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From mj...@apache.org
Subject [2/4] flink-web git commit: rebuild website
Date Fri, 11 Dec 2015 09:55:47 GMT
http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/blog/index.html
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diff --git a/content/blog/index.html b/content/blog/index.html
index a375a85..7ecedfb 100644
--- a/content/blog/index.html
+++ b/content/blog/index.html
@@ -160,6 +160,17 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a></h2>
+      <p>11 Dec 2015 by Matthias J. Sax (<a href="https://twitter.com/MatthiasJSax">@MatthiasJSax</a>)</p>
+
+      <p>In this blog post, we describe Flink's compatibility package for <a href="https://storm.apache.org">Apache Storm</a> that allows to embed Spouts (sources) and Bolts (operators) in a regular Flink streaming job. Furthermore, the compatibility package provides a Storm compatible API in order to execute whole Storm topologies with (almost) no code adaption.</p>
+
+      <p><a href="/news/2015/12/11/storm-compatibility.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a></h2>
       <p>04 Dec 2015 by Fabian Hueske (<a href="https://twitter.com/fhueske">@fhueske</a>)</p>
 
@@ -279,18 +290,6 @@ vertex-centric or gather-sum-apply to Flink dataflows.</p>
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2015/05/11/Juggling-with-Bits-and-Bytes.html">Juggling with Bits and Bytes</a></h2>
-      <p>11 May 2015 by Fabian Hüske (<a href="https://twitter.com/fhueske">@fhueske</a>)</p>
-
-      <p><p>Nowadays, a lot of open-source systems for analyzing large data sets are implemented in Java or other JVM-based programming languages. The most well-known example is Apache Hadoop, but also newer frameworks such as Apache Spark, Apache Drill, and also Apache Flink run on JVMs. A common challenge that JVM-based data analysis engines face is to store large amounts of data in memory - both for caching and for efficient processing such as sorting and joining of data. Managing the JVM memory well makes the difference between a system that is hard to configure and has unpredictable reliability and performance and a system that behaves robustly with few configuration knobs.</p>
-<p>In this blog post we discuss how Apache Flink manages memory, talk about its custom data de/serialization stack, and show how it operates on binary data.</p></p>
-
-      <p><a href="/news/2015/05/11/Juggling-with-Bits-and-Bytes.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -323,6 +322,16 @@ vertex-centric or gather-sum-apply to Flink dataflows.</p>
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a></li>
+      
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a></li>
       
       

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/blog/page2/index.html
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diff --git a/content/blog/page2/index.html b/content/blog/page2/index.html
index 3d3cfaa..d7a14d6 100644
--- a/content/blog/page2/index.html
+++ b/content/blog/page2/index.html
@@ -160,6 +160,18 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2015/05/11/Juggling-with-Bits-and-Bytes.html">Juggling with Bits and Bytes</a></h2>
+      <p>11 May 2015 by Fabian Hüske (<a href="https://twitter.com/fhueske">@fhueske</a>)</p>
+
+      <p><p>Nowadays, a lot of open-source systems for analyzing large data sets are implemented in Java or other JVM-based programming languages. The most well-known example is Apache Hadoop, but also newer frameworks such as Apache Spark, Apache Drill, and also Apache Flink run on JVMs. A common challenge that JVM-based data analysis engines face is to store large amounts of data in memory - both for caching and for efficient processing such as sorting and joining of data. Managing the JVM memory well makes the difference between a system that is hard to configure and has unpredictable reliability and performance and a system that behaves robustly with few configuration knobs.</p>
+<p>In this blog post we discuss how Apache Flink manages memory, talk about its custom data de/serialization stack, and show how it operates on binary data.</p></p>
+
+      <p><a href="/news/2015/05/11/Juggling-with-Bits-and-Bytes.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2015/04/13/release-0.9.0-milestone1.html">Announcing Flink 0.9.0-milestone1 preview release</a></h2>
       <p>13 Apr 2015</p>
 
@@ -286,19 +298,6 @@ and offers a new API including definition of flexible windows.</p>
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2014/11/04/release-0.7.0.html">Apache Flink 0.7.0 available</a></h2>
-      <p>04 Nov 2014</p>
-
-      <p><p>We are pleased to announce the availability of Flink 0.7.0. This release includes new user-facing features as well as performance and bug fixes, brings the Scala and Java APIs in sync, and introduces Flink Streaming. A total of 34 people have contributed to this release, a big thanks to all of them!</p>
-
-</p>
-
-      <p><a href="/news/2014/11/04/release-0.7.0.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -331,6 +330,16 @@ and offers a new API including definition of flexible windows.</p>
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a></li>
+      
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a></li>
       
       

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/blog/page3/index.html
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diff --git a/content/blog/page3/index.html b/content/blog/page3/index.html
index af2711f..2fbc678 100644
--- a/content/blog/page3/index.html
+++ b/content/blog/page3/index.html
@@ -160,6 +160,19 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2014/11/04/release-0.7.0.html">Apache Flink 0.7.0 available</a></h2>
+      <p>04 Nov 2014</p>
+
+      <p><p>We are pleased to announce the availability of Flink 0.7.0. This release includes new user-facing features as well as performance and bug fixes, brings the Scala and Java APIs in sync, and introduces Flink Streaming. A total of 34 people have contributed to this release, a big thanks to all of them!</p>
+
+</p>
+
+      <p><a href="/news/2014/11/04/release-0.7.0.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2014/10/03/upcoming_events.html">Upcoming Events</a></h2>
       <p>03 Oct 2014</p>
 
@@ -279,19 +292,6 @@ academic and open source project that Flink originates from.</p>
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2014/01/13/stratosphere-release-0.4.html">Stratosphere 0.4 Released</a></h2>
-      <p>13 Jan 2014</p>
-
-      <p><p>We are pleased to announce that version 0.4 of the Stratosphere system has been released. </p>
-
-</p>
-
-      <p><a href="/news/2014/01/13/stratosphere-release-0.4.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -324,6 +324,16 @@ academic and open source project that Flink originates from.</p>
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a></li>
+      
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a></li>
       
       

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/blog/page4/index.html
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diff --git a/content/blog/page4/index.html b/content/blog/page4/index.html
index 894ab73..86b4acf 100644
--- a/content/blog/page4/index.html
+++ b/content/blog/page4/index.html
@@ -160,6 +160,19 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2014/01/13/stratosphere-release-0.4.html">Stratosphere 0.4 Released</a></h2>
+      <p>13 Jan 2014</p>
+
+      <p><p>We are pleased to announce that version 0.4 of the Stratosphere system has been released. </p>
+
+</p>
+
+      <p><a href="/news/2014/01/13/stratosphere-release-0.4.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2014/01/12/0.4-migration-guide.html">Stratosphere Version 0.4 Migration Guide</a></h2>
       <p>12 Jan 2014</p>
 
@@ -351,6 +364,16 @@ We demonstrate our optimizer and a job submission client that allows users to pe
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a></li>
+      
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a></li>
       
       

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/img/blog/flink-storm.png
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http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/img/blog/smirk.png
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http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/index.html
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diff --git a/content/index.html b/content/index.html
index 4f1d587..68f43a3 100644
--- a/content/index.html
+++ b/content/index.html
@@ -231,6 +231,10 @@
 
