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From u..@apache.org
Subject [34/84] [abbrv] flink-web git commit: Updated Flink site
Date Wed, 18 Jan 2017 14:00:34 GMT
http://git-wip-us.apache.org/repos/asf/flink-web/blob/d8883b04/content/faq.html
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-      
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-<div class="row">
-  <div class="col-sm-8 col-sm-offset-2">
-    <div class="row">
-      <div class="col-sm-12"><h1>Frequently Asked Questions (FAQ)</h1></div>
-    </div>
-
-<!--
-Licensed to the Apache Software Foundation (ASF) under one
-or more contributor license agreements.  See the NOTICE file
-distributed with this work for additional information
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-
-<p>The following questions are frequently asked with regard to the Flink project <strong>in general</strong>. If you have further questions, make sure to consult the <a href="">documentation</a> or <a href="">ask the community</a>.</p>
-
-<div class="page-toc">
-<ul id="markdown-toc">
-  <li><a href="#general" id="markdown-toc-general">General</a>    <ul>
-      <li><a href="#is-flink-a-hadoop-project" id="markdown-toc-is-flink-a-hadoop-project">Is Flink a Hadoop Project?</a></li>
-      <li><a href="#do-i-have-to-install-apache-hadoop-to-use-flink" id="markdown-toc-do-i-have-to-install-apache-hadoop-to-use-flink">Do I have to install Apache Hadoop to use Flink?</a></li>
-    </ul>
-  </li>
-  <li><a href="#usage" id="markdown-toc-usage">Usage</a>    <ul>
-      <li><a href="#how-do-i-assess-the-progress-of-a-flink-program" id="markdown-toc-how-do-i-assess-the-progress-of-a-flink-program">How do I assess the progress of a Flink program?</a></li>
-      <li><a href="#how-can-i-figure-out-why-a-program-failed" id="markdown-toc-how-can-i-figure-out-why-a-program-failed">How can I figure out why a program failed?</a></li>
-      <li><a href="#how-do-i-debug-flink-programs" id="markdown-toc-how-do-i-debug-flink-programs">How do I debug Flink programs?</a></li>
-      <li><a href="#what-is-the-parallelism-how-do-i-set-it" id="markdown-toc-what-is-the-parallelism-how-do-i-set-it">What is the parallelism? How do I set it?</a></li>
-    </ul>
-  </li>
-  <li><a href="#errors" id="markdown-toc-errors">Errors</a>    <ul>
-      <li><a href="#why-am-i-getting-a-nonserializableexception-" id="markdown-toc-why-am-i-getting-a-nonserializableexception-">Why am I getting a “NonSerializableException” ?</a></li>
-      <li><a href="#in-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters" id="markdown-toc-in-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters">In Scala API, I get an error about implicit values and evidence parameters</a></li>
-      <li><a href="#i-get-an-error-message-saying-that-not-enough-buffers-are-available-how-do-i-fix-this" id="markdown-toc-i-get-an-error-message-saying-that-not-enough-buffers-are-available-how-do-i-fix-this">I get an error message saying that not enough buffers are available. How do I fix this?</a></li>
-      <li><a href="#my-job-fails-early-with-a-javaioeofexception-what-could-be-the-cause" id="markdown-toc-my-job-fails-early-with-a-javaioeofexception-what-could-be-the-cause">My job fails early with a java.io.EOFException. What could be the cause?</a></li>
-      <li><a href="#my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do" id="markdown-toc-my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do">My job fails with various exceptions from the HDFS/Hadoop code. What can I do?</a></li>
-      <li><a href="#in-eclipse-i-get-compilation-errors-in-the-scala-projects" id="markdown-toc-in-eclipse-i-get-compilation-errors-in-the-scala-projects">In Eclipse, I get compilation errors in the Scala projects</a></li>
-      <li><a href="#my-program-does-not-compute-the-correct-result-why-are-my-custom-key-types" id="markdown-toc-my-program-does-not-compute-the-correct-result-why-are-my-custom-key-types">My program does not compute the correct result. Why are my custom key types</a></li>
-      <li><a href="#i-get-a-javalanginstantiationexception-for-my-data-type-what-is-wrong" id="markdown-toc-i-get-a-javalanginstantiationexception-for-my-data-type-what-is-wrong">I get a java.lang.InstantiationException for my data type, what is wrong?</a></li>
-      <li><a href="#i-cant-stop-flink-with-the-provided-stop-scripts-what-can-i-do" id="markdown-toc-i-cant-stop-flink-with-the-provided-stop-scripts-what-can-i-do">I can’t stop Flink with the provided stop-scripts. What can I do?</a></li>
-      <li><a href="#i-got-an-outofmemoryexception-what-can-i-do" id="markdown-toc-i-got-an-outofmemoryexception-what-can-i-do">I got an OutOfMemoryException. What can I do?</a></li>
-      <li><a href="#why-do-the-taskmanager-log-files-become-so-huge" id="markdown-toc-why-do-the-taskmanager-log-files-become-so-huge">Why do the TaskManager log files become so huge?</a></li>
-      <li><a href="#the-slot-allocated-for-my-task-manager-has-been-released-what-should-i-do" id="markdown-toc-the-slot-allocated-for-my-task-manager-has-been-released-what-should-i-do">The slot allocated for my task manager has been released. What should I do?</a></li>
-    </ul>
-  </li>
-  <li><a href="#yarn-deployment" id="markdown-toc-yarn-deployment">YARN Deployment</a>    <ul>
-      <li><a href="#the-yarn-session-runs-only-for-a-few-seconds" id="markdown-toc-the-yarn-session-runs-only-for-a-few-seconds">The YARN session runs only for a few seconds</a></li>
-      <li><a href="#my-yarn-containers-are-killed-because-they-use-too-much-memory" id="markdown-toc-my-yarn-containers-are-killed-because-they-use-too-much-memory">My YARN containers are killed because they use too much memory</a></li>
-      <li><a href="#the-yarn-session-crashes-with-a-hdfs-permission-exception-during-startup" id="markdown-toc-the-yarn-session-crashes-with-a-hdfs-permission-exception-during-startup">The YARN session crashes with a HDFS permission exception during startup</a></li>
-      <li><a href="#my-job-is-not-reacting-to-a-job-cancellation" id="markdown-toc-my-job-is-not-reacting-to-a-job-cancellation">My job is not reacting to a job cancellation?</a></li>
-    </ul>
-  </li>
-  <li><a href="#features" id="markdown-toc-features">Features</a>    <ul>
-      <li><a href="#what-kind-of-fault-tolerance-does-flink-provide" id="markdown-toc-what-kind-of-fault-tolerance-does-flink-provide">What kind of fault-tolerance does Flink provide?</a></li>
-      <li><a href="#are-hadoop-like-utilities-such-as-counters-and-the-distributedcache-supported" id="markdown-toc-are-hadoop-like-utilities-such-as-counters-and-the-distributedcache-supported">Are Hadoop-like utilities, such as Counters and the DistributedCache supported?</a></li>
