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Subject [3/3] incubator-beam-site git commit: Regenerate website
Date Thu, 01 Dec 2016 22:31:35 GMT
Regenerate website


Branch: refs/heads/asf-site
Commit: f439af099412e73da73a288cd212ff8e93221e35
Parents: 7e96f7b
Author: Dan Halperin <>
Authored: Thu Dec 1 14:31:10 2016 -0800
Committer: Dan Halperin <>
Committed: Thu Dec 1 14:31:10 2016 -0800

 content/documentation/runners/flink/index.html | 138 +++++++++++++++++++-
 1 file changed, 137 insertions(+), 1 deletion(-)
diff --git a/content/documentation/runners/flink/index.html b/content/documentation/runners/flink/index.html
index 6ccaff7..edd5bcd 100644
--- a/content/documentation/runners/flink/index.html
+++ b/content/documentation/runners/flink/index.html
@@ -146,7 +146,143 @@
       <div class="row">
         <h1 id="using-the-apache-flink-runner">Using the Apache Flink Runner</h1>
-<p>This page is under construction (<a href="">BEAM-506</a>).</p>
+<p>The Apache Flink Runner can be used to execute Beam pipelines using <a href="">Apache
Flink</a>. When using the Flink Runner you will create a jar file containing your job
that can be executed on a regular Flink cluster. It’s also possible to execute a Beam pipeline
using Flink’s local execution mode without setting up a cluster. This is helpful for development
and debugging of your pipeline.</p>
+<p>The Flink Runner and Flink are suitable for large scale, continuous jobs, and provide:</p>
+  <li>A streaming-first runtime that supports both batch processing and data streaming
+  <li>A runtime that supports very high throughput and low event latency at the same
+  <li>Fault-tolerance with <em>exactly-once</em> processing guarantees</li>
+  <li>Natural back-pressure in streaming programs</li>
+  <li>Custom memory management for efficient and robust switching between in-memory
and out-of-core data processing algorithms</li>
+  <li>Integration with YARN and other components of the Apache Hadoop ecosystem</li>
+<p>The <a href="/documentation/runners/capability-matrix/">Beam Capability Matrix</a>
documents the supported capabilities of the Flink Runner.</p>
+<h2 id="flink-runner-prerequisites-and-setup">Flink Runner prerequisites and setup</h2>
+<p>If you want to use the local execution mode with the Flink runner to don’t have
to complete any setup.</p>
+<p>To use the Flink Runner for executing on a cluster, you have to setup a Flink cluster
by following the Flink <a href="">setup
+<p>To find out which version of Flink you need you can run this command to check the
version of the Flink dependency that your project is using:</p>
+<div class="highlighter-rouge"><pre class="highlight"><code>$ mvn dependency:tree
-Pflink-runner |grep flink
+[INFO] |  +- org.apache.flink:flink-streaming-java_2.10:jar:1.1.2:runtime
+<p>Here, we would need Flink 1.1.2.</p>
+<p>For more information, the <a href="">Flink
Documentation</a> can be helpful.</p>
+<h3 id="specify-your-dependency">Specify your dependency</h3>
+<p>You must specify your dependency on the Flink Runner.</p>
+<div class="language-java highlighter-rouge"><pre class="highlight"><code><span
class="o">&lt;</span><span class="n">dependency</span><span class="o">&gt;</span>
+  <span class="o">&lt;</span><span class="n">groupId</span><span
class="o">&gt;</span><span class="n">org</span><span class="o">.</span><span
class="na">apache</span><span class="o">.</span><span class="na">beam</span><span
class="o">&lt;/</span><span class="n">groupId</span><span class="o">&gt;</span>
+  <span class="o">&lt;</span><span class="n">artifactId</span><span
class="o">&gt;</span><span class="n">beam</span><span class="o">-</span><span
class="n">runners</span><span class="o">-</span><span class="n">flink_2</span><span
class="o">.</span><span class="mi">10</span><span class="o">&lt;/</span><span
class="n">artifactId</span><span class="o">&gt;</span>
+  <span class="o">&lt;</span><span class="n">version</span><span
class="o">&gt;</span><span class="mf">0.3</span><span class="o">.</span><span
class="mi">0</span><span class="o">-</span><span class="n">incubating</span><span
class="o">&lt;/</span><span class="n">version</span><span class="o">&gt;</span>
+  <span class="o">&lt;</span><span class="n">scope</span><span
class="o">&gt;</span><span class="n">runtime</span><span class="o">&lt;/</span><span
class="n">scope</span><span class="o">&gt;</span>
+<span class="o">&lt;/</span><span class="n">dependency</span><span
+<h2 id="executing-a-pipeline-on-a-flink-cluster">Executing a pipeline on a Flink cluster</h2>
+<p>For executing a pipeline on a Flink cluster you need to package your program along
will all dependencies in a so-called fat jar. How you do this depends on your build system