     <ul class="list-group">
   
+      <li class="list-group-item"><span>11 Dec 2015</span> &raquo;
+        <a href="/news/2015/12/11/storm-compatibility.html">Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</a>
+      </li>
+  
       <li class="list-group-item"><span>04 Dec 2015</span> &raquo;
         <a href="/news/2015/12/04/Introducing-windows.html">Introducing Stream Windows in Apache Flink</a>
       </li>
@@ -246,10 +250,6 @@
       <li class="list-group-item"><span>16 Sep 2015</span> &raquo;
         <a href="/news/2015/09/16/off-heap-memory.html">Off-heap Memory in Apache Flink and the curious JIT compiler</a>
       </li>
-  
-      <li class="list-group-item"><span>03 Sep 2015</span> &raquo;
-        <a href="/news/2015/09/03/flink-forward.html">Announcing Flink Forward 2015</a>
-      </li>
 
 </ul>
 

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/news/2014/01/28/querying_mongodb.html
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diff --git a/content/news/2014/01/28/querying_mongodb.html b/content/news/2014/01/28/querying_mongodb.html
index 64c5e85..aad0153 100644
--- a/content/news/2014/01/28/querying_mongodb.html
+++ b/content/news/2014/01/28/querying_mongodb.html
@@ -161,16 +161,16 @@
 
 <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"><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">&quot;Input Lines&quot;</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>
+<div class="highlight"><pre><code class="language-java"><span class="n">HadoopDataSource</span> <span class="n">source</span> <span class="o">=</span> <span class="k">new</span> <span class="n">HadoopDataSource</span><span class="o">(</span><span class="k">new</span> <span class="n">TextInputFormat</span><span class="o">(),</span> <span class="k">new</span> <span class="n">JobConf</span><span class="o">(),</span> <span class="s">&quot;Input Lines&quot;</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="n">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"><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>
+<div class="highlight"><pre><code class="language-java"><span class="n">JobConf</span> <span class="n">conf</span> <span class="o">=</span> <span class="k">new</span> <span class="n">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">&quot;mongo.input.uri&quot;</span><span class="o">,</span><span class="s">&quot;mongodb://localhost:27017/enron_mail.messages&quot;</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">&quot;Read from Mongodb&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="nf">WritableWrapperConverter</span><span class="o">());</span></code></pre></div>
+<span class="n">HadoopDataSource</span> <span class="n">src</span> <span class="o">=</span> <span class="k">new</span> <span class="n">HadoopDataSource</span><span class="o">(</span><span class="k">new</span> <span class="n">MongoInputFormat</span><span class="o">(),</span> <span class="n">conf</span><span class="o">,</span> <span class="s">&quot;Read from Mongodb&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">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/~enron/">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>

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/news/2014/11/18/hadoop-compatibility.html
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diff --git a/content/news/2014/11/18/hadoop-compatibility.html b/content/news/2014/11/18/hadoop-compatibility.html
index 0db27fd..b15c4f9 100644
--- a/content/news/2014/11/18/hadoop-compatibility.html
+++ b/content/news/2014/11/18/hadoop-compatibility.html
@@ -196,25 +196,25 @@
   <span class="c1">// Setup Hadoop’s TextInputFormat</span>
   <span class="n">HadoopInputFormat</span><span class="o">&lt;</span><span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">&gt;</span> <span class="n">hadoopInputFormat</span> <span class="o">=</span> 
       <span class="k">new</span> <span class="n">HadoopInputFormat</span><span class="o">&lt;</span><span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">&gt;(</span>
-        <span class="k">new</span> <span class="nf">TextInputFormat</span><span class="o">(),</span> <span class="n">LongWritable</span><span class="o">.</span><span class="na">class</span><span class="o">,</span> <span class="n">Text</span><span class="o">.</span><span class="na">class</span><span class="o">,</span> <span class="k">new</span> <span class="nf">JobConf</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">hadoopInputFormat</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">inputPath</span><span class="o">));</span>
+        <span class="k">new</span> <span class="n">TextInputFormat</span><span class="o">(),</span> <span class="n">LongWritable</span><span class="o">.</span><span class="na">class</span><span class="o">,</span> <span class="n">Text</span><span class="o">.</span><span class="na">class</span><span class="o">,</span> <span class="k">new</span> <span class="n">JobConf</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">hadoopInputFormat</span><span class="o">.</span><span class="na">getJobConf</span><span class="o">(),</span> <span class="k">new</span> <span class="n">Path</span><span class="o">(</span><span class="n">inputPath</span><span class="o">));</span>
   
   <span class="c1">// Read a DataSet with the Hadoop InputFormat</span>
   <span class="n">DataSet</span><span class="o">&lt;</span><span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">&gt;&gt;</span> <span class="n">text</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">createInput</span><span class="o">(</span><span class="n">hadoopInputFormat</span><span class="o">);</span>
   <span class="n">DataSet</span><span class="o">&lt;</span><span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;&gt;</span> <span class="n">words</span> <span class="o">=</span> <span class="n">text</span>
     <span class="c1">// Wrap Tokenizer Mapper function</span>
-    <span class="o">.</span><span class="na">flatMap</span><span class="o">(</span><span class="k">new</span> <span class="n">HadoopMapFunction</span><span class="o">&lt;</span><span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">,</span> <span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(</span><span class="k">new</span> <span class="nf">Tokenizer</span><span class="o">()))</span>
+    <span class="o">.</span><span class="na">flatMap</span><span class="o">(</span><span class="k">new</span> <span class="n">HadoopMapFunction</span><span class="o">&lt;</span><span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">,</span> <span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(</span><span class="k">new</span> <span class="n">Tokenizer</span><span class="o">()))</span>
     <span class="o">.</span><span class="na">groupBy</span><span class="o">(</span><span class="mi">0</span><span class="o">)</span>
     <span class="c1">// Wrap Counter Reducer function (used as Reducer and Combiner)</span>
     <span class="o">.</span><span class="na">reduceGroup</span><span class="o">(</span><span class="k">new</span> <span class="n">HadoopReduceCombineFunction</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">,</span> <span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(</span>
-      <span class="k">new</span> <span class="nf">Counter</span><span class="o">(),</span> <span class="k">new</span> <span class="nf">Counter</span><span class="o">()));</span>
+      <span class="k">new</span> <span class="n">Counter</span><span class="o">(),</span> <span class="k">new</span> <span class="n">Counter</span><span class="o">()));</span>
         
   <span class="c1">// Setup Hadoop’s TextOutputFormat</span>
   <span class="n">HadoopOutputFormat</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;</span> <span class="n">hadoopOutputFormat</span> <span class="o">=</span> 
     <span class="k">new</span> <span class="n">HadoopOutputFormat</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(</span>
-      <span class="k">new</span> <span class="n">TextOutputFormat</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(),</span> <span class="k">new</span> <span class="nf">JobConf</span><span class="o">());</span>
+      <span class="k">new</span> <span class="n">TextOutputFormat</span><span class="o">&lt;</span><span class="n">Text</span><span class="o">,</span> <span class="n">LongWritable</span><span class="o">&gt;(),</span> <span class="k">new</span> <span class="n">JobConf</span><span class="o">());</span>
   <span class="n">hadoopOutputFormat</span><span class="o">.</span><span class="na">getJobConf</span><span class="o">().</span><span class="na">set</span><span class="o">(</span><span class="s">&quot;mapred.textoutputformat.separator&quot;</span><span class="o">,</span> <span class="s">&quot; &quot;</span><span class="o">);</span>
-  <span class="n">TextOutputFormat</span><span class="o">.</span><span class="na">setOutputPath</span><span class="o">(</span><span class="n">hadoopOutputFormat</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">outputPath</span><span class="o">));</span>
+  <span class="n">TextOutputFormat</span><span class="o">.</span><span class="na">setOutputPath</span><span class="o">(</span><span class="n">hadoopOutputFormat</span><span class="o">.</span><span class="na">getJobConf</span><span class="o">(),</span> <span class="k">new</span> <span class="n">Path</span><span class="o">(</span><span class="n">outputPath</span><span class="o">));</span>
         