-    </ul>
-  </li>
-</ul>
-
-</div>
-
-<h2 id="general">General</h2>
-
-<h3 id="is-flink-a-hadoop-project">Is Flink a Hadoop Project?</h3>
-
-<p>Flink is a data processing system and an <strong>alternative to Hadoop’s
-MapReduce component</strong>. It comes with its <em>own runtime</em> rather than building on top
-of MapReduce. As such, it can work completely independently of the Hadoop
-ecosystem. However, Flink can also access Hadoop’s distributed file
-system (HDFS) to read and write data, and Hadoop’s next-generation resource
-manager (YARN) to provision cluster resources. Since most Flink users are
-using Hadoop HDFS to store their data, Flink already ships the required libraries to
-access HDFS.</p>
-
-<h3 id="do-i-have-to-install-apache-hadoop-to-use-flink">Do I have to install Apache Hadoop to use Flink?</h3>
-
-<p><strong>No</strong>. Flink can run <strong>without</strong> a Hadoop installation. However, a <em>very common</em>
-setup is to use Flink to analyze data stored in the Hadoop Distributed
-File System (HDFS). To make these setups work out of the box, Flink bundles the
-Hadoop client libraries by default.</p>
-
-<p>Additionally, we provide a special YARN Enabled download of Flink for
-users with an existing Hadoop YARN cluster. <a href="http://hadoop.apache.org/docs/r2.2.0/hadoop-yarn/hadoop-yarn-site/YARN.html">Apache Hadoop
-YARN</a>
-is Hadoop’s cluster resource manager that allows use of
-different execution engines next to each other on a cluster.</p>
-
-<h2 id="usage">Usage</h2>
-
-<h3 id="how-do-i-assess-the-progress-of-a-flink-program">How do I assess the progress of a Flink program?</h3>
-
-<p>There are a multiple of ways to track the progress of a Flink program:</p>
-
-<ul>
-  <li>The JobManager (the master of the distributed system) starts a web interface
-to observe program execution. In runs on port 8081 by default (configured in
-<code>conf/flink-config.yml</code>).</li>
-  <li>When you start a program from the command line, it will print the status
-changes of all operators as the program progresses through the operations.</li>
-  <li>All status changes are also logged to the JobManager’s log file.</li>
-</ul>
-
-<h3 id="how-can-i-figure-out-why-a-program-failed">How can I figure out why a program failed?</h3>
-
-<ul>
-  <li>The JobManager web frontend (by default on port 8081) displays the exceptions
-of failed tasks.</li>
-  <li>If you run the program from the command-line, task exceptions are printed to
-the standard error stream and shown on the console.</li>
-  <li>Both the command line and the web interface allow you to figure out which
-parallel task first failed and caused the other tasks to cancel the execution.</li>
-  <li>Failing tasks and the corresponding exceptions are reported in the log files
-of the master and the worker where the exception occurred
-(<code>log/flink-&lt;user&gt;-jobmanager-&lt;host&gt;.log</code> and
-<code>log/flink-&lt;user&gt;-taskmanager-&lt;host&gt;.log</code>).</li>
-</ul>
-
-<h3 id="how-do-i-debug-flink-programs">How do I debug Flink programs?</h3>
-
-<ul>
-  <li>When you start a program locally with the <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/apis/local_execution.html">LocalExecutor</a>,
-you can place breakpoints in your functions and debug them like normal
-Java/Scala programs.</li>
-  <li>The <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/apis/programming_guide.html#accumulators--counters">Accumulators</a> are very helpful in
-tracking the behavior of the parallel execution. They allow you to gather
-information inside the program’s operations and show them after the program
-execution.</li>
-</ul>
-
-<h3 id="what-is-the-parallelism-how-do-i-set-it">What is the parallelism? How do I set it?</h3>
-
-<p>In Flink programs, the parallelism determines how operations are split into
-individual tasks which are assigned to task slots. Each node in a cluster has at
-least one task slot. The total number of task slots is the number of all task slots
-on all machines. If the parallelism is set to <code>N</code>, Flink tries to divide an
-operation into <code>N</code> parallel tasks which can be computed concurrently using the
-available task slots. The number of task slots should be equal to the
-parallelism to ensure that all tasks can be computed in a task slot concurrently.</p>
-
-<p><strong>Note</strong>: Not all operations can be divided into multiple tasks. For example, a
-<code>GroupReduce</code> operation without a grouping has to be performed with a
-parallelism of 1 because the entire group needs to be present at exactly one
-node to perform the reduce operation. Flink will determine whether the
-parallelism has to be 1 and set it accordingly.</p>
-
-<p>The parallelism can be set in numerous ways to ensure a fine-grained control
-over the execution of a Flink program. See
-the <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/setup/config.html#common-options">Configuration guide</a> for detailed instructions on how to
-set the parallelism. Also check out <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/setup/config.html#configuring-taskmanager-processing-slots">this figure</a> detailing
-how the processing slots and parallelism are related to each other.</p>
-
-<h2 id="errors">Errors</h2>
-
-<h3 id="why-am-i-getting-a-nonserializableexception-">Why am I getting a “NonSerializableException” ?</h3>
-
-<p>All functions in Flink must be serializable, as defined by <a href="http://docs.oracle.com/javase/7/docs/api/java/io/Serializable.html">java.io.Serializable</a>.
-Since all function interfaces are serializable, the exception means that one
-of the fields used in your function is not serializable.</p>
-
-<p>In particular, if your function is an inner class, or anonymous inner class,
-it contains a hidden reference to the enclosing class (usually called <code>this$0</code>, if you look
-at the function in the debugger). If the enclosing class is not serializable, this is probably
-the source of the error. Solutions are to</p>
-
-<ul>
-  <li>make the function a standalone class, or a static inner class (no more reference to the enclosing class)</li>
-  <li>make the enclosing class serializable</li>
-  <li>use a Java 8 lambda function.</li>
-</ul>
-
-<h3 id="in-scala-api-i-get-an-error-about-implicit-values-and-evidence-parameters">In Scala API, I get an error about implicit values and evidence parameters</h3>
-
-<p>It means that the implicit value for the type information could not be provided.
