. Once > merged, Flink Streaming users can use both Scala and Java for their > development. The Flink Streaming Scala API is built as a thin layer on top > of the Java API, making sure that the APIs are kept easily in sync. > + > +###[Intermediate datasets]( > https://github.com/apache/incubator-flink/pull/254) > + > +This pull request introduces a major change in the Flink runtime. > Currently, the Flink runtime is based on the notion of operators that > exchange data through channels. With the PR, intermediate data sets that > are produced by operators become first-class citizens in the runtime. While > this does not have any user-facing impact yet, it lays the groundwork for a > slew of future features such as blocking execution, fine-grained > fault-tolerance, and more efficient data sharing between cluster and client. > + > +###[Configurable execution mode]( > https://github.com/apache/incubator-flink/pull/259) > + > +This pull request allows the user to change the object-reuse behaviour. > Before this pull request, some operations would reuse objects passed to the > user function while others would always create new objects. This introduces > a system wide switch and changes all operators to either reuse objects or > don’t reuse objects. > + > +###[Distributed Coordination via Akka]( > https://github.com/apache/incubator-flink/pull/149) > + > +Another major change is a complete rewrite of the JobManager / > TaskManager components in Scala. In addition to that, the old RPC service > was replaced by Actors, using the Akka framework. > + > +###[Sorting of very large records]( > https://github.com/apache/incubator-flink/pull/249 ) > + > +Flink's internal sort-algorithms were improved to better handle large > records (multiple 100s of megabytes or larger). Previously, the system did > in some cases hold instances of multiple large records, resulting in high > memory consumption and JVM heap thrashing. Through this fix, large records > are streamed through the operators, reducing the memory consumption and GC > pressure. The system now requires much less memory to support algorithms > that work on such large records. > + > +###[Kryo Serialization as the new default fallback]( > https://github.com/apache/incubator-flink/pull/271) > + > +Flink’s build-in type serialization framework is handles all common > types very efficiently. Prior versions uses Avro to serialize types that > the built-in framework could not handle. > +Flink serialization system improved a lot over time and by now surpasses > the capabilities of Avro in many cases. Kryo now serves as the default > fallback serialization framework, supporting a much broader range of types. > + > +###[Hadoop FileSystem support]( > https://github.com/apache/incubator-flink/pull/268) > + > +This change permits users to use all file systems supported by Hadoop > with Flink. In practice this means that users can use Flink with Tachyon, > Google Cloud Storage (also out of the box Flink YARN support on Google > Compute Cloud), FTP and all the other file system implementations for > Hadoop. > + > +##Heading to the 0.8.0 release > + > +The community is working hard together with the Apache infra team to > migrate the Flink infrastructure to a top-level project. At the same time, > the Flink community is working on the Flink 0.8.0 release which should be > out very soon. > \ No newline at end of file > > Modified: flink/site/blog/index.html > URL: > http://svn.apache.org/viewvc/flink/site/blog/index.html?rev=1650029&r1=1650028&r2=1650029&view=diff > > ============================================================================== > --- flink/site/blog/index.html (original) > +++ flink/site/blog/index.html Wed Jan 7 10:40:31 2015 > @@ -131,6 +131,68 @@ > <div class="col-md-8"> > > <article> > + <h2><a > href="/news/2015/01/06/december-in-flink.html">December 2014 in the Flink > community</a></h2> > + <p class="meta">06 Jan 2015</p> > + > + <div><p>This is the first blog post of a > “newsletter†like series where we give a summary of the monthly > activity in the Flink community. As the Flink project grows, this can serve > as a "tl;dr" for people that are not following the Flink dev and > user mailing lists, or those that are simply overwhelmed by the traffic.</p> > + > +<h3 id="flink-graduation">Flink graduation</h3> > + > +<p>The biggest news is that the Apache board approved Flink as a > top-level Apache project! The Flink team is working closely with the Apache > press team for an official announcement, so stay tuned for details!</p> > + > +<h3 id="new-flink-website">New Flink website</h3> > + > +<p>The <a href="http://flink.apache.org";>Flink website</a> got a total > make-over, both in terms of appearance and content.</p> > + > +<h3 id="flink-irc-channel">Flink IRC channel</h3> > + > +<p>A new IRC channel called #flink was created at irc.freenode.org. An > easy way to access the IRC channel is through the <a href=" > http://webchat.freenode.net/";>web client</a>. Feel free to stop by to > ask anything or share your ideas about Apache Flink!</p> > + > +<h3 id="meetups-and-talks">Meetups and Talks</h3> > + > +<p>Apache Flink was presented in the <a href=" > http://www.meetup.com/Netherlands-Hadoop-User-Group/events/218635152";>Amsterdam > Hadoop User Group</a></p> > + > +<h2 id="notable-code-contributions">Notable code contributions</h2> > + > +<p><strong>Note:</strong> Code contributions listed here may not be part > of a release or even the current snapshot yet.