   <span class="c1">// Output &amp; Execute</span>
   <span class="n">words</span><span class="o">.</span><span class="na">output</span><span class="o">(</span><span class="n">hadoopOutputFormat</span><span class="o">);</span>

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/news/2015/02/09/streaming-example.html
----------------------------------------------------------------------
diff --git a/content/news/2015/02/09/streaming-example.html b/content/news/2015/02/09/streaming-example.html
index e60e63e..ad07284 100644
--- a/content/news/2015/02/09/streaming-example.html
+++ b/content/news/2015/02/09/streaming-example.html
@@ -245,16 +245,16 @@ found <a href="https://github.com/mbalassi/flink/blob/stockprices/flink-staging/
                 <span class="nd">@Override</span>
                 <span class="kd">public</span> <span class="n">StockPrice</span> <span class="nf">map</span><span class="o">(</span><span class="n">String</span> <span class="n">value</span><span class="o">)</span> <span class="kd">throws</span> <span class="n">Exception</span> <span class="o">{</span>
                     <span class="n">tokens</span> <span class="o">=</span> <span class="n">value</span><span class="o">.</span><span class="na">split</span><span class="o">(</span><span class="s">&quot;,&quot;</span><span class="o">);</span>
-                    <span class="k">return</span> <span class="k">new</span> <span class="nf">StockPrice</span><span class="o">(</span><span class="n">tokens</span><span class="o">[</span><span class="mi">0</span><span class="o">],</span>
+                    <span class="k">return</span> <span class="k">new</span> <span class="n">StockPrice</span><span class="o">(</span><span class="n">tokens</span><span class="o">[</span><span class="mi">0</span><span class="o">],</span>
                         <span class="n">Double</span><span class="o">.</span><span class="na">parseDouble</span><span class="o">(</span><span class="n">tokens</span><span class="o">[</span><span class="mi">1</span><span class="o">]));</span>
                 <span class="o">}</span>
             <span class="o">});</span>
 
     <span class="c1">//Generate other stock streams</span>
-    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">SPX_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockSource</span><span class="o">(</span><span class="s">&quot;SPX&quot;</span><span class="o">,</span> <span class="mi">10</span><span class="o">));</span>
-    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">FTSE_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockSource</span><span class="o">(</span><span class="s">&quot;FTSE&quot;</span><span class="o">,</span> <span class="mi">20</span><span class="o">));</span>
-    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">DJI_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockSource</span><span class="o">(</span><span class="s">&quot;DJI&quot;</span><span class="o">,</span> <span class="mi">30</span><span class="o">));</span>
-    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">BUX_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockSource</span><span class="o">(</span><span class="s">&quot;BUX&quot;</span><span class="o">,</span> <span class="mi">40</span><span class="o">));</span>
+    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">SPX_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="n">StockSource</span><span class="o">(</span><span class="s">&quot;SPX&quot;</span><span class="o">,</span> <span class="mi">10</span><span class="o">));</span>
+    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">FTSE_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="n">StockSource</span><span class="o">(</span><span class="s">&quot;FTSE&quot;</span><span class="o">,</span> <span class="mi">20</span><span class="o">));</span>
+    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">DJI_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="n">StockSource</span><span class="o">(</span><span class="s">&quot;DJI&quot;</span><span class="o">,</span> <span class="mi">30</span><span class="o">));</span>
+    <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">BUX_stream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="n">StockSource</span><span class="o">(</span><span class="s">&quot;BUX&quot;</span><span class="o">,</span> <span class="mi">40</span><span class="o">));</span>
 
     <span class="c1">//Merge all stock streams together</span>
     <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">stockStream</span> <span class="o">=</span> <span class="n">socketStockStream</span>
@@ -335,11 +335,11 @@ of this example, the data streams are simply generated using the
     <span class="nd">@Override</span>
     <span class="kd">public</span> <span class="kt">void</span> <span class="nf">invoke</span><span class="o">(</span><span class="n">Collector</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">collector</span><span class="o">)</span> <span class="kd">throws</span> <span class="n">Exception</span> <span class="o">{</span>
         <span class="n">price</span> <span class="o">=</span> <span class="n">DEFAULT_PRICE</span><span class="o">;</span>
-        <span class="n">Random</span> <span class="n">random</span> <span class="o">=</span> <span class="k">new</span> <span class="nf">Random</span><span class="o">();</span>
+        <span class="n">Random</span> <span class="n">random</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Random</span><span class="o">();</span>
 
         <span class="k">while</span> <span class="o">(</span><span class="kc">true</span><span class="o">)</span> <span class="o">{</span>
             <span class="n">price</span> <span class="o">=</span> <span class="n">price</span> <span class="o">+</span> <span class="n">random</span><span class="o">.</span><span class="na">nextGaussian</span><span class="o">()</span> <span class="o">*</span> <span class="n">sigma</span><span class="o">;</span>
-            <span class="n">collector</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockPrice</span><span class="o">(</span><span class="n">symbol</span><span class="o">,</span> <span class="n">price</span><span class="o">));</span>
+            <span class="n">collector</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="n">StockPrice</span><span class="o">(</span><span class="n">symbol</span><span class="o">,</span> <span class="n">price</span><span class="o">));</span>
             <span class="n">Thread</span><span class="o">.</span><span class="na">sleep</span><span class="o">(</span><span class="n">random</span><span class="o">.</span><span class="na">nextInt</span><span class="o">(</span><span class="mi">200</span><span class="o">));</span>
         <span class="o">}</span>
     <span class="o">}</span>
@@ -426,7 +426,7 @@ performed on named fields of POJOs, making the code more readable.</p>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">maxByStock</span> <span class="o">=</span> <span class="n">windowedStream</span><span class="o">.</span><span class="na">groupBy</span><span class="o">(</span><span class="s">&quot;symbol&quot;</span><span class="o">)</span>
     <span class="o">.</span><span class="na">maxBy</span><span class="o">(</span><span class="s">&quot;price&quot;</span><span class="o">).</span><span class="na">flatten</span><span class="o">();</span>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">StockPrice</span><span class="o">&gt;</span> <span class="n">rollingMean</span> <span class="o">=</span> <span class="n">windowedStream</span><span class="o">.</span><span class="na">groupBy</span><span class="o">(</span><span class="s">&quot;symbol&quot;</span><span class="o">)</span>
-    <span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="nf">WindowMean</span><span class="o">()).</span><span class="na">flatten</span><span class="o">();</span>
+    <span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="n">WindowMean</span><span class="o">()).</span><span class="na">flatten</span><span class="o">();</span>
 