-Make sure that you have an <code>import org.apache.flink.api.scala._</code> statement in your code.</p>
-
-<p>If you are using flink operations inside functions or classes that take
-generic parameters a TypeInformation must be available for that parameter.
-This can be achieved by using a context bound:</p>
-
-<div class="highlight"><pre><code class="language-scala"><span class="k">def</span> <span class="n">myFunction</span><span class="o">[</span><span class="kt">T:</span> <span class="kt">TypeInformation</span><span class="o">](</span><span class="n">input</span><span class="k">:</span> <span class="kt">DataSet</span><span class="o">[</span><span class="kt">T</span><span class="o">])</span><span class="k">:</span> <span class="kt">DataSet</span><span class="o">[</span><span class="kt">Seq</span><span class="o">[</span><span class="kt">T</span><span class="o">]]</span> <span class="k">=</span> <span class="o">{</span>
-  <span class="n">input</span><span class="o">.</span><span class="n">reduceGroup</span><span class="o">(</span> <span class="n">i</span> <span class="k">=&gt;</span> <span class="n">i</span><span class="o">.</span><span class="n">toSeq</span> <span class="o">)</span>
-<span class="o">}</span></code></pre></div>
-
-<p>See <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/internals/types_serialization.html">Type Extraction and Serialization</a> for
-an in-depth discussion of how Flink handles types.</p>
-
-<h3 id="i-get-an-error-message-saying-that-not-enough-buffers-are-available-how-do-i-fix-this">I get an error message saying that not enough buffers are available. How do I fix this?</h3>
-
-<p>If you run Flink in a massively parallel setting (100+ parallel threads),
-you need to adapt the number of network buffers via the config parameter
-<code>taskmanager.network.numberOfBuffers</code>.
-As a rule-of-thumb, the number of buffers should be at least
-<code>4 * numberOfTaskManagers * numberOfSlotsPerTaskManager^2</code>. See
-<a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/setup/config.html#configuring-the-network-buffers">Configuration Reference</a> for details.</p>
-
-<h3 id="my-job-fails-early-with-a-javaioeofexception-what-could-be-the-cause">My job fails early with a java.io.EOFException. What could be the cause?</h3>
-
-<p>The most common case for these exception is when Flink is set up with the
-wrong HDFS version. Because different HDFS versions are often not compatible
-with each other, the connection between the filesystem master and the client
-breaks.</p>
-
-<div class="highlight"><pre><code class="language-bash">Call to &lt;host:port&gt; failed on <span class="nb">local </span>exception: java.io.EOFException
-    at org.apache.hadoop.ipc.Client.wrapException<span class="o">(</span>Client.java:775<span class="o">)</span>
-    at org.apache.hadoop.ipc.Client.call<span class="o">(</span>Client.java:743<span class="o">)</span>
-    at org.apache.hadoop.ipc.RPC<span class="nv">$Invoker</span>.invoke<span class="o">(</span>RPC.java:220<span class="o">)</span>
-    at <span class="nv">$Proxy0</span>.getProtocolVersion<span class="o">(</span>Unknown Source<span class="o">)</span>
-    at org.apache.hadoop.ipc.RPC.getProxy<span class="o">(</span>RPC.java:359<span class="o">)</span>
-    at org.apache.hadoop.hdfs.DFSClient.createRPCNamenode<span class="o">(</span>DFSClient.java:106<span class="o">)</span>
-    at org.apache.hadoop.hdfs.DFSClient.&lt;init&gt;<span class="o">(</span>DFSClient.java:207<span class="o">)</span>
-    at org.apache.hadoop.hdfs.DFSClient.&lt;init&gt;<span class="o">(</span>DFSClient.java:170<span class="o">)</span>
-    at org.apache.hadoop.hdfs.DistributedFileSystem.initialize<span class="o">(</span>DistributedFileSystem.java:82<span class="o">)</span>
-    at org.apache.flinkruntime.fs.hdfs.DistributedFileSystem.initialize<span class="o">(</span>DistributedFileSystem.java:276</code></pre></div>
-
-<p>Please refer to the <a href="/downloads.html#maven">download page</a> and
-the <a href="https://github.com/apache/flink/tree/master/README.md">build instructions</a>
-for details on how to set up Flink for different Hadoop and HDFS versions.</p>
-
-<h3 id="my-job-fails-with-various-exceptions-from-the-hdfshadoop-code-what-can-i-do">My job fails with various exceptions from the HDFS/Hadoop code. What can I do?</h3>
-
-<p>Flink is shipping with the Hadoop 2.2 binaries by default. These binaries are used
-to connect to HDFS or YARN.
-It seems that there are some bugs in the HDFS client which cause exceptions while writing to HDFS
-(in particular under high load).
-Among the exceptions are the following:</p>
-
-<ul>
-  <li><code>HDFS client trying to connect to the standby Namenode "org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.ipc.StandbyException): Operation category READ is not supported in state standby"</code></li>
-  <li>
-    <p><code>java.io.IOException: Bad response ERROR for block BP-1335380477-172.22.5.37-1424696786673:blk_1107843111_34301064 from datanode 172.22.5.81:50010
-at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer$ResponseProcessor.run(DFSOutputStream.java:732)</code></p>
-  </li>
-  <li><code>Caused by: org.apache.hadoop.ipc.RemoteException(java.lang.ArrayIndexOutOfBoundsException): 0
-      at org.apache.hadoop.hdfs.server.blockmanagement.DatanodeManager.getDatanodeStorageInfos(DatanodeManager.java:478)
-      at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.updatePipelineInternal(FSNamesystem.java:6039)
-      at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.updatePipeline(FSNamesystem.java:6002)</code></li>
-</ul>
-
-<p>If you are experiencing any of these, we recommend using a Flink build with a Hadoop version matching
-your local HDFS version.