</p> > + > +<h3 id="streaming-scala-api"><a href=" > https://github.com/apache/incubator-flink/pull/275";>Streaming Scala > API</a></h3> > + > +<p>The Flink Streaming Java API recently got its Scala counterpart. Once > merged, Flink Streaming users can use both Scala and Java for their > development. The Flink Streaming Scala API is built as a thin layer on top > of the Java API, making sure that the APIs are kept easily in sync.</p> > + > +<h3 id="intermediate-datasets"><a href=" > https://github.com/apache/incubator-flink/pull/254";>Intermediate > datasets</a></h3> > + > +<p>This pull request introduces a major change in the Flink runtime. > Currently, the Flink runtime is based on the notion of operators that > exchange data through channels. With the PR, intermediate data sets that > are produced by operators become first-class citizens in the runtime. While > this does not have any user-facing impact yet, it lays the groundwork for a > slew of future features such as blocking execution, fine-grained > fault-tolerance, and more efficient data sharing between cluster and > client.</p> > + > +<h3 id="configurable-execution-mode"><a href=" > https://github.com/apache/incubator-flink/pull/259";>Configurable > execution mode</a></h3> > + > +<p>This pull request allows the user to change the object-reuse > behaviour. Before this pull request, some operations would reuse objects > passed to the user function while others would always create new objects. > This introduces a system wide switch and changes all operators to either > reuse objects or don’t reuse objects.</p> > + > +<h3 id="distributed-coordination-via-akka"><a href=" > https://github.com/apache/incubator-flink/pull/149";>Distributed > Coordination via Akka</a></h3> > + > +<p>Another major change is a complete rewrite of the JobManager / > TaskManager components in Scala. In addition to that, the old RPC service > was replaced by Actors, using the Akka framework.</p> > + > +<h3 id="sorting-of-very-large-records"><a href=" > https://github.com/apache/incubator-flink/pull/249";>Sorting of very large > records</a></h3> > + > +<p>Flink's internal sort-algorithms were improved to better handle > large records (multiple 100s of megabytes or larger). Previously, the > system did in some cases hold instances of multiple large records, > resulting in high memory consumption and JVM heap thrashing. Through this > fix, large records are streamed through the operators, reducing the memory > consumption and GC pressure. The system now requires much less memory to > support algorithms that work on such large records.</p> > + > +<h3 id="kryo-serialization-as-the-new-default-fallback"><a href=" > https://github.com/apache/incubator-flink/pull/271";>Kryo Serialization as > the new default fallback</a></h3> > + > +<p>Flink’s build-in type serialization framework is handles all common > types very efficiently. Prior versions uses Avro to serialize types that > the built-in framework could not handle. > +Flink serialization system improved a lot over time and by now surpasses > the capabilities of Avro in many cases. Kryo now serves as the default > fallback serialization framework, supporting a much broader range of > types.</p> > + > +<h3 id="hadoop-filesystem-support"><a href=" > https://github.com/apache/incubator-flink/pull/268";>Hadoop FileSystem > support</a></h3> > + > +<p>This change permits users to use all file systems supported by Hadoop > with Flink. In practice this means that users can use Flink with Tachyon, > Google Cloud Storage (also out of the box Flink YARN support on Google > Compute Cloud), FTP and all the other file system implementations for > Hadoop.</p> > + > +<h2 id="heading-to-the-0.8.0-release">Heading to the 0.8.0 release</h2> > + > +<p>The community is working hard together with the Apache infra team to > migrate the Flink infrastructure to a top-level project. At the same time, > the Flink community is working on the Flink 0.8.0 release which should be > out very soon.</p> > +</div> > + <a > href="/news/2015/01/06/december-in-flink.html#disqus_thread">December 2014 > in the Flink community</a> > + </article> > + > + <article> > <h2><a > href="/news/2014/11/18/hadoop-compatibility.html">Hadoop Compatibility in > Flink</a></h2> > <p class="meta">18 Nov 2014</p> > > @@ -786,98 +848,6 @@ Inspect the result in HDFS using:</p> > <a > href="/news/2014/02/18/amazon-elastic-mapreduce-cloud-yarn.html#disqus_thread">Use > Stratosphere with Amazon Elastic MapReduce</a> > </article> > > - <article> > - <h2><a > href="/news/2014/01/28/querying_mongodb.html">Accessing Data Stored in > MongoDB with Stratosphere</a></h2> > - <p class="meta">28 Jan 2014</p> > - > - <div><p>We recently merged a <a href=" > https://github.com/stratosphere/stratosphere/pull/437";>pull request</a> > that allows you to use any existing Hadoop <a href=" > http://developer.yahoo.com/hadoop/tutorial/module5.html#inputformat";>InputFormat</a> > with Stratosphere. So you can now (in the <code>0.5-SNAPSHOT</code> and > upwards versions) define a Hadoop-based data source:</p> > -<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="n">HadoopDataSource</span> <span > class="n">source</span> <span class="o">=</span> <span class="k">new</span> > <span class="nf">HadoopDataSource</span><span class="o">(</span><span > class="k">new</span> <span class="nf">TextInputFormat</span><span > class="o">(),</span> <span class="k">new</span> <span > class="nf">JobConf</span><span class="o">(),</span> <span > class="s">"Input Lines"</span><span class="o">);</span> > -<span class="n">TextInputFormat</span><span class="o">.