 <span class="c1">//Compute the mean of a window</span>
 <span class="kd">public</span> <span class="kd">final</span> <span class="kd">static</span> <span class="kd">class</span> <span class="nc">WindowMean</span> <span class="kd">implements</span> 
@@ -446,7 +446,7 @@ performed on named fields of POJOs, making the code more readable.</p>
                 <span class="n">symbol</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="na">symbol</span><span class="o">;</span>
                 <span class="n">count</span><span class="o">++;</span>
             <span class="o">}</span>
-            <span class="n">out</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="nf">StockPrice</span><span class="o">(</span><span class="n">symbol</span><span class="o">,</span> <span class="n">sum</span> <span class="o">/</span> <span class="n">count</span><span class="o">));</span>
+            <span class="n">out</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="n">StockPrice</span><span class="o">(</span><span class="n">symbol</span><span class="o">,</span> <span class="n">sum</span> <span class="o">/</span> <span class="n">count</span><span class="o">));</span>
         <span class="o">}</span>
     <span class="o">}</span>
 <span class="o">}</span></code></pre></div>
@@ -506,7 +506,7 @@ every 30 seconds.</p>
   <div data-lang="java7">
 
     <div class="highlight"><pre><code class="language-java" data-lang="java"><span class="kd">private</span> <span class="kd">static</span> <span class="kd">final</span> <span class="n">Double</span> <span class="n">DEFAULT_PRICE</span> <span class="o">=</span> <span class="mi">1000</span><span class="o">.;</span>
-<span class="kd">private</span> <span class="kd">static</span> <span class="kd">final</span> <span class="n">StockPrice</span> <span class="n">DEFAULT_STOCK_PRICE</span> <span class="o">=</span> <span class="k">new</span> <span class="nf">StockPrice</span><span class="o">(</span><span class="s">&quot;&quot;</span><span class="o">,</span> <span class="n">DEFAULT_PRICE</span><span class="o">);</span>
+<span class="kd">private</span> <span class="kd">static</span> <span class="kd">final</span> <span class="n">StockPrice</span> <span class="n">DEFAULT_STOCK_PRICE</span> <span class="o">=</span> <span class="k">new</span> <span class="n">StockPrice</span><span class="o">(</span><span class="s">&quot;&quot;</span><span class="o">,</span> <span class="n">DEFAULT_PRICE</span><span class="o">);</span>
 
 <span class="c1">//Use delta policy to create price change warnings</span>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;</span> <span class="n">priceWarnings</span> <span class="o">=</span> <span class="n">stockStream</span><span class="o">.</span><span class="na">groupBy</span><span class="o">(</span><span class="s">&quot;symbol&quot;</span><span class="o">)</span>
@@ -516,13 +516,13 @@ every 30 seconds.</p>
             <span class="k">return</span> <span class="n">Math</span><span class="o">.</span><span class="na">abs</span><span class="o">(</span><span class="n">oldDataPoint</span><span class="o">.</span><span class="na">price</span> <span class="o">-</span> <span class="n">newDataPoint</span><span class="o">.</span><span class="na">price</span><span class="o">);</span>
         <span class="o">}</span>
     <span class="o">},</span> <span class="n">DEFAULT_STOCK_PRICE</span><span class="o">))</span>
-<span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="nf">SendWarning</span><span class="o">()).</span><span class="na">flatten</span><span class="o">();</span>
+<span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="n">SendWarning</span><span class="o">()).</span><span class="na">flatten</span><span class="o">();</span>
 
 <span class="c1">//Count the number of warnings every half a minute</span>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Count</span><span class="o">&gt;</span> <span class="n">warningsPerStock</span> <span class="o">=</span> <span class="n">priceWarnings</span><span class="o">.</span><span class="na">map</span><span class="o">(</span><span class="k">new</span> <span class="n">MapFunction</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Count</span><span class="o">&gt;()</span> <span class="o">{</span>
     <span class="nd">@Override</span>
     <span class="kd">public</span> <span class="n">Count</span> <span class="nf">map</span><span class="o">(</span><span class="n">String</span> <span class="n">value</span><span class="o">)</span> <span class="kd">throws</span> <span class="n">Exception</span> <span class="o">{</span>
-        <span class="k">return</span> <span class="k">new</span> <span class="nf">Count</span><span class="o">(</span><span class="n">value</span><span class="o">,</span> <span class="mi">1</span><span class="o">);</span>
+        <span class="k">return</span> <span class="k">new</span> <span class="n">Count</span><span class="o">(</span><span class="n">value</span><span class="o">,</span> <span class="mi">1</span><span class="o">);</span>
     <span class="o">}</span>
 <span class="o">}).</span><span class="na">groupBy</span><span class="o">(</span><span class="s">&quot;symbol&quot;</span><span class="o">).</span><span class="na">window</span><span class="o">(</span><span class="n">Time</span><span class="o">.</span><span class="na">of</span><span class="o">(</span><span class="mi">30</span><span class="o">,</span> <span class="n">TimeUnit</span><span class="o">.</span><span class="na">SECONDS</span><span class="o">)).</span><span class="na">sum</span><span class="o">(</span><span class="s">&quot;count&quot;</span><span class="o">).</span><span class="na">flatten</span><span class="o">();</span>
 
@@ -604,7 +604,7 @@ but for the sake of this example we generate dummy tweet data.</p>
   <div data-lang="java7">
 
     <div class="highlight"><pre><code class="language-java" data-lang="java"><span class="c1">//Read a stream of tweets</span>
-<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;</span> <span class="n">tweetStream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="nf">TweetSource</span><span class="o">());</span>
+<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;</span> <span class="n">tweetStream</span> <span class="o">=</span> <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="k">new</span> <span class="n">TweetSource</span><span class="o">());</span>
 
 <span class="c1">//Extract the stock symbols</span>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;</span> <span class="n">mentionedSymbols</span> <span class="o">=</span> <span class="n">tweetStream</span><span class="o">.</span><span class="na">flatMap</span><span class="o">(</span>
@@ -627,7 +627,7 @@ but for the sake of this example we generate dummy tweet data.</p>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Count</span><span class="o">&gt;</span> <span class="n">tweetsPerStock</span> <span class="o">=</span> <span class="n">mentionedSymbols</span><span class="o">.</span><span class="na">map</span><span class="o">(</span><span class="k">new</span> <span class="n">MapFunction</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">Count</span><span class="o">&gt;()</span> <span class="o">{</span>
     <span class="nd">@Override</span>
     <span class="kd">public</span> <span class="n">Count</span> <span class="nf">map</span><span class="o">(</span><span class="n">String</span> <span class="n">value</span><span class="o">)</span> <span class="kd">throws</span> <span class="n">Exception</span> <span class="o">{</span>
-        <span class="k">return</span> <span class="k">new</span> <span class="nf">Count</span><span class="o">(</span><span class="n">value</span><span class="o">,</span> <span class="mi">1</span><span class="o">);</span>
+        <span class="k">return</span> <span class="k">new</span> <span class="n">Count</span><span class="o">(</span><span class="n">value</span><span class="o">,</span> <span class="mi">1</span><span class="o">);</span>
     <span class="o">}</span>
 <span class="o">}).</span><span class="na">groupBy</span><span class="o">(</span><span class="s">&quot;symbol&quot;</span><span class="o">).</span><span class="na">window</span><span class="o">(</span><span class="n">Time</span><span class="o">.</span><span class="na">of</span><span class="o">(</span><span class="mi">30</span><span class="o">,</span> <span class="n">TimeUnit</span><span class="o">.</span><span class="na">SECONDS</span><span class="o">)).</span><span class="na">sum</span><span class="o">(</span><span class="s">&quot;count&quot;</span><span class="o">).</span><span class="na">flatten</span><span class="o">();</span>
 
@@ -637,8 +637,8 @@ but for the sake of this example we generate dummy tweet data.</p>
 