-You can also manually build Flink against the exact Hadoop version (for example
-when using a Hadoop distribution with a custom patch level)</p>
-
-<h3 id="in-eclipse-i-get-compilation-errors-in-the-scala-projects">In Eclipse, I get compilation errors in the Scala projects</h3>
-
-<p>Flink uses a new feature of the Scala compiler (called “quasiquotes”) that have not yet been properly
-integrated with the Eclipse Scala plugin. In order to make this feature available in Eclipse, you
-need to manually configure the <em>flink-scala</em> project to use a <em>compiler plugin</em>:</p>
-
-<ul>
-  <li>Right click on <em>flink-scala</em> and choose “Properties”</li>
-  <li>Select “Scala Compiler” and click on the “Advanced” tab. (If you do not have that, you probably have not set up Eclipse for Scala properly.)</li>
-  <li>Check the box “Use Project Settings”</li>
-  <li>In the field “Xplugin”, put the path “/home/<user-name>/.m2/repository/org/scalamacros/paradise_2.10.4/2.0.1/paradise_2.10.4-2.0.1.jar"</user-name></li>
-  <li>NOTE: You have to build Flink with Maven on the command line first, to make sure the plugin is downloaded.</li>
-</ul>
-
-<h3 id="my-program-does-not-compute-the-correct-result-why-are-my-custom-key-types">My program does not compute the correct result. Why are my custom key types</h3>
-<p>are not grouped/joined correctly?</p>
-
-<p>Keys must correctly implement the methods <code>java.lang.Object#hashCode()</code>,
-<code>java.lang.Object#equals(Object o)</code>, and <code>java.util.Comparable#compareTo(...)</code>.
-These methods are always backed with default implementations which are usually
-inadequate. Therefore, all keys must override <code>hashCode()</code> and <code>equals(Object o)</code>.</p>
-
-<h3 id="i-get-a-javalanginstantiationexception-for-my-data-type-what-is-wrong">I get a java.lang.InstantiationException for my data type, what is wrong?</h3>
-
-<p>All data type classes must be public and have a public nullary constructor
-(constructor with no arguments). Further more, the classes must not be abstract
-or interfaces. If the classes are internal classes, they must be public and
-static.</p>
-
-<h3 id="i-cant-stop-flink-with-the-provided-stop-scripts-what-can-i-do">I can’t stop Flink with the provided stop-scripts. What can I do?</h3>
-
-<p>Stopping the processes sometimes takes a few seconds, because the shutdown may
-do some cleanup work.</p>
-
-<p>In some error cases it happens that the JobManager or TaskManager cannot be
-stopped with the provided stop-scripts (<code>bin/stop-local.sh</code> or <code>bin/stop-
-cluster.sh</code>). You can kill their processes on Linux/Mac as follows:</p>
-
-<ul>
-  <li>Determine the process id (pid) of the JobManager / TaskManager process. You
-can use the <code>jps</code> command on Linux(if you have OpenJDK installed) or command
-<code>ps -ef | grep java</code> to find all Java processes.</li>
-  <li>Kill the process with <code>kill -9 &lt;pid&gt;</code>, where <code>pid</code> is the process id of the
-affected JobManager or TaskManager process.</li>
-</ul>
-
-<p>On Windows, the TaskManager shows a table of all processes and allows you to
-destroy a process by right its entry.</p>
-
-<p>Both the JobManager and TaskManager services will write signals (like SIGKILL
-and SIGTERM) into their respective log files. This can be helpful for 
-debugging issues with the stopping behavior.</p>
-
-<h3 id="i-got-an-outofmemoryexception-what-can-i-do">I got an OutOfMemoryException. What can I do?</h3>
-
-<p>These exceptions occur usually when the functions in the program consume a lot
-of memory by collection large numbers of objects, for example in lists or maps.
-The OutOfMemoryExceptions in Java are kind of tricky. The exception is not
-necessarily thrown by the component that allocated most of the memory but by the
-component that tried to requested the latest bit of memory that could not be
-provided.</p>
-
-<p>There are two ways to go about this:</p>
-
-<ol>
-  <li>
-    <p>See whether you can use less memory inside the functions. For example, use
-arrays of primitive types instead of object types.</p>
-  </li>
-  <li>
-    <p>Reduce the memory that Flink reserves for its own processing. The
-TaskManager reserves a certain portion of the available memory for sorting,
-hashing, caching, network buffering, etc. That part of the memory is unavailable
-to the user-defined functions. By reserving it, the system can guarantee to not
-run out of memory on large inputs, but to plan with the available memory and
-destage operations to disk, if necessary. By default, the system reserves around
-70% of the memory. If you frequently run applications that need more memory in
-the user-defined functions, you can reduce that value using the configuration
-entries <code>taskmanager.memory.fraction</code> or <code>taskmanager.memory.size</code>. See the
-<a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/setup/config.html">Configuration Reference</a> for details. This will leave more memory to JVM heap,
-but may cause data processing tasks to go to disk more often.</p>
-  </li>
-</ol>
-
-<p>Another reason for OutOfMemoryExceptions is the use of the wrong state backend.
-By default, Flink is using a heap-based state backend for operator state in
-streaming jobs. The <code>RocksDBStateBackend</code> allows state sizes larger than the
-available heap space.</p>
-
-<h3 id="why-do-the-taskmanager-log-files-become-so-huge">Why do the TaskManager log files become so huge?</h3>
-
-<p>Check the logging behavior of your jobs. Emitting logging per object or tuple may be
-helpful to debug jobs in small setups with tiny data sets but can limit performance
-and consume substantial disk space if used for large input data.</p>
-
-<h3 id="the-slot-allocated-for-my-task-manager-has-been-released-what-should-i-do">The slot allocated for my task manager has been released. What should I do?</h3>
-
-<p>If you see a <code>java.lang.Exception: The slot in which the task was executed has been released. Probably loss of TaskManager</code> even though the TaskManager did actually not crash, it 
-means that the TaskManager was unresponsive for a time. That can be due to network issues, but is frequently due to long garbage collection stalls.
-In this case, a quick fix would be to use an incremental Garbage Collector, like the G1 garbage collector. It usually leads to shorter pauses. Furthermore, you can dedicate more memory to
-the user code by reducing the amount of memory Flink grabs for its internal operations (see configuration of TaskManager managed memory).</p>
-
-<p>If both of these approaches fail and the error persists, simply increase the TaskManager’s heartbeat pause by setting AKKA_WATCH_HEARTBEAT_PAUSE (akka.watch.heartbeat.pause) to a greater value (e.g. 600s).