</span><span > class="na">addInputPath</span><span class="o">(</span><span > class="n">source</span><span class="o">.</span><span > class="na">getJobConf</span><span class="o">(),</span> <span > class="k">new</span> <span class="nf">Path</span><span > class="o">(</span><span class="n">dataInput</span><span class="o">));</span> > -</code></pre></div> > -<p>We describe in the following article how to access data stored in <a > href="http://www.mongodb.org/";>MongoDB</a> with Stratosphere. This allows > users to join data from multiple sources (e.g. MonogDB and HDFS) or perform > machine learning with the documents stored in MongoDB.</p> > - > -<p>The approach here is to use the <code>MongoInputFormat</code> that was > developed for Apache Hadoop but now also runs with Stratosphere.</p> > -<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="n">JobConf</span> <span class="n">conf</span> > <span class="o">=</span> <span class="k">new</span> <span > class="nf">JobConf</span><span class="o">();</span> > -<span class="n">conf</span><span class="o">.</span><span > class="na">set</span><span class="o">(</span><span > class="s">"mongo.input.uri"</span><span class="o">,</span><span > class="s">"mongodb://localhost:27017/enron_mail.messages"</span><span > class="o">);</span> > -<span class="n">HadoopDataSource</span> <span class="n">src</span> <span > class="o">=</span> <span class="k">new</span> <span > class="nf">HadoopDataSource</span><span class="o">(</span><span > class="k">new</span> <span class="nf">MongoInputFormat</span><span > class="o">(),</span> <span class="n">conf</span><span class="o">,</span> > <span class="s">"Read from Mongodb"</span><span > class="o">,</span> <span class="k">new</span> <span > class="nf">WritableWrapperConverter</span><span class="o">());</span> > -</code></pre></div> > -<h3 id="example-program">Example Program</h3> > - > -<p>The example program reads data from the <a href=" > http://www.cs.cmu.edu/%7Eenron/";>enron dataset</a> that contains about > 500k internal e-mails. The data is stored in MongoDB and the Stratosphere > program counts the number of e-mails per day.</p> > - > -<p>The complete code of this sample program is available on <a href=" > https://github.com/stratosphere/stratosphere-mongodb-example > ">GitHub</a>.</p> > - > -<h4 id="prepare-mongodb-and-the-data">Prepare MongoDB and the Data</h4> > - > -<ul> > -<li>Install MongoDB</li> > -<li>Download the enron dataset from <a href=" > http://mongodb-enron-email.s3-website-us-east-1.amazonaws.com/";>their > website</a>.</li> > -<li>Unpack and load it</li> > -</ul> > -<div class="highlight"><pre><code class="language-bash" data-lang="bash"> > bunzip2 enron_mongo.tar.bz2 > - tar xvf enron_mongo.tar > - mongorestore dump/enron_mail/messages.bson > -</code></pre></div> > -<p>We used <a href="http://robomongo.org/";>Robomongo</a> to visually > examine the dataset stored in MongoDB.</p> > - > -<p><img src="/img/blog/robomongo.png" style="width:90%;margin:15px"></p> > - > -<h4 id="build-mongoinputformat">Build <code>MongoInputFormat</code></h4> > - > -<p>MongoDB offers an InputFormat for Hadoop on their <a href=" > https://github.com/mongodb/mongo-hadoop";>GitHub page</a>. The code is not > available in any Maven repository, so we have to build the jar file on our > own.</p> > - > -<ul> > -<li>Check out the repository</li> > -</ul> > -<div class="highlight"><pre><code class="language-text" > data-lang="text">git clone https://github.com/mongodb/mongo-hadoop.git > -cd mongo-hadoop > -</code></pre></div> > -<ul> > -<li>Set the appropriate Hadoop version in the <code>build.sbt</code>, we > used <code>1.1</code>.</li> > -</ul> > -<div class="highlight"><pre><code class="language-bash" > data-lang="bash">hadoopRelease in ThisBuild :<span class="o">=</span> <span > class="s2">"1.1"</span> > -</code></pre></div> > -<ul> > -<li>Build the input format</li> > -</ul> > -<div class="highlight"><pre><code class="language-bash" > data-lang="bash">./sbt package > -</code></pre></div> > -<p>The jar-file is now located in <code>core/target</code>.</p> > - > -<h4 id="the-stratosphere-program">The Stratosphere Program</h4> > - > -<p>Now we have everything prepared to run the Stratosphere program. I > only ran it on my local computer, out of Eclipse. To do that, check out the > code ...</p> > -<div class="highlight"><pre><code class="language-bash" > data-lang="bash">git clone > https://github.com/stratosphere/stratosphere-mongodb-example.git > -</code></pre></div> > -<p>... and import it as a Maven project into your Eclipse. You have to > manually add the previously built mongo-hadoop jar-file as a dependency. > -You can now press the "Run" button and see how Stratosphere > executes the little program. It was running for about 8 seconds on the 1.5 > GB dataset.</p> > - > -<p>The result (located in <code>/tmp/enronCountByDay</code>) now looks > like this.