     <span class="nd">@Override</span>
     <span class="kd">public</span> <span class="kt">void</span> <span class="nf">invoke</span><span class="o">(</span><span class="n">Collector</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;</span> <span class="n">collector</span><span class="o">)</span> <span class="kd">throws</span> <span class="n">Exception</span> <span class="o">{</span>
-        <span class="n">random</span> <span class="o">=</span> <span class="k">new</span> <span class="nf">Random</span><span class="o">();</span>
-        <span class="n">stringBuilder</span> <span class="o">=</span> <span class="k">new</span> <span class="nf">StringBuilder</span><span class="o">();</span>
+        <span class="n">random</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Random</span><span class="o">();</span>
+        <span class="n">stringBuilder</span> <span class="o">=</span> <span class="k">new</span> <span class="n">StringBuilder</span><span class="o">();</span>
 
         <span class="k">while</span> <span class="o">(</span><span class="kc">true</span><span class="o">)</span> <span class="o">{</span>
             <span class="n">stringBuilder</span><span class="o">.</span><span class="na">setLength</span><span class="o">(</span><span class="mi">0</span><span class="o">);</span>
@@ -720,7 +720,7 @@ these data streams are potentially infinite, we apply the join on a
 <span class="c1">//Compute rolling correlation</span>
 <span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Double</span><span class="o">&gt;</span> <span class="n">rollingCorrelation</span> <span class="o">=</span> <span class="n">tweetsAndWarning</span>
     <span class="o">.</span><span class="na">window</span><span class="o">(</span><span class="n">Time</span><span class="o">.</span><span class="na">of</span><span class="o">(</span><span class="mi">30</span><span class="o">,</span> <span class="n">TimeUnit</span><span class="o">.</span><span class="na">SECONDS</span><span class="o">))</span>
-    <span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="nf">WindowCorrelation</span><span class="o">());</span>
+    <span class="o">.</span><span class="na">mapWindow</span><span class="o">(</span><span class="k">new</span> <span class="n">WindowCorrelation</span><span class="o">());</span>
 
 <span class="n">rollingCorrelation</span><span class="o">.</span><span class="na">print</span><span class="o">();</span>
 

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/news/2015/08/24/introducing-flink-gelly.html
----------------------------------------------------------------------
diff --git a/content/news/2015/08/24/introducing-flink-gelly.html b/content/news/2015/08/24/introducing-flink-gelly.html
index 2bc2f8a..a414072 100644
--- a/content/news/2015/08/24/introducing-flink-gelly.html
+++ b/content/news/2015/08/24/introducing-flink-gelly.html
@@ -232,7 +232,7 @@ of vertices, edges and the node degrees. </p>
 the ones provided by the batch processing API. These transformations can be applied one after the
 other, yielding a new Graph after each step, in a fashion similar to operators on DataSets: </p>
 
-<div class="highlight"><pre><code class="language-java"><span class="n">inputGraph</span><span class="o">.</span><span class="na">getUndirected</span><span class="o">().</span><span class="na">mapEdges</span><span class="o">(</span><span class="k">new</span> <span class="nf">CustomEdgeMapper</span><span class="o">());</span></code></pre></div>
+<div class="highlight"><pre><code class="language-java"><span class="n">inputGraph</span><span class="o">.</span><span class="na">getUndirected</span><span class="o">().</span><span class="na">mapEdges</span><span class="o">(</span><span class="k">new</span> <span class="n">CustomEdgeMapper</span><span class="o">());</span></code></pre></div>
 
 <p>Transformations can be applied on:</p>
 
@@ -268,7 +268,7 @@ one or more values per vertex, the more general  <code>groupReduceOnEdges()</cod
 <p>Assume you would want to compute the sum of the values of all incoming neighbors for each vertex.
 We will call the <code>reduceOnNeighbors()</code> aggregation method since the sum is an associative and commutative operation and the neighbors’ values are needed:</p>
 
-<div class="highlight"><pre><code class="language-java"><span class="n">graph</span><span class="o">.</span><span class="na">reduceOnNeighbors</span><span class="o">(</span><span class="k">new</span> <span class="nf">SumValues</span><span class="o">(),</span> <span class="n">EdgeDirection</span><span class="o">.</span><span class="na">IN</span><span class="o">);</span></code></pre></div>
+<div class="highlight"><pre><code class="language-java"><span class="n">graph</span><span class="o">.</span><span class="na">reduceOnNeighbors</span><span class="o">(</span><span class="k">new</span> <span class="n">SumValues</span><span class="o">(),</span> <span class="n">EdgeDirection</span><span class="o">.</span><span class="na">IN</span><span class="o">);</span></code></pre></div>
 
 <p>The vertex with id 1 is the only node that has no incoming edges. The result is therefore:</p>
 
@@ -454,7 +454,7 @@ playlist, we use a coGroup function to filter out the mismatches.</p>
 <span class="c1">// read the mismatches dataset and extract the songIDs</span>
 <span class="n">DataSet</span><span class="o">&lt;</span><span class="n">Tuple3</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span> <span class="n">String</span><span class="o">,</span> <span class="n">Integer</span><span class="o">&gt;&gt;</span> <span class="n">validTriplets</span> <span class="o">=</span> <span class="n">triplets</span>
         <span class="o">.</span><span class="na">coGroup</span><span class="o">(</span><span class="n">mismatches</span><span class="o">).</span><span class="na">where</span><span class="o">(</span><span class="mi">1</span><span class="o">).</span><span class="na">equalTo</span><span class="o">(</span><span class="mi">0</span><span class="o">)</span>
-        <span class="o">.</span><span class="na">with</span><span class="o">(</span><span class="k">new</span> <span class="nf">CoGroupFunction</span><span class="o">()</span> <span class="o">{</span>
+        <span class="o">.</span><span class="na">with</span><span class="o">(</span><span class="k">new</span> <span class="n">CoGroupFunction</span><span class="o">()</span> <span class="o">{</span>
                 <span class="kt">void</span> <span class="nf">coGroup</span><span class="o">(</span><span class="n">Iterable</span> <span class="n">triplets</span><span class="o">,</span> <span class="n">Iterable</span> <span class="n">invalidSongs</span><span class="o">,</span> <span class="n">Collector</span> <span class="n">out</span><span class="o">)</span> <span class="o">{</span>
                         <span class="k">if</span> <span class="o">(!</span><span class="n">invalidSongs</span><span class="o">.</span><span class="na">iterator</span><span class="o">().</span><span class="na">hasNext</span><span class="o">())</span> <span class="o">{</span>
                             <span class="k">for</span> <span class="o">(</span><span class="n">Tuple3</span> <span class="n">triplet</span> <span class="o">:</span> <span class="n">triplets</span><span class="o">)</span> <span class="o">{</span> <span class="c1">// valid triplet</span>
@@ -492,7 +492,7 @@ basically iterate through the edge value and collect the target (song) of the ma
 
 <div class="highlight"><pre><code class="language-java"><span class="c1">//get the top track (most listened to) for each user</span>
 <span class="n">DataSet</span><span class="o">&lt;</span><span class="n">Tuple2</span><span class="o">&gt;</span> <span class="n">usersWithTopTrack</span> <span class="o">=</span> <span class="n">userSongGraph</span>
-        <span class="o">.</span><span class="na">groupReduceOnEdges</span><span class="o">(</span><span class="k">new</span> <span class="nf">GetTopSongPerUser</span><span class="o">(),</span> <span class="n">EdgeDirection</span><span class="o">.</span><span class="na">OUT</span><span class="o">);</span>
+        <span class="o">.</span><span class="na">groupReduceOnEdges</span><span class="o">(</span><span class="k">new</span> <span class="n">GetTopSongPerUser</span><span class="o">(),</span> <span class="n">EdgeDirection</span><span class="o">.</span><span class="na">OUT</span><span class="o">);</span>
 