-This will cause the JobManager to wait for a heartbeat for a longer time interval before considering the TaskManager lost.</p>
-
-<h2 id="yarn-deployment">YARN Deployment</h2>
-
-<h3 id="the-yarn-session-runs-only-for-a-few-seconds">The YARN session runs only for a few seconds</h3>
-
-<p>The <code>./bin/yarn-session.sh</code> script is intended to run while the YARN-session is
-open. In some error cases however, the script immediately stops running. The
-output looks like this:</p>
-
-<div class="highlight"><pre><code>07:34:27,004 INFO  org.apache.hadoop.yarn.client.api.impl.YarnClientImpl         - Submitted application application_1395604279745_273123 to ResourceManager at jobtracker-host
-Flink JobManager is now running on worker1:6123
-JobManager Web Interface: http://jobtracker-host:54311/proxy/application_1295604279745_273123/
-07:34:51,528 INFO  org.apache.flinkyarn.Client                                   - Application application_1295604279745_273123 finished with state FINISHED at 1398152089553
-07:34:51,529 INFO  org.apache.flinkyarn.Client                                   - Killing the Flink-YARN application.
-07:34:51,529 INFO  org.apache.hadoop.yarn.client.api.impl.YarnClientImpl         - Killing application application_1295604279745_273123
-07:34:51,534 INFO  org.apache.flinkyarn.Client                                   - Deleting files in hdfs://user/marcus/.flink/application_1295604279745_273123
-07:34:51,559 INFO  org.apache.flinkyarn.Client                                   - YARN Client is shutting down
-</code></pre></div>
-
-<p>The problem here is that the Application Master (AM) is stopping and the YARN client assumes that the application has finished.</p>
-
-<p>There are three possible reasons for that behavior:</p>
-
-<ul>
-  <li>
-    <p>The ApplicationMaster exited with an exception. To debug that error, have a
-look in the logfiles of the container. The <code>yarn-site.xml</code> file contains the
-configured path. The key for the path is <code>yarn.nodemanager.log-dirs</code>, the
-default value is <code>${yarn.log.dir}/userlogs</code>.</p>
-  </li>
-  <li>
-    <p>YARN has killed the container that runs the ApplicationMaster. This case
-happens when the AM used too much memory or other resources beyond YARN’s
-limits. In this case, you’ll find error messages in the nodemanager logs on
-the host.</p>
-  </li>
-  <li>
-    <p>The operating system has shut down the JVM of the AM. This can happen if the
-YARN configuration is wrong and more memory than physically available is
-configured. Execute <code>dmesg</code> on the machine where the AM was running to see if
-this happened. You see messages from Linux’ <a href="http://linux-mm.org/OOM_Killer">OOM killer</a>.</p>
-  </li>
-</ul>
-
-<h3 id="my-yarn-containers-are-killed-because-they-use-too-much-memory">My YARN containers are killed because they use too much memory</h3>
-
-<p>This is usually indicated my a log message like the following one:</p>
-
-<div class="highlight"><pre><code>Container container_e05_1467433388200_0136_01_000002 is completed with diagnostics: Container [pid=5832,containerID=container_e05_1467433388200_0136_01_000002] is running beyond physical memory limits. Current usage: 2.3 GB of 2 GB physical memory used; 6.1 GB of 4.2 GB virtual memory used. Killing container.
-</code></pre></div>
-
-<p>In that case, the JVM process grew too large. Because the Java heap size is always limited, the extra memory typically comes from non-heap sources:</p>
-
-<ul>
-  <li>Libraries that use off-heap memory. (Flink’s own off-heap memory is limited and taken into account when calculating the allowed heap size.)</li>
-  <li>PermGen space (strings and classes), code caches, memory mapped jar files</li>
-  <li>Native libraries (RocksDB)</li>
-</ul>
-
-<p>You can activate the <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.0/setup/config.html#memory-and-performance-debugging">memory debug logger</a> to get more insight into what memory pool is actually using up too much memory.</p>
-
-<h3 id="the-yarn-session-crashes-with-a-hdfs-permission-exception-during-startup">The YARN session crashes with a HDFS permission exception during startup</h3>
-
-<p>While starting the YARN session, you are receiving an exception like this:</p>
-
-<div class="highlight"><pre><code>Exception in thread "main" org.apache.hadoop.security.AccessControlException: Permission denied: user=robert, access=WRITE, inode="/user/robert":hdfs:supergroup:drwxr-xr-x
-  at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:234)
-  at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.check(FSPermissionChecker.java:214)
-  at org.apache.hadoop.hdfs.server.namenode.FSPermissionChecker.checkPermission(FSPermissionChecker.java:158)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkPermission(FSNamesystem.java:5193)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkPermission(FSNamesystem.java:5175)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkAncestorAccess(FSNamesystem.java:5149)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2090)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2043)
-  at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:1996)
-  at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:491)
-  at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:301)
-  at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java:59570)
-  at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:585)
-  at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:928)
-  at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2053)
-  at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2049)
-  at java.security.AccessController.doPrivileged(Native Method)
-  at javax.security.auth.Subject.doAs(Subject.java:396)
-  at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)
-  at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2047)
-
-  at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
-  at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:39)
-  at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:27)
-  at java.lang.reflect.Constructor.newInstance(Constructor.java:513)
-  at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:106)
-  at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
-  at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:1393)
-  at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1382)
-  at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1307)
-  at org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:384)
-  at org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:380)
-  at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
-  at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:380)
-  at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:324)
-  at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:905)
-  at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:886)
-  at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:783)
-  at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:365)
-  at org.apache.hadoop.fs.FileUtil.copy(FileUtil.java:338)
-  at org.apache.hadoop.fs.FileSystem.copyFromLocalFile(FileSystem.java:2021)
-  at org.apache.hadoop.fs.FileSystem.copyFromLocalFile(FileSystem.java:1989)
-  at org.apache.hadoop.fs.FileSystem.copyFromLocalFile(FileSystem.java:1954)
-  at org.apache.flinkyarn.Utils.setupLocalResource(Utils.java:176)
-  at org.apache.flinkyarn.Client.run(Client.java:362)
-  at org.apache.flinkyarn.Client.main(Client.java:568)
-</code></pre></div>
-
-<p>The reason for this error is, that the home directory of the user <strong>in HDFS</strong>
-has the wrong permissions. The user (in this case <code>robert</code>) can not create
-directories in his own home directory.</p>
-
-<p>Flink creates a <code>.flink/</code> directory in the users home directory
-where it stores the Flink jar and configuration file.</p>
-
-<h3 id="my-job-is-not-reacting-to-a-job-cancellation">My job is not reacting to a job cancellation?</h3>
-
-<p>Flink is canceling a job by calling the <code>cancel()</code> method on all user tasks. Ideally,
-the tasks properly react to the call and stop what they are currently doing, so that 
-all threads can shut down.</p>
-
-<p>If the tasks are not reacting for a certain amount of time, Flink will start interrupting
-the thread periodically.</p>
-
-<p>The TaskManager logs will also contain the current stack of the method where the user 
-code is blocked.</p>
-
-<h2 id="features">Features</h2>
-
-<h3 id="what-kind-of-fault-tolerance-does-flink-provide">What kind of fault-tolerance does Flink provide?</h3>
-
-<p>For streaming programs Flink has a novel approach to draw periodic snapshots of the streaming dataflow state and use those for recovery.