</p> > -<div class="highlight"><pre><code class="language-text" > data-lang="text">11,Fri Sep 26 10:00:00 CEST 1997 > -154,Tue Jun 29 10:56:00 CEST 1999 > -292,Tue Aug 10 12:11:00 CEST 1999 > -185,Thu Aug 12 18:35:00 CEST 1999 > -26,Fri Mar 19 12:33:00 CET 1999 > -</code></pre></div> > -<p>There is one thing left I want to point out here. MongoDB represents > objects stored in the database as JSON-documents. Since Stratosphere's > standard types do not support JSON documents, I was using the > <code>WritableWrapper</code> here. This wrapper allows to use any Hadoop > datatype with Stratosphere.</p> > - > -<p>The following code example shows how the JSON-documents are accessed > in Stratosphere.</p> > -<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="kd">public</span> <span > class="kt">void</span> <span class="nf">map</span><span > class="o">(</span><span class="n">Record</span> <span > class="n">record</span><span class="o">,</span> <span > class="n">Collector</span><span class="o"><</span><span > class="n">Record</span><span class="o">></span> <span > class="n">out</span><span class="o">)</span> <span class="kd">throws</span> > <span class="n">Exception</span> <span class="o">{</span> > - <span class="n">Writable</span> <span class="n">valWr</span> <span > class="o">=</span> <span class="n">record</span><span > class="o">.</span><span class="na">getField</span><span > class="o">(</span><span class="mi">1</span><span class="o">,</span> <span > class="n">WritableWrapper</span><span class="o">.</span><span > class="na">class</span><span class="o">).</span><span > class="na">value</span><span class="o">();</span> > - <span class="n">BSONWritable</span> <span class="n">value</span> > <span class="o">=</span> <span class="o">(</span><span > class="n">BSONWritable</span><span class="o">)</span> <span > class="n">valWr</span><span class="o">;</span> > - <span class="n">Object</span> <span class="n">headers</span> <span > class="o">=</span> <span class="n">value</span><span > class="o">.</span><span class="na">getDoc</span><span > class="o">().</span><span class="na">get</span><span > class="o">(</span><span class="s">"headers"</span><span > class="o">);</span> > - <span class="n">BasicDBObject</span> <span class="n">headerOb</span> > <span class="o">=</span> <span class="o">(</span><span > class="n">BasicDBObject</span><span class="o">)</span> <span > class="n">headers</span><span class="o">;</span> > - <span class="n">String</span> <span class="n">date</span> <span > class="o">=</span> <span class="o">(</span><span > class="n">String</span><span class="o">)</span> <span > class="n">headerOb</span><span class="o">.</span><span > class="na">get</span><span class="o">(</span><span > class="s">"Date"</span><span class="o">);</span> > - <span class="c1">// further date processing</span> > -<span class="o">}</span> > -</code></pre></div> > -<p>Please use the comments if you have questions or if you want to > showcase your own MongoDB-Stratosphere integration. > -<br><br> > -<small>Written by Robert Metzger (<a href="https://twitter.com/rmetzger_ > ">@rmetzger_</a>).</small></p> > -</div> > - <a > href="/news/2014/01/28/querying_mongodb.html#disqus_thread">Accessing Data > Stored in MongoDB with Stratosphere</a> > - </article> > - > </div> > <div class="col-md-2"></div> > </div> > > Modified: flink/site/blog/page2/index.html > URL: > http://svn.apache.org/viewvc/flink/site/blog/page2/index.html?rev=1650029&r1=1650028&r2=1650029&view=diff > > ============================================================================== > --- flink/site/blog/page2/index.html (original) > +++ flink/site/blog/page2/index.html Wed Jan 7 10:40:31 2015 > @@ -131,6 +131,98 @@ > <div class="col-md-8"> > > <article> > + <h2><a > href="/news/2014/01/28/querying_mongodb.html">Accessing Data Stored in > MongoDB with Stratosphere</a></h2> > + <p class="meta">28 Jan 2014</p> > + > + <div><p>We recently merged a <a href=" > https://github.com/stratosphere/stratosphere/pull/437";>pull request</a> > that allows you to use any existing Hadoop <a href=" > http://developer.yahoo.com/hadoop/tutorial/module5.html#inputformat";>InputFormat</a> > with Stratosphere. So you can now (in the <code>0.5-SNAPSHOT</code> and > upwards versions) define a Hadoop-based data source:</p> > +<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="n">HadoopDataSource</span> <span > class="n">source</span> <span class="o">=</span> <span class="k">new</span> > <span class="nf">HadoopDataSource</span><span class="o">(</span><span > class="k">new</span> <span class="nf">TextInputFormat</span><span > class="o">(),</span> <span class="k">new</span> <span > class="nf">JobConf</span><span class="o">(),</span> <span > class="s">"Input Lines"</span><span class="o">);</span> > +<span class="n">TextInputFormat</span><span class="o">.</span><span > class="na">addInputPath</span><span class="o">(</span><span > class="n">source</span><span class="o">.</span><span > class="na">getJobConf</span><span class="o">(),</span> <span > class="k">new</span> <span class="nf">Path</span><span > class="o">(</span><span class="n">dataInput</span><span class="o">));</span> > +</code></pre></div> > +<p>We describe in the following article how to access data stored in <a > href="http://www.mongodb.org/";>MongoDB</a> with Stratosphere. This allows > users to join data from multiple sources (e.g. MonogDB and HDFS) or perform > machine learning with the documents stored in MongoDB.</p> > + > +<p>The approach here is to use the <code>MongoInputFormat</code> that was > developed for Apache Hadoop but now also runs with Stratosphere.