but if you follow along the <a href="/get-started/quickstart/">Beam Quickstart</a>
this is the command that you have to run:</p>
+<div class="highlighter-rouge"><pre class="highlight"><code>$ mvn package
+<p>The Beam Quickstart Maven project is setup to use the Maven Shade plugin to create
a fat jar and the <code class="highlighter-rouge">-Pflink-runner</code> argument
makes sure to include the dependency on the Flink Runner.</p>
+<p>For actually running the pipeline you would use this command</p>
+<div class="highlighter-rouge"><pre class="highlight"><code>$ mvn exec:java
-Dexec.mainClass=org.apache.beam.examples.WordCount \
+    -Pflink-runner \
+    -Dexec.args="--runner=FlinkRunner \
+      --inputFile=/path/to/pom.xml \
+      --output=/path/to/counts \
+      --flinkMaster=&lt;flink master url&gt; \
+      --filesToStage=target/word-count-beam--bundled-0.1.jar"
+<p>If you have a Flink <code class="highlighter-rouge">JobManager</code>
running on your local machine you can give <code class="highlighter-rouge">localhost:6123</code>
+<code class="highlighter-rouge">flinkMaster</code>.</p>
+<h2 id="pipeline-options-for-the-flink-runner">Pipeline options for the Flink Runner</h2>
+<p>When executing your pipeline with the Flink Runner, you can set these pipeline options.</p>
+<table class="table table-bordered">
+  <th>Field</th>
+  <th>Description</th>
+  <th>Default Value</th>
+  <td><code>runner</code></td>
+  <td>The pipeline runner to use. This option allows you to determine the pipeline
runner at runtime.</td>
+  <td>Set to <code>FlinkRunner</code> to run using Flink.</td>
+  <td><code>streaming</code></td>
+  <td>Whether streaming mode is enabled or disabled; <code>true</code>
if enabled. Set to <code>true</code> if running pipelines with unbounded <code>PCollection</code>s.</td>
+  <td><code>false</code></td>
+  <td><code>flinkMaster</code></td>
+  <td>The url of the Flink JobManager on which to execute pipelines. This can either
be the address of a cluster JobManager, in the form <code>"host:port"</code> or
one of the special Strings <code>"[local]"</code> or <code>"[auto]"</code>.
<code>"[local]"</code> will start a local Flink Cluster in the JVM while <code>"[auto]"</code>
will let the system decide where to execute the pipeline based on the environment.</td>
+  <td><code>[auto]</code></td>
+  <td><code>filesToStage</code></td>
+  <td>Jar Files to send to all workers and put on the classpath. Here you have to put
the fat jar that contains your program along with all dependencies.</td>
+  <td>empty</td>
+  <td><code>parallelism</code></td>
+  <td>The degree of parallelism to be used when distributing operations onto workers.</td>
+  <td><code>1</code></td>
+  <td><code>checkpointingInterval</code></td>
+  <td>The interval between consecutive checkpoints (i.e. snapshots of the current pipeline
state used for fault tolerance).</td>
+  <td><code>-1L</code>, i.e. disabled</td>
+  <td><code>numberOfExecutionRetries</code></td>
+  <td>Sets the number of times that failed tasks are re-executed. A value of <code>0</code>
effectively disables fault tolerance. A value of <code>-1</code> indicates that
the system default value (as defined in the configuration) should be used.</td>
+  <td><code>-1</code></td>
+  <td><code>executionRetryDelay</code></td>
+  <td>Sets the delay between executions. A value of <code>-1</code> indicates
that the default value should be used.</td>
+  <td><code>-1</code></td>
+  <td><code>stateBackend</code></td>
+  <td>Sets the state backend to use in streaming mode. The default is to read this
setting from the Flink config.</td>
+  <td><code>empty</code>, i.e. read from Flink config</td>
+<p>See the reference documentation for the  <span class="language-java"><a
class="language-python"><a href="">PipelineOptions</a></span>
interface (and its subinterfaces) for the complete list of pipeline configuration options.</p>
+<h2 id="additional-information-and-caveats">Additional information and caveats</h2>
+<h3 id="monitoring-your-job">Monitoring your job</h3>
+<p>You can monitor a running Flink job using the Flink JobManager Dashboard. By default,
this is available at port <code class="highlighter-rouge">8081</code> of the JobManager
node. If you have a Flink installation on your local machine that would be <code class="highlighter-rouge">http://localhost:8081</code>.</p>
+<h3 id="streaming-execution">Streaming Execution</h3>
+<p>If your pipeline uses an unbounded data source or sink, the Flink Runner will automatically
switch to streaming mode. You can enforce streaming mode by using the <code class="highlighter-rouge">streaming</code>
setting mentioned above.</p>

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