-This mechanism is both efficient and flexible. See the documentation on <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/internals/stream_checkpointing.html">streaming fault tolerance</a> for details.</p>
-
-<p>For batch processing programs Flink remembers the program’s sequence of transformations and can restart failed jobs.</p>
-
-<h3 id="are-hadoop-like-utilities-such-as-counters-and-the-distributedcache-supported">Are Hadoop-like utilities, such as Counters and the DistributedCache supported?</h3>
-
-<p><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/apis/programming_guide.html#accumulators--counters">Flink’s Accumulators</a> work very similar like
-Hadoop’s counters, but are more powerful.</p>
-
-<p>Flink has a <a href="https://github.com/apache/flink/tree/master/flink-core/src/main/java/org/apache/flink/api/common/cache/DistributedCache.java">Distributed Cache</a> that is deeply integrated with the APIs. Please refer to the <a href="https://github.com/apache/flink/tree/master/flink-java/src/main/java/org/apache/flink/api/java/ExecutionEnvironment.java#L831">JavaDocs</a> for details on how to use it.</p>
-
-<p>In order to make data sets available on all tasks, we encourage you to use <a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2/apis/programming_guide.html#broadcast-variables">Broadcast Variables</a> instead. They are more efficient and easier to use than the distributed cache.</p>
-
-
-  </div>
-</div>
-
-
-      <hr />
-      <div class="footer text-center">
-        <p>Copyright © 2014-2016 <a href="http://apache.org">The Apache Software Foundation</a>. All Rights Reserved.</p>
-        <p>Apache Flink, Apache, and the Apache feather logo are either registered trademarks or trademarks of The Apache Software Foundation.</p>
-        <p><a href="/privacy-policy.html">Privacy Policy</a> &middot; <a href="/blog/feed.xml">RSS feed</a></p>
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-<!DOCTYPE html>
-<html lang="en">
-  <head>
-    <meta charset="utf-8">
-    <meta http-equiv="X-UA-Compatible" content="IE=edge">
-    <meta name="viewport" content="width=device-width, initial-scale=1">
-    <!-- The above 3 meta tags *must* come first in the head; any other head content must come *after* these tags -->
-    <title>Apache Flink: Features</title>
-    <link rel="shortcut icon" href="/favicon.ico" type="image/x-icon">
-    <link rel="icon" href="/favicon.ico" type="image/x-icon">
-
-    <!-- Bootstrap -->
-    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/css/bootstrap.min.css">
-    <link rel="stylesheet" href="/css/flink.css">
-    <link rel="stylesheet" href="/css/syntax.css">
-
-    <!-- Blog RSS feed -->
-    <link href="/blog/feed.xml" rel="alternate" type="application/rss+xml" title="Apache Flink Blog: RSS feed" />
-
-    <!-- jQuery (necessary for Bootstrap's JavaScript plugins) -->
-    <!-- We need to load Jquery in the header for custom google analytics event tracking-->
-    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.2/jquery.min.js"></script>
-
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-      <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
-    <![endif]-->
-  </head>
-  <body>  
-    
-
-  <!-- Top navbar. -->
-    <nav class="navbar navbar-default navbar-fixed-top">
-      <div class="container">
-        <!-- The logo. -->
-        <div class="navbar-header">
-          <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
-            <span class="icon-bar"></span>
-            <span class="icon-bar"></span>
-            <span class="icon-bar"></span>
-          </button>
-          <div class="navbar-logo">
-            <a href="/">
-              <img alt="Apache Flink" src="/img/navbar-brand-logo.jpg" width="78px" height="40px">
-            </a>
-          </div>
-        </div><!-- /.navbar-header -->
-
-        <!-- The navigation links. -->
-        <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
-          <ul class="nav navbar-nav">
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-            <li><a href="/index.html">Overview</a></li>
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-            <li class="active"><a href="/features.html">Features</a></li>
-
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-
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-              <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"><small><span class="glyphicon glyphicon-new-window"></span></small> Quickstart <span class="caret"></span></a>
-              <ul class="dropdown-menu" role="menu">
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/quickstart/setup_quickstart.html">Setup</a></li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/quickstart/run_example_quickstart.html">Example: Wikipedia Edit Stream</a></li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/quickstart/java_api_quickstart.html">Java API</a></li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/quickstart/scala_api_quickstart.html">Scala API</a></li>
-              </ul>
-            </li>
-
-            <!-- Documentation -->
-            <li class="dropdown">
-              <a href="" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"><small><span class="glyphicon glyphicon-new-window"></span></small> Documentation <span class="caret"></span></a>
-              <ul class="dropdown-menu" role="menu">
-                <!-- Latest stable release -->
-                <li role="presentation" class="dropdown-header"><strong>Latest Release</strong> (Stable)</li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1">1.1 Documentation</a></li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/api/java" class="active">1.1 Javadocs</a></li>
-                <!--<li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.1/api/scala/index.html" class="active">1.1 ScalaDocs</a></li> -->
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-                <!-- Snapshot docs -->
-                <li class="divider"></li>
-                <li role="presentation" class="dropdown-header"><strong>Snapshot</strong> (Development)</li>
-                <li><a href="http://ci.apache.org/projects/flink/flink-docs-release-1.2">1.2 Documentation</a></li>
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-
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-                <li class="divider"></li>
-                <li><a href="/visualizer/"><small><span class="glyphicon glyphicon-new-window"></span></small> Plan Visualizer</a></li>
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-              </ul>
-            </li>
-
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-
-          <ul class="nav navbar-nav navbar-right">
-            <!-- Blog -->
-            <li class=" hidden-md hidden-sm"><a href="/blog/">Blog</a></li>
-
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-              <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false">Community <span class="caret"></span></a>
-              <ul class="dropdown-menu" role="menu">
-                <!-- Community -->
-                <li role="presentation" class="dropdown-header"><strong>Community</strong></li>
-                <li><a href="/community.html#mailing-lists">Mailing Lists</a></li>
-                <li><a href="/community.html#irc">IRC</a></li>
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-                <li class="divider"></li>
-                <li role="presentation" class="dropdown-header"><strong>Contribute</strong></li>
-                <li><a href="/how-to-contribute.html">How to Contribute</a></li>
-                <li><a href="/contribute-code.html">Contribute Code</a></li>
-                <li><a href="/contribute-documentation.html">Contribute Documentation</a></li>
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-                <!-- Project -->
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-                <li><a href="/slides.html">Slides</a></li>
-                <li><a href="/material.html">Material</a></li>
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-              </ul>
-            </li>
-          </ul>
-        </div><!-- /.navbar-collapse -->
-      </div><!-- /.container -->
-    </nav>
-
-
-    <!-- Main content. -->
-    <div class="container">
-      
-
-<div class="row">
-  <div class="col-sm-10 col-sm-offset-1">
-
-<!-- --------------------------------------------- -->
-<!--                Streaming
-<!-- --------------------------------------------- -->
-
-<hr />
-
-<div class="row" style="padding: 0 0 0 0">
-  <div class="col-sm-12" style="text-align: center;">
-    <h1 id="streaming"><b>Streaming</b></h1>
-  </div>
-</div>
-
-<hr />
-
-<!-- High Performance -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="performance"><i>High Performance &amp; Low Latency</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-12">
-    <p class="lead">Flink's data streaming runtime achieves high throughput rates and low latency with little configuration.