</p> > +<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="n">JobConf</span> <span class="n">conf</span> > <span class="o">=</span> <span class="k">new</span> <span > class="nf">JobConf</span><span class="o">();</span> > +<span class="n">conf</span><span class="o">.</span><span > class="na">set</span><span class="o">(</span><span > class="s">"mongo.input.uri"</span><span class="o">,</span><span > class="s">"mongodb://localhost:27017/enron_mail.messages"</span><span > class="o">);</span> > +<span class="n">HadoopDataSource</span> <span class="n">src</span> <span > class="o">=</span> <span class="k">new</span> <span > class="nf">HadoopDataSource</span><span class="o">(</span><span > class="k">new</span> <span class="nf">MongoInputFormat</span><span > class="o">(),</span> <span class="n">conf</span><span class="o">,</span> > <span class="s">"Read from Mongodb"</span><span > class="o">,</span> <span class="k">new</span> <span > class="nf">WritableWrapperConverter</span><span class="o">());</span> > +</code></pre></div> > +<h3 id="example-program">Example Program</h3> > + > +<p>The example program reads data from the <a href=" > http://www.cs.cmu.edu/%7Eenron/";>enron dataset</a> that contains about > 500k internal e-mails. The data is stored in MongoDB and the Stratosphere > program counts the number of e-mails per day.</p> > + > +<p>The complete code of this sample program is available on <a href=" > https://github.com/stratosphere/stratosphere-mongodb-example > ">GitHub</a>.</p> > + > +<h4 id="prepare-mongodb-and-the-data">Prepare MongoDB and the Data</h4> > + > +<ul> > +<li>Install MongoDB</li> > +<li>Download the enron dataset from <a href=" > http://mongodb-enron-email.s3-website-us-east-1.amazonaws.com/";>their > website</a>.</li> > +<li>Unpack and load it</li> > +</ul> > +<div class="highlight"><pre><code class="language-bash" data-lang="bash"> > bunzip2 enron_mongo.tar.bz2 > + tar xvf enron_mongo.tar > + mongorestore dump/enron_mail/messages.bson > +</code></pre></div> > +<p>We used <a href="http://robomongo.org/";>Robomongo</a> to visually > examine the dataset stored in MongoDB.</p> > + > +<p><img src="/img/blog/robomongo.png" style="width:90%;margin:15px"></p> > + > +<h4 id="build-mongoinputformat">Build <code>MongoInputFormat</code></h4> > + > +<p>MongoDB offers an InputFormat for Hadoop on their <a href=" > https://github.com/mongodb/mongo-hadoop";>GitHub page</a>. The code is not > available in any Maven repository, so we have to build the jar file on our > own.</p> > + > +<ul> > +<li>Check out the repository</li> > +</ul> > +<div class="highlight"><pre><code class="language-text" > data-lang="text">git clone https://github.com/mongodb/mongo-hadoop.git > +cd mongo-hadoop > +</code></pre></div> > +<ul> > +<li>Set the appropriate Hadoop version in the <code>build.sbt</code>, we > used <code>1.1</code>.</li> > +</ul> > +<div class="highlight"><pre><code class="language-bash" > data-lang="bash">hadoopRelease in ThisBuild :<span class="o">=</span> <span > class="s2">"1.1"</span> > +</code></pre></div> > +<ul> > +<li>Build the input format</li> > +</ul> > +<div class="highlight"><pre><code class="language-bash" > data-lang="bash">./sbt package > +</code></pre></div> > +<p>The jar-file is now located in <code>core/target</code>.</p> > + > +<h4 id="the-stratosphere-program">The Stratosphere Program</h4> > + > +<p>Now we have everything prepared to run the Stratosphere program. I > only ran it on my local computer, out of Eclipse. To do that, check out the > code ...</p> > +<div class="highlight"><pre><code class="language-bash" > data-lang="bash">git clone > https://github.com/stratosphere/stratosphere-mongodb-example.git > +</code></pre></div> > +<p>... and import it as a Maven project into your Eclipse. You have to > manually add the previously built mongo-hadoop jar-file as a dependency. > +You can now press the "Run" button and see how Stratosphere > executes the little program. It was running for about 8 seconds on the 1.5 > GB dataset.</p> > + > +<p>The result (located in <code>/tmp/enronCountByDay</code>) now looks > like this.</p> > +<div class="highlight"><pre><code class="language-text" > data-lang="text">11,Fri Sep 26 10:00:00 CEST 1997 > +154,Tue Jun 29 10:56:00 CEST 1999 > +292,Tue Aug 10 12:11:00 CEST 1999 > +185,Thu Aug 12 18:35:00 CEST 1999 > +26,Fri Mar 19 12:33:00 CET 1999 > +</code></pre></div> > +<p>There is one thing left I want to point out here. MongoDB represents > objects stored in the database as JSON-documents. Since Stratosphere's > standard types do not support JSON documents, I was using the > <code>WritableWrapper</code> here. This wrapper allows to use any Hadoop > datatype with Stratosphere.</p> > + > +<p>The following code example shows how the JSON-documents are accessed > in Stratosphere.</p> > +<div class="highlight"><pre><code class="language-java" > data-lang="java"><span class="kd">public</span> <span > class="kt">void</span> <span class="nf">map</span><span > class="o">(</span><span class="n">Record</span> <span > class="n">record</span><span class="o">,</span> <span > class="n">Collector</span><span class="o"><</span><span > class="n">Record</span><span class="o">></span> <span > class="n">out</span><span class="o">)</span> <span class="kd">throws</span> > <span class="n">Exception</span> <span class="o">{</span> > + <span class="n">Writable</span> <span class="n">valWr</span> <span > class="o">=</span> <span class="n">record</span><span > class="o">.