 <span class="kd">class</span> <span class="nc">GetTopSongPerUser</span> <span class="kd">implements</span> <span class="n">EdgesFunctionWithVertexValue</span> <span class="o">{</span>
     <span class="kt">void</span> <span class="nf">iterateEdges</span><span class="o">(</span><span class="n">Vertex</span> <span class="n">vertex</span><span class="o">,</span> <span class="n">Iterable</span><span class="o">&lt;</span><span class="n">Edge</span><span class="o">&gt;</span> <span class="n">edges</span><span class="o">)</span> <span class="o">{</span>
@@ -505,7 +505,7 @@ basically iterate through the edge value and collect the target (song) of the ma
                 <span class="n">topSong</span> <span class="o">=</span> <span class="n">edge</span><span class="o">.</span><span class="na">getTarget</span><span class="o">();</span>
             <span class="o">}</span>
         <span class="o">}</span>
-        <span class="k">return</span> <span class="k">new</span> <span class="nf">Tuple2</span><span class="o">(</span><span class="n">vertex</span><span class="o">.</span><span class="na">getId</span><span class="o">(),</span> <span class="n">topSong</span><span class="o">);</span>
+        <span class="k">return</span> <span class="k">new</span> <span class="n">Tuple2</span><span class="o">(</span><span class="n">vertex</span><span class="o">.</span><span class="na">getId</span><span class="o">(),</span> <span class="n">topSong</span><span class="o">);</span>
     <span class="o">}</span>
 <span class="o">}</span></code></pre></div>
 
@@ -541,14 +541,14 @@ straightforward as a call to the <code>Graph.fromDataSet()</code> method.</p>
                 <span class="o">}</span>
         <span class="o">})</span>
         <span class="o">.</span><span class="na">groupBy</span><span class="o">(</span><span class="mi">1</span><span class="o">)</span>
-        <span class="o">.</span><span class="na">reduceGroup</span><span class="o">(</span><span class="k">new</span> <span class="nf">GroupReduceFunction</span><span class="o">()</span> <span class="o">{</span>
+        <span class="o">.</span><span class="na">reduceGroup</span><span class="o">(</span><span class="k">new</span> <span class="n">GroupReduceFunction</span><span class="o">()</span> <span class="o">{</span>
                 <span class="kt">void</span> <span class="nf">reduce</span><span class="o">(</span><span class="n">Iterable</span><span class="o">&lt;</span><span class="n">Edge</span><span class="o">&gt;</span> <span class="n">edges</span><span class="o">,</span> <span class="n">Collector</span><span class="o">&lt;</span><span class="n">Edge</span><span class="o">&gt;</span> <span class="n">out</span><span class="o">)</span> <span class="o">{</span>
-                    <span class="n">List</span> <span class="n">users</span> <span class="o">=</span> <span class="k">new</span> <span class="nf">ArrayList</span><span class="o">();</span>
+                    <span class="n">List</span> <span class="n">users</span> <span class="o">=</span> <span class="k">new</span> <span class="n">ArrayList</span><span class="o">();</span>
                     <span class="k">for</span> <span class="o">(</span><span class="n">Edge</span> <span class="n">edge</span> <span class="o">:</span> <span class="n">edges</span><span class="o">)</span> <span class="o">{</span>
                         <span class="n">users</span><span class="o">.</span><span class="na">add</span><span class="o">(</span><span class="n">edge</span><span class="o">.</span><span class="na">getSource</span><span class="o">());</span>
                         <span class="k">for</span> <span class="o">(</span><span class="kt">int</span> <span class="n">i</span> <span class="o">=</span> <span class="mi">0</span><span class="o">;</span> <span class="n">i</span> <span class="o">&lt;</span> <span class="n">users</span><span class="o">.</span><span class="na">size</span><span class="o">()</span> <span class="o">-</span> <span class="mi">1</span><span class="o">;</span> <span class="n">i</span><span class="o">++)</span> <span class="o">{</span>
                             <span class="k">for</span> <span class="o">(</span><span class="kt">int</span> <span class="n">j</span> <span class="o">=</span> <span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="o">;</span> <span class="n">j</span> <span class="o">&lt;</span> <span class="n">users</span><span class="o">.</span><span class="na">size</span><span class="o">()</span> <span class="o">-</span> <span class="mi">1</span><span class="o">;</span> <span class="n">j</span><span class="o">++)</span> <span class="o">{</span>
-                                <span class="n">out</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="nf">Edge</span><span class="o">(</span><span class="n">users</span><span class="o">.</span><span class="na">get</span><span class="o">(</span><span class="n">i</span><span class="o">),</span> <span class="n">users</span><span class="o">.</span><span class="na">get</span><span class="o">(</span><span class="n">j</span><span class="o">)));</span>
+                                <span class="n">out</span><span class="o">.</span><span class="na">collect</span><span class="o">(</span><span class="k">new</span> <span class="n">Edge</span><span class="o">(</span><span class="n">users</span><span class="o">.</span><span class="na">get</span><span class="o">(</span><span class="n">i</span><span class="o">),</span> <span class="n">users</span><span class="o">.</span><span class="na">get</span><span class="o">(</span><span class="n">j</span><span class="o">)));</span>
                             <span class="o">}</span>
                         <span class="o">}</span>
                     <span class="o">}</span>
@@ -579,12 +579,12 @@ among their neighbors. </p>
 
 <span class="c1">// update the vertex values and run the label propagation algorithm</span>
 <span class="n">DataSet</span><span class="o">&lt;</span><span class="n">Vertex</span><span class="o">&gt;</span> <span class="n">verticesWithCommunity</span> <span class="o">=</span> <span class="n">similarUsersGraph</span>
-        <span class="o">.</span><span class="na">joinWithVertices</span><span class="o">(</span><span class="n">idsWithlLabels</span><span class="o">,</span> <span class="k">new</span> <span class="nf">MapFunction</span><span class="o">()</span> <span class="o">{</span>
+        <span class="o">.</span><span class="na">joinWithVertices</span><span class="o">(</span><span class="n">idsWithlLabels</span><span class="o">,</span> <span class="k">new</span> <span class="n">MapFunction</span><span class="o">()</span> <span class="o">{</span>
                 <span class="kd">public</span> <span class="n">Long</span> <span class="nf">map</span><span class="o">(</span><span class="n">Tuple2</span> <span class="n">idWithLabel</span><span class="o">)</span> <span class="o">{</span>
                     <span class="k">return</span> <span class="n">idWithLabel</span><span class="o">.</span><span class="na">f1</span><span class="o">;</span>
                 <span class="o">}</span>
         <span class="o">})</span>
-        <span class="o">.</span><span class="na">run</span><span class="o">(</span><span class="k">new</span> <span class="nf">LabelPropagation</span><span class="o">(</span><span class="n">numIterations</span><span class="o">))</span>
+        <span class="o">.</span><span class="na">run</span><span class="o">(</span><span class="k">new</span> <span class="n">LabelPropagation</span><span class="o">(</span><span class="n">numIterations</span><span class="o">))</span>
         <span class="o">.</span><span class="na">getVertices</span><span class="o">();</span></code></pre></div>
 