-    The charts below show the performance of a distributed item counting task, requiring streaming data shuffles.</p>
-  </div>
-</div>
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12 img-column">
-    <img src="/img/features/streaming_performance.png" alt="Performance of data streaming applications" style="width:75%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Event Time Streaming -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="event_time"><i>Support for Event Time and Out-of-Order Events</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink supports stream processing and windowing with <b>Event Time</b> semantics.</p>
-    <p class="lead">Event time makes it easy to compute over streams where events arrive out of order, and where events may arrive delayed.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/out_of_order_stream.png" alt="Event Time and Out-of-Order Streams" style="width:100%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Exactly-once Semantics -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="exactly_once"><i>Exactly-once Semantics for Stateful Computations</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Streaming applications can maintain custom state during their computation.</p>
-    <p class="lead">Flink's checkpointing mechanism ensures <i>exactly once</i> semantics for the state in the presence of failures.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/exactly_once_state.png" alt="Exactly-once Semantics for Stateful Computations" style="width:50%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Windowing -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="windows"><i>Highly flexible Streaming Windows</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink supports windows over time, count, or sessions, as well as data-driven windows.</p>
-    <p class="lead">Windows can be customized with flexible triggering conditions, to support sophisticated streaming patterns.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/windows.png" alt="Windows" style="width:100%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Continuous streaming -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="streaming_model"><i>Continuous Streaming Model with Backpressure</i></h1>
-  </div>
-</div>
-
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Data streaming applications are executed with continuous (long lived) operators.</p>
-    <p class="lead">Flink's streaming runtime has natural flow control: Slow data sinks backpressure faster sources.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/continuous_streams.png" alt="Continuous Streaming Model" style="width:60%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Lightweight distributed snapshots -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="snapshots"><i>Fault-tolerance via Lightweight Distributed Snapshots</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink's fault tolerance mechanism is based on Chandy-Lamport distributed snapshots.</p>
-    <p class="lead">The mechanism is lightweight, allowing the system to maintain high throughput rates and provide strong consistency guarantees at the same time.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/distributed_snapshots.png" alt="Lightweight Distributed Snapshots" style="width:40%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- --------------------------------------------- -->
-<!--                Batch
-<!-- --------------------------------------------- -->
-
-<div class="row" style="padding: 0 0 0 0">
-  <div class="col-sm-12" style="text-align: center;">
-    <h1 id="batch-on-streaming"><b>Batch and Streaming in One System</b></h1>
-  </div>
-</div>
-
-<hr />
-
-<!-- One Runtime for Streaming and Batch Processing -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="one_runtime"><i>One Runtime for Streaming and Batch Processing</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink uses one common runtime for data streaming applications and batch processing applications.</p>
-    <p class="lead">Batch processing applications run efficiently as special cases of stream processing applications.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/one_runtime.png" alt="Unified Runtime for Batch and Stream Data Analysis" style="width:50%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Memory Management -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="memory_management"><i>Memory Management</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink implements its own memory management inside the JVM.</p>
-    <p class="lead">Applications scale to data sizes beyond main memory and experience less garbage collection overhead.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/memory_heap_division.png" alt="Managed JVM Heap" style="width:50%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Iterations -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="iterations"><i>Iterations and Delta Iterations</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Flink has dedicated support for iterative computations (as in machine learning and graph analysis).</p>
-    <p class="lead">Delta iterations can exploit computational dependencies for faster convergence.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/iterations.png" alt="Performance of iterations and delta iterations" style="width:75%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- Optimizer -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="optimizer"><i>Program Optimizer</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-6">
-    <p class="lead">Batch programs are automatically optimized to exploit situations where expensive operations (like shuffles and sorts) can be avoided, and when intermediate data should be cached.</p>
-  </div>
-  <div class="col-sm-6 img-column">
-    <img src="/img/features/optimizer_choice.png" alt="Optimizer choosing between different execution strategies" style="width:100%" />
-  </div>
-</div>
-
-<hr />
-
-<!-- --------------------------------------------- -->
-<!--             APIs and Libraries
-<!-- --------------------------------------------- -->
-
-<div class="row" style="padding: 0 0 0 0">
-  <div class="col-sm-12" style="text-align: center;">
-    <h1 id="apis-and-libs"><b>APIs and Libraries</b></h1>
-  </div>
-</div>
-
-<hr />
-
-<!-- Data Streaming API -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="streaming_api"><i>Streaming Data Applications</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-5">
-    <p class="lead">The <i>DataStream</i> API supports functional transformations on data streams, with user-defined state, and flexible windows.</p>