</span><span class="na">getField</span><span > class="o">(</span><span class="mi">1</span><span class="o">,</span> <span > class="n">WritableWrapper</span><span class="o">.</span><span > class="na">class</span><span class="o">).</span><span > class="na">value</span><span class="o">();</span> > + <span class="n">BSONWritable</span> <span class="n">value</span> > <span class="o">=</span> <span class="o">(</span><span > class="n">BSONWritable</span><span class="o">)</span> <span > class="n">valWr</span><span class="o">;</span> > + <span class="n">Object</span> <span class="n">headers</span> <span > class="o">=</span> <span class="n">value</span><span > class="o">.</span><span class="na">getDoc</span><span > class="o">().</span><span class="na">get</span><span > class="o">(</span><span class="s">"headers"</span><span > class="o">);</span> > + <span class="n">BasicDBObject</span> <span class="n">headerOb</span> > <span class="o">=</span> <span class="o">(</span><span > class="n">BasicDBObject</span><span class="o">)</span> <span > class="n">headers</span><span class="o">;</span> > + <span class="n">String</span> <span class="n">date</span> <span > class="o">=</span> <span class="o">(</span><span > class="n">String</span><span class="o">)</span> <span > class="n">headerOb</span><span class="o">.</span><span > class="na">get</span><span class="o">(</span><span > class="s">"Date"</span><span class="o">);</span> > + <span class="c1">// further date processing</span> > +<span class="o">}</span> > +</code></pre></div> > +<p>Please use the comments if you have questions or if you want to > showcase your own MongoDB-Stratosphere integration. > +<br><br> > +<small>Written by Robert Metzger (<a href="https://twitter.com/rmetzger_ > ">@rmetzger_</a>).</small></p> > +</div> > + <a > href="/news/2014/01/28/querying_mongodb.html#disqus_thread">Accessing Data > Stored in MongoDB with Stratosphere</a> > + </article> > + > + <article> > <h2><a > href="/news/2014/01/26/optimizer_plan_visualization_tool.html">Optimizer > Plan Visualization Tool</a></h2> > <p class="meta">26 Jan 2014</p> > > @@ -448,24 +540,6 @@ Analyzing big data sets as they occur in > <a > href="/news/2012/11/12/btw2013demo.html#disqus_thread">Stratosphere Demo > Paper Accepted for BTW 2013</a> > </article> > > - <article> > - <h2><a > href="/news/2012/10/15/icde2013.html">Stratosphere Demo Accepted for ICDE > 2013</a></h2> > - <p class="meta">15 Oct 2012</p> > - > - <div> <p>Our demo submission<br /> > -<strong><cite>"Peeking into the Optimization of Data Flow Programs with > MapReduce-style UDFs"</cite></strong><br /> > -has been accepted for ICDE 2013 in Brisbane, Australia.<br /> > -The demo illustrates the contributions of our VLDB 2012 paper > <cite>"Opening the Black Boxes in Data Flow Optimization"</cite> <a > href="/assets/papers/optimizationOfDataFlowsWithUDFs_13.pdf">[PDF]</a> and > <a > href="/assets/papers/optimizationOfDataFlowsWithUDFs_poster_13.pdf">[Poster > PDF]</a>.</p> > -<p>Visit our poster, enjoy the demo, and talk to us if you are going to > attend ICDE 2013.</p> > -<p><strong>Abstract:</strong><br /> > -Data flows are a popular abstraction to define data-intensive processing > tasks. In order to support a wide range of use cases, many data processing > systems feature MapReduce-style user-defined functions (UDFs). In contrast > to UDFs as known from relational DBMS, MapReduce-style UDFs have less > strict templates. These templates do not alone provide all the information > needed to decide whether they can be reordered with relational operators > and other UDFs. However, it is well-known that reordering operators such as > filters, joins, and aggregations can yield runtime improvements by orders > of magnitude.<br /> > -We demonstrate an optimizer for data flows that is able to reorder > operators with MapReduce-style UDFs written in an imperative language. Our > approach leverages static code analysis to extract information from UDFs > which is used to reason about the reorderbility of UDF operators. This > information is sufficient to enumerate a large fraction of the search space > covered by conventional RDBMS optimizers including filter and aggregation > push-down, bushy join orders, and choice of physical execution strategies > based on interesting properties.<br /> > -We demonstrate our optimizer and a job submission client that allows > users to peek step-by-step into each phase of the optimization process: the > static code analysis of UDFs, the enumeration of reordered candidate data > flows, the generation of physical execution plans, and their parallel > execution. For the demonstration, we provide a selection of relational and > non-relational data flow programs which highlight the salient features of > our approach.