 <p><a href="#top">Back to top</a></p>

http://git-wip-us.apache.org/repos/asf/flink-web/blob/1e63786d/content/news/2015/12/11/storm-compatibility.html
----------------------------------------------------------------------
diff --git a/content/news/2015/12/11/storm-compatibility.html b/content/news/2015/12/11/storm-compatibility.html
new file mode 100644
index 0000000..1ec4470
--- /dev/null
+++ b/content/news/2015/12/11/storm-compatibility.html
@@ -0,0 +1,346 @@
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+<html lang="en">
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+      <h1>Storm Compatibility in Apache Flink: How to run existing Storm topologies on Flink</h1>
+
+      <article>
+        <p>11 Dec 2015 by Matthias J. Sax (<a href="https://twitter.com/MatthiasJSax">@MatthiasJSax</a>)</p>
+
+<p><a href="https://storm.apache.org">Apache Storm</a> was one of the first distributed and scalable stream processing systems available in the open source space offering (near) real-time tuple-by-tuple processing semantics.
+Initially released by the developers at Backtype in 2011 under the Eclipse open-source license, it became popular very quickly.
+Only shortly afterwards, Twitter acquired Backtype.
+Since then, Storm has been growing in popularity, is used in production at many big companies, and is the de-facto industry standard for big data stream processing.
+In 2013, Storm entered the Apache incubator program, followed by its graduation to top-level in 2014.</p>
+
+<p>Apache Flink is a stream processing engine that improves upon older technologies like Storm in several dimensions,
+including <a href="https://ci.apache.org/projects/flink/flink-docs-master/internals/stream_checkpointing.html">strong consistency guarantees</a> (“exactly once”),
+a higher level <a href="https://ci.apache.org/projects/flink/flink-docs-master/apis/streaming_guide.html">DataStream API</a>,
+support for <a href="http://flink.apache.org/news/2015/12/04/Introducing-windows.html">event time and a rich windowing system</a>,
+as well as <a href="https://data-artisans.com/high-throughput-low-latency-and-exactly-once-stream-processing-with-apache-flink/">superior throughput with competitive low latency</a>.</p>
+
+<p>While Flink offers several technical benefits over Storm, an existing investment on a codebase of applications developed for Storm often makes it difficult to switch engines.
+For these reasons, as part of the Flink 0.10 release, Flink ships with a Storm compatibility package that allows users to:</p>
+
+<ul>
+  <li>Run <strong>unmodified</strong> Storm topologies using Apache Flink benefiting from superior performance.</li>
+  <li><strong>Embed</strong> Storm code (spouts and bolts) as operators inside Flink DataStream programs.</li>
+</ul>
+
+<p>Only minor code changes are required in order to submit the program to Flink instead of Storm.
+This minimizes the work for developers to run existing Storm topologies while leveraging Apache Flink’s fast and robust execution engine.</p>
+
+<p>We note that the Storm compatibility package is continuously improving and does not cover the full spectrum of Storm’s API.
+However, it is powerful enough to cover many use cases.</p>
+
+<h2 id="executing-storm-topologies-with-flink">Executing Storm topologies with Flink</h2>
+
+<center>
+<img src="/img/blog/flink-storm.png" style="height:200px;margin:15px" />
+</center>
+
+<p>The easiest way to use the Storm compatibility package is by executing a whole Storm topology in Flink.
+For this, you only need to replace the dependency <code>storm-core</code> by <code>flink-storm</code> in your Storm project and <strong>change two lines of code</strong> in your original Storm program.</p>
+
+<p>The following example shows a simple Storm-Word-Count-Program that can be executed in Flink.
+First, the program is assembled the Storm way without any code change to Spouts, Bolts, or the topology itself.</p>
+
+<div class="highlight"><pre><code class="language-java"><span class="c1">// assemble topology, the Storm way</span>
+<span class="n">TopologyBuilder</span> <span class="n">builder</span> <span class="o">=</span> <span class="k">new</span> <span class="n">TopologyBuilder</span><span class="o">();</span>
+<span class="n">builder</span><span class="o">.</span><span class="na">setSpout</span><span class="o">(</span><span class="s">&quot;source&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">StormFileSpout</span><span class="o">(</span><span class="n">inputFilePath</span><span class="o">));</span>
+<span class="n">builder</span><span class="o">.</span><span class="na">setBolt</span><span class="o">(</span><span class="s">&quot;tokenizer&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">StormBoltTokenizer</span><span class="o">())</span>
+       <span class="o">.</span><span class="na">shuffleGrouping</span><span class="o">(</span><span class="s">&quot;source&quot;</span><span class="o">);</span>
+<span class="n">builder</span><span class="o">.</span><span class="na">setBolt</span><span class="o">(</span><span class="s">&quot;counter&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">StormBoltCounter</span><span class="o">())</span>
+       <span class="o">.</span><span class="na">fieldsGrouping</span><span class="o">(</span><span class="s">&quot;tokenizer&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">Fields</span><span class="o">(</span><span class="s">&quot;word&quot;</span><span class="o">));</span>
+<span class="n">builder</span><span class="o">.</span><span class="na">setBolt</span><span class="o">(</span><span class="s">&quot;sink&quot;</span><span class="o">,</span> <span class="k">new</span> <span class="n">StormBoltFileSink</span><span class="o">(</span><span class="n">outputFilePath</span><span class="o">))</span>
+       <span class="o">.</span><span class="na">shuffleGrouping</span><span class="o">(</span><span class="s">&quot;counter&quot;</span><span class="o">);</span></code></pre></div>
+
+<p>In order to execute the topology, we need to translate it to a <code>FlinkTopology</code> and submit it to a local or remote Flink cluster, very similar to submitting the application to a Storm cluster.<sup><a href="#fn1" id="ref1">1</a></sup></p>
+
+<div class="highlight"><pre><code class="language-java"><span class="c1">// transform Storm topology to Flink program</span>
+<span class="c1">// replaces: StormTopology topology = builder.createTopology();</span>
+<span class="n">FlinkTopology</span> <span class="n">topology</span> <span class="o">=</span> <span class="n">FlinkTopology</span><span class="o">.</span><span class="na">createTopology</span><span class="o">(</span><span class="n">builder</span><span class="o">);</span>
+
+<span class="n">Config</span> <span class="n">conf</span> <span class="o">=</span> <span class="k">new</span> <span class="n">Config</span><span class="o">();</span>
+<span class="k">if</span><span class="o">(</span><span class="n">runLocal</span><span class="o">)</span> <span class="o">{</span>
+	<span class="c1">// use FlinkLocalCluster instead of LocalCluster</span>
+	<span class="n">FlinkLocalCluster</span> <span class="n">cluster</span> <span class="o">=</span> <span class="n">FlinkLocalCluster</span><span class="o">.</span><span class="na">getLocalCluster</span><span class="o">();</span>
+	<span class="n">cluster</span><span class="o">.</span><span class="na">submitTopology</span><span class="o">(</span><span class="s">&quot;WordCount&quot;</span><span class="o">,</span> <span class="n">conf</span><span class="o">,</span> <span class="n">topology</span><span class="o">);</span>
+<span class="o">}</span> <span class="k">else</span> <span class="o">{</span>
+	<span class="c1">// use FlinkSubmitter instead of StormSubmitter</span>
+	<span class="n">FlinkSubmitter</span><span class="o">.</span><span class="na">submitTopology</span><span class="o">(</span><span class="s">&quot;WordCount&quot;</span><span class="o">,</span> <span class="n">conf</span><span class="o">,</span> <span class="n">topology</span><span class="o">);</span>
+<span class="o">}</span></code></pre></div>
+
+<p>As a shorter Flink-style alternative that replaces the Storm-style submission code, you can also use context-based job execution:</p>