-    <p class="lead">The example shows how to compute a sliding histogram of word occurrences of a data stream of texts.</p>
-  </div>
-  <div class="col-sm-7">
-    <p class="lead">WindowWordCount in Flink's DataStream API</p>
-
-<div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">case</span> <span class="k">class</span> <span class="nc">Word</span><span class="o">(</span><span class="n">word</span><span class="k">:</span> <span class="kt">String</span><span class="o">,</span> <span class="n">freq</span><span class="k">:</span> <span class="kt">Long</span><span class="o">)</span>
-
-<span class="k">val</span> <span class="n">texts</span><span class="k">:</span> <span class="kt">DataStream</span><span class="o">[</span><span class="kt">String</span><span class="o">]</span> <span class="k">=</span> <span class="o">...</span>
-
-<span class="k">val</span> <span class="n">counts</span> <span class="k">=</span> <span class="n">text</span>
-  <span class="o">.</span><span class="n">flatMap</span> <span class="o">{</span> <span class="n">line</span> <span class="k">=&gt;</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="o">(</span><span class="s">&quot;\\W+&quot;</span><span class="o">)</span> <span class="o">}</span>
-  <span class="o">.</span><span class="n">map</span> <span class="o">{</span> <span class="n">token</span> <span class="k">=&gt;</span> <span class="nc">Word</span><span class="o">(</span><span class="n">token</span><span class="o">,</span> <span class="mi">1</span><span class="o">)</span> <span class="o">}</span>
-  <span class="o">.</span><span class="n">keyBy</span><span class="o">(</span><span class="s">&quot;word&quot;</span><span class="o">)</span>
-  <span class="o">.</span><span class="n">timeWindow</span><span class="o">(</span><span class="nc">Time</span><span class="o">.</span><span class="n">seconds</span><span class="o">(</span><span class="mi">5</span><span class="o">),</span> <span class="nc">Time</span><span class="o">.</span><span class="n">seconds</span><span class="o">(</span><span class="mi">1</span><span class="o">))</span>
-  <span class="o">.</span><span class="n">sum</span><span class="o">(</span><span class="s">&quot;freq&quot;</span><span class="o">)</span></code></pre></div>
-
-  </div>
-</div>
-
-<hr />
-
-<!-- Batch Processing API -->
-<div class="row" style="padding: 0 0 2em 0">
-  <div class="col-sm-12">
-    <h1 id="batch_api"><i>Batch Processing Applications</i></h1>
-  </div>
-</div>
-<div class="row">
-  <div class="col-sm-5">
-    <p class="lead">Flink's <i>DataSet</i> API lets you write beautiful type-safe and maintainable code in Java or Scala. It supports a wide range of data types beyond key/value pairs, and a wealth of operators.</p>
-    <p class="lead">The example shows the core loop of the PageRank algorithm for graphs.</p>
-  </div>
-  <div class="col-sm-7">
-
-<div class="highlight"><pre><code class="language-scala" data-lang="scala"><span class="k">case</span> <span class="k">class</span> <span class="nc">Page</span><span class="o">(</span><span class="n">pageId</span><span class="k">:</span> <span class="kt">Long</span><span class="o">,</span> <span class="n">rank</span><span class="k">:</span> <span class="kt">Double</span><span class="o">)</span>
-<span class="k">case</span> <span class="k">class</span> <span class="nc">Adjacency</span><span class="o">(</span><span class="n">id</span><span class="k">:</span> <span class="kt">Long</span><span class="o">,</span> <span class="n">neighbors</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[</span><span class="kt">Long</span><span class="o">])</span>
-
-<span class="k">val</span> <span class="n">result</span> <span class="k">=</span> <span class="n">initialRanks</span><span class="o">.</span><span class="n">iterate</span><span class="o">(</span><span class="mi">30</span><span class="o">)</span> <span class="o">{</span> <span class="n">pages</span> <span class="k">=&gt;</span>
-  <span class="n">pages</span><span class="o">.</span><span class="n">join</span><span class="o">(</span><span class="n">adjacency</span><span class="o">).</span><span class="n">where</span><span class="o">(</span><span class="s">&quot;pageId&quot;</span><span class="o">).</span><span class="n">equalTo</span><span class="o">(</span><span class="s">&quot;id&quot;</span><span class="o">)</span> <span class="o">{</span>
-
-    <span class="o">(</span><span class="n">page</span><span class="o">,</span> <span class="n">adj</span><span class="o">,</span> <span class="n">out</span><span class="k">:</span> <span class="kt">Collector</span><span class="o">[</span><span class="kt">Page</span><span class="o">])</span> <span class="k">=&gt;</span> <span class="o">{</span>
-      <span class="n">out</span><span class="o">.</span><span class="n">collect</span><span class="o">(</span><span class="nc">Page</span><span class="o">(</span><span class="n">page</span><span class="o">.</span><span class="n">pageId</span><span class="o">,</span> <span class="mf">0.15</span> <span class="o">/</span> <span class="n">numPages</span><span class="o">))</span>
-
-      <span class="k">val</span> <span class="n">nLen</span> <span class="k">=</span> <span class="n">adj</span><span class="o">.</span><span class="n">neighbors</span><span class="o">.</span><span class="n">length</span>
-      <span class="k">for</span> <span class="o">(</span><span class="n">n</span> <span class="k">&lt;-</span> <span class="n">adj</span><span class="o">.</span><span class="n">neighbors</span><span class="o">)</span> <span class="o">{</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">collect</span><span class="o">(</span><span class="nc">Page</span><span class="o">(</span><span class="n">n</span><span class="o">,</span> <span class="mf">0.85</span> <span class="o">*</span> <span class="n">page</span><span class="o">.</span><span class="n">rank</span> <span class="o">/</span> <span class="n">nLen</span><span class="o">))</span>
-      <span class="o">}</span>
-    <span class="o">}</span>
-  <span class="o">}</span>
-  <span class="o">.</span><span class="n">groupBy</span><span class="o">(</span><span class="s">&quot;pageId&quot;</span><span class="o">).</span><span class="n">sum</span><span class="o">(</span><span class="s">&quot;rank&quot;</span><span class="o">)</span>
-<span class="o">}</span></code></pre></div>
-
-  </div>
-</div>
-
-<hr />
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-    <p class="lead">Flink's stack offers libraries with high-level APIs for different use cases: Complex Event Processing, Machine Learning, and Graph Analytics.</p>
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