</p> > - > -</div> > - <a > href="/news/2012/10/15/icde2013.html#disqus_thread">Stratosphere Demo > Accepted for ICDE 2013</a> > - </article> > - > </div> > <div class="col-md-2"></div> > </div> > > Modified: flink/site/blog/page3/index.html > URL: > http://svn.apache.org/viewvc/flink/site/blog/page3/index.html?rev=1650029&r1=1650028&r2=1650029&view=diff > > ============================================================================== > --- flink/site/blog/page3/index.html (original) > +++ flink/site/blog/page3/index.html Wed Jan 7 10:40:31 2015 > @@ -131,6 +131,24 @@ > <div class="col-md-8"> > > <article> > + <h2><a > href="/news/2012/10/15/icde2013.html">Stratosphere Demo Accepted for ICDE > 2013</a></h2> > + <p class="meta">15 Oct 2012</p> > + > + <div> <p>Our demo submission<br /> > +<strong><cite>"Peeking into the Optimization of Data Flow Programs with > MapReduce-style UDFs"</cite></strong><br /> > +has been accepted for ICDE 2013 in Brisbane, Australia.<br /> > +The demo illustrates the contributions of our VLDB 2012 paper > <cite>"Opening the Black Boxes in Data Flow Optimization"</cite> <a > href="/assets/papers/optimizationOfDataFlowsWithUDFs_13.pdf">[PDF]</a> and > <a > href="/assets/papers/optimizationOfDataFlowsWithUDFs_poster_13.pdf">[Poster > PDF]</a>.</p> > +<p>Visit our poster, enjoy the demo, and talk to us if you are going to > attend ICDE 2013.</p> > +<p><strong>Abstract:</strong><br /> > +Data flows are a popular abstraction to define data-intensive processing > tasks. In order to support a wide range of use cases, many data processing > systems feature MapReduce-style user-defined functions (UDFs). In contrast > to UDFs as known from relational DBMS, MapReduce-style UDFs have less > strict templates. These templates do not alone provide all the information > needed to decide whether they can be reordered with relational operators > and other UDFs. However, it is well-known that reordering operators such as > filters, joins, and aggregations can yield runtime improvements by orders > of magnitude.<br /> > +We demonstrate an optimizer for data flows that is able to reorder > operators with MapReduce-style UDFs written in an imperative language. Our > approach leverages static code analysis to extract information from UDFs > which is used to reason about the reorderbility of UDF operators. This > information is sufficient to enumerate a large fraction of the search space > covered by conventional RDBMS optimizers including filter and aggregation > push-down, bushy join orders, and choice of physical execution strategies > based on interesting properties.<br /> > +We demonstrate our optimizer and a job submission client that allows > users to peek step-by-step into each phase of the optimization process: the > static code analysis of UDFs, the enumeration of reordered candidate data > flows, the generation of physical execution plans, and their parallel > execution. For the demonstration, we provide a selection of relational and > non-relational data flow programs which highlight the salient features of > our approach.</p> > + > +</div> > + <a > href="/news/2012/10/15/icde2013.html#disqus_thread">Stratosphere Demo > Accepted for ICDE 2013</a> > + </article> > + > + <article> > <h2><a > href="/news/2012/08/21/release02.html">Version 0.2 Released</a></h2> > <p class="meta">21 Aug 2012</p> > > > Added: flink/site/news/2015/01/06/december-in-flink.html > URL: > http://svn.apache.org/viewvc/flink/site/news/2015/01/06/december-in-flink.html?rev=1650029&view=auto > > ============================================================================== > --- flink/site/news/2015/01/06/december-in-flink.html (added) > +++ flink/site/news/2015/01/06/december-in-flink.html Wed Jan 7 10:40:31 > 2015 > @@ -0,0 +1,339 @@ > +<!DOCTYPE html> > +<html lang="en"> > + <head> > + <meta charset="utf-8"> > + <meta http-equiv="X-UA-Compatible" content="IE=edge"> > + <meta 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community</h2> > + <p class="meta">06 Jan 2015</p> > + <div> > + <p>This is the first blog post of a > “newsletter†like series where we give a summary of the monthly > activity in the Flink community. As the Flink project grows, this can serve > as a "tl;dr" for people that are not following the Flink dev and > user mailing lists, or those that are simply overwhelmed by the traffic.</p> > + > +<h3 id="flink-graduation">Flink graduation</h3> > + > +<p>The biggest news is that the Apache board approved Flink as a > top-level Apache project! The Flink team is working closely with the Apache > press team for an official announcement, so stay tuned for details!</p> > + > +<h3 id="new-flink-website">New Flink website</h3> > + > +<p>The <a href="http://flink.apache.org";>Flink website</a> got a total > make-over, both in terms of appearance and content.</p> > + > +<h3 id="flink-irc-channel">Flink IRC channel</h3> > + > +<p>A new IRC channel called #flink was created at irc.freenode.org. An > easy way to access the IRC channel is through the <a href=" > http://webchat.freenode.net/";>web client</a>. Feel free to stop by to > ask anything or share your ideas about Apache Flink!</p> > + > +<h3 id="meetups-and-talks">Meetups and Talks</h3> > + > +<p>Apache Flink was presented in the <a href=" > http://www.meetup.com/Netherlands-Hadoop-User-Group/events/218635152";>Amsterdam > Hadoop User Group</a></p> > + > +<h2 id="notable-code-contributions">Notable code contributions</h2> > + > +<p><strong>Note:</strong> Code contributions listed here may not be part > of a release or even the current snapshot yet.</p> > + > +<h3 id="streaming-scala-api"><a href=" > https://github.com/apache/incubator-flink/pull/275";>Streaming Scala > API</a></h3> > + > +<p>The Flink Streaming Java API recently got its Scala counterpart. Once > merged, Flink Streaming users can use both Scala and Java for their > development. The Flink Streaming Scala API is built as a thin layer on top > of the Java API, making sure that the APIs are kept easily in sync.