+
+<div class="highlight"><pre><code class="language-java"><span class="c1">// transform Storm topology to Flink program (as above)</span>
+<span class="n">FlinkTopology</span> <span class="n">topology</span> <span class="o">=</span> <span class="n">FlinkTopology</span><span class="o">.</span><span class="na">createTopology</span><span class="o">(</span><span class="n">builder</span><span class="o">);</span>
+
+<span class="c1">// executes locally by default or remotely if submitted with Flink&#39;s command-line client</span>
+<span class="n">topology</span><span class="o">.</span><span class="na">execute</span><span class="o">()</span></code></pre></div>
+
+<p>After the code is packaged in a jar file (e.g., <code>StormWordCount.jar</code>), it can be easily submitted to Flink via</p>
+
+<div class="highlight"><pre><code>bin/flink run StormWordCount.jar
+</code></pre></div>
+
+<p>The used Spouts and Bolts as well as the topology assemble code is not changed at all!
+Only the translation and submission step have to be changed to the Storm-API compatible Flink pendants.
+This allows for minimal code changes and easy adaption to Flink.</p>
+
+<h3 id="embedding-spouts-and-bolts-in-flink-programs">Embedding Spouts and Bolts in Flink programs</h3>
+
+<p>It is also possible to use Spouts and Bolts within a regular Flink DataStream program.
+The compatibility package provides wrapper classes for Spouts and Bolts which are implemented as a Flink <code>SourceFunction</code> and <code>StreamOperator</code> respectively.
+Those wrappers automatically translate incoming Flink POJO and <code>TupleXX</code> records into Storm’s <code>Tuple</code> type and emitted <code>Values</code> back into either POJOs or <code>TupleXX</code> types for further processing by Flink operators.
+As Storm is type agnostic, it is required to specify the output type of embedded Spouts/Bolts manually to get a fully typed Flink streaming program.</p>
+
+<div class="highlight"><pre><code class="language-java"><span class="c1">// use regular Flink streaming environment</span>
+<span class="n">StreamExecutionEnvironment</span> <span class="n">env</span> <span class="o">=</span> <span class="n">StreamExecutionEnvironment</span><span class="o">.</span><span class="na">getExecutionEnvironment</span><span class="o">();</span>
+
+<span class="c1">// use Spout as source</span>
+<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Tuple1</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;&gt;</span> <span class="n">source</span> <span class="o">=</span> 
+  <span class="n">env</span><span class="o">.</span><span class="na">addSource</span><span class="o">(</span><span class="c1">// Flink provided wrapper including original Spout</span>
+                <span class="k">new</span> <span class="n">SpoutWrapper</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;(</span><span class="k">new</span> <span class="n">FileSpout</span><span class="o">(</span><span class="n">localFilePath</span><span class="o">)),</span> 
+                <span class="c1">// specify output type manually</span>
+                <span class="n">TypeExtractor</span><span class="o">.</span><span class="na">getForObject</span><span class="o">(</span><span class="k">new</span> <span class="n">Tuple1</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;(</span><span class="s">&quot;&quot;</span><span class="o">)));</span>
+<span class="c1">// FileSpout cannot be parallelized</span>
+<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Tuple1</span><span class="o">&lt;</span><span class="n">String</span><span class="o">&gt;&gt;</span> <span class="n">text</span> <span class="o">=</span> <span class="n">source</span><span class="o">.</span><span class="na">setParallelism</span><span class="o">(</span><span class="mi">1</span><span class="o">);</span>
+
+<span class="c1">// further processing with Flink</span>
+<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span><span class="n">Integer</span><span class="o">&gt;</span> <span class="n">tokens</span> <span class="o">=</span> <span class="n">text</span><span class="o">.</span><span class="na">flatMap</span><span class="o">(</span><span class="k">new</span> <span class="n">Tokenizer</span><span class="o">()).</span><span class="na">keyBy</span><span class="o">(</span><span class="mi">0</span><span class="o">);</span>
+
+<span class="c1">// use Bolt for counting</span>
+<span class="n">DataStream</span><span class="o">&lt;</span><span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span><span class="n">Integer</span><span class="o">&gt;</span> <span class="n">counts</span> <span class="o">=</span>
+  <span class="n">tokens</span><span class="o">.</span><span class="na">transform</span><span class="o">(</span><span class="s">&quot;Counter&quot;</span><span class="o">,</span>
+                   <span class="c1">// specify output type manually</span>
+                   <span class="n">TypeExtractor</span><span class="o">.</span><span class="na">getForObject</span><span class="o">(</span><span class="k">new</span> <span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span><span class="n">Integer</span><span class="o">&gt;(</span><span class="s">&quot;&quot;</span><span class="o">,</span><span class="mi">0</span><span class="o">))</span>
+                   <span class="c1">// Flink provided wrapper including original Bolt</span>
+                   <span class="k">new</span> <span class="n">BoltWrapper</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span><span class="n">Tuple2</span><span class="o">&lt;</span><span class="n">String</span><span class="o">,</span><span class="n">Integer</span><span class="o">&gt;&gt;(</span><span class="k">new</span> <span class="n">BoltCounter</span><span class="o">()));</span>
+
+<span class="c1">// write result to file via Flink sink</span>
+<span class="n">counts</span><span class="o">.</span><span class="na">writeAsText</span><span class="o">(</span><span class="n">outputPath</span><span class="o">);</span>
+
+<span class="c1">// start Flink job</span>
+<span class="n">env</span><span class="o">.</span><span class="na">execute</span><span class="o">(</span><span class="s">&quot;WordCount with Spout source and Bolt counter&quot;</span><span class="o">);</span></code></pre></div>
+
+<p>Although some boilerplate code is needed (we plan to address this soon!), the actual embedded Spout and Bolt code can be used unmodified.
+We also note that the resulting program is fully typed, and type errors will be found by Flink’s type extractor even if the original Spouts and Bolts are not.</p>
+
+<h2 id="outlook">Outlook</h2>
+
+<p>The Storm compatibility package is currently in beta and undergoes continuous development.
+We are currently working on providing consistency guarantees for stateful Bolts.
+Furthermore, we want to provide a better API integration for embedded Spouts and Bolts by providing a “StormExecutionEnvironment” as a special extension of Flink’s <code>StreamExecutionEnvironment</code>.
+We are also investigating the integration of Storm’s higher-level programming API Trident.</p>
+
+<h2 id="summary">Summary</h2>
+
+<p>Flink’s compatibility package for Storm allows using unmodified Spouts and Bolts within Flink.
+This enables you to even embed third-party Spouts and Bolts where the source code is not available.
+While you can embed Spouts/Bolts in a Flink program and mix-and-match them with Flink operators, running whole topologies is the easiest way to get started and can be achieved with almost no code changes.</p>
+
+<p>If you want to try out Flink’s Storm compatibility package checkout our <a href="https://ci.apache.org/projects/flink/flink-docs-master/apis/storm_compatibility.html">Documentation</a>.</p>
+
+<hr />
+
+<p><sup id="fn1">1. We confess, there are three lines changed compared to a Storm project <img class="emoji" style="width:16px;height:16px;align:absmiddle" src="/img/blog/smirk.png" />—because the example covers local <em>and</em> remote execution. <a href="#ref1" title="Back to text.">↩</a></sup></p>
+
+
+      </article>
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