</p> > + > +<h3 id="intermediate-datasets"><a href=" > https://github.com/apache/incubator-flink/pull/254";>Intermediate > datasets</a></h3> > + > +<p>This pull request introduces a major change in the Flink runtime. > Currently, the Flink runtime is based on the notion of operators that > exchange data through channels. With the PR, intermediate data sets that > are produced by operators become first-class citizens in the runtime. While > this does not have any user-facing impact yet, it lays the groundwork for a > slew of future features such as blocking execution, fine-grained > fault-tolerance, and more efficient data sharing between cluster and > client.</p> > + > +<h3 id="configurable-execution-mode"><a href=" > https://github.com/apache/incubator-flink/pull/259";>Configurable > execution mode</a></h3> > + > +<p>This pull request allows the user to change the object-reuse > behaviour. Before this pull request, some operations would reuse objects > passed to the user function while others would always create new objects. > This introduces a system wide switch and changes all operators to either > reuse objects or don’t reuse objects.</p> > + > +<h3 id="distributed-coordination-via-akka"><a href=" > https://github.com/apache/incubator-flink/pull/149";>Distributed > Coordination via Akka</a></h3> > + > +<p>Another major change is a complete rewrite of the JobManager / > TaskManager components in Scala. In addition to that, the old RPC service > was replaced by Actors, using the Akka framework.</p> > + > +<h3 id="sorting-of-very-large-records"><a href=" > https://github.com/apache/incubator-flink/pull/249";>Sorting of very large > records</a></h3> > + > +<p>Flink's internal sort-algorithms were improved to better handle > large records (multiple 100s of megabytes or larger). Previously, the > system did in some cases hold instances of multiple large records, > resulting in high memory consumption and JVM heap thrashing. Through this > fix, large records are streamed through the operators, reducing the memory > consumption and GC pressure. The system now requires much less memory to > support algorithms that work on such large records.</p> > + > +<h3 id="kryo-serialization-as-the-new-default-fallback"><a href=" > https://github.com/apache/incubator-flink/pull/271";>Kryo Serialization as > the new default fallback</a></h3> > + > +<p>Flink’s build-in type serialization framework is handles all common > types very efficiently. Prior versions uses Avro to serialize types that > the built-in framework could not handle. > +Flink serialization system improved a lot over time and by now surpasses > the capabilities of Avro in many cases. Kryo now serves as the default > fallback serialization framework, supporting a much broader range of > types.</p> > + > +<h3 id="hadoop-filesystem-support"><a href=" > https://github.com/apache/incubator-flink/pull/268";>Hadoop FileSystem > support</a></h3> > + > +<p>This change permits users to use all file systems supported by Hadoop > with Flink. In practice this means that users can use Flink with Tachyon, > Google Cloud Storage (also out of the box Flink YARN support on Google > Compute Cloud), FTP and all the other file system implementations for > Hadoop.</p> > + > +<h2 id="heading-to-the-0.8.0-release">Heading to the 0.8.0 release</h2> > + > +<p>The community is working hard together with the Apache infra team to > migrate the Flink infrastructure to a top-level project. At the same time, > the Flink community is working on the Flink 0.8.0 release which should be > out very soon.</p> > + > + </div> > + </article> > + </div> > + <div class="col-md-2"></div> > + </div> > + <div class="row" style="padding-top:30px"> > + <div class="col-md-2"></div> > + <div class="col-md-8"> > + <div id="disqus_thread"></div> > + <script type="text/javascript"> > + /* * * CONFIGURATION VARIABLES: EDIT BEFORE > PASTING INTO YOUR WEBPAGE * * */ > + var disqus_shortname = 'stratosphere-eu'; // > required: replace example with your forum shortname > + > + /* * * DON'T EDIT BELOW THIS LINE * * */ > + (function() { > + var dsq = document.createElement('script'); > dsq.type = 'text/javascript'; dsq.async = true; > + dsq.src = '//' + disqus_shortname + '. > disqus.com/embed.js'; > + (document.getElementsByTagName('head')[0] || > document.getElementsByTagName('body')[0]).appendChild(dsq); > + })(); > + </script> > + <noscript>Please enable JavaScript to view the <a > href="http://disqus.com/?ref_noscript";>comments powered by > Disqus.</a></noscript> > + <a href="http://disqus.com"; > class="dsq-brlink">comments powered by <span > class="logo-disqus">Disqus</span></a> > + </div> > + <div class="col-md-2"></div> > + </div> > +</div> > + > + </div> > + <section id="af-upfooter" class="af-section"> > + <div class="container"> > + <p>Apache Flink is an effort undergoing incubation at The > Apache > + Software Foundation (ASF), sponsored by the Apache > Incubator PMC. > + Incubation is required of all newly accepted > projects until a further > + review indicates that the infrastructure, > communications, and > + decision making process have stabilized in a > manner consistent with > + other successful ASF projects. 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