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<h1 class="title">Write Your 1st Gearpump App</h1>
<p>We&#8217;ll use <a href="https://github.com/gearpump/gearpump/blob/master/examples/streaming/wordcount/src/main/scala/io/gearpump/streaming/examples/wordcount/">wordcount</a> as an example to illustrate how to write GearPump applications.</p>
<h3 id="mavensbt-settings">Maven/Sbt Settings</h3>
<p>Repository and library dependencies can be found at <a href="maven-setting.html">Maven Setting</a>.</p>
<h3 id="ide-setup-optional">IDE Setup (Optional)</h3>
<p>You can get your preferred IDE ready for Gearpump by following <a href="dev-ide-setup.html">this guide</a>.</p>
<h3 id="define-processortask-class-and-partitioner-class">Define Processor(Task) class and Partitioner class</h3>
<p>An application is a Directed Acyclic Graph (DAG) of processors. In the wordcount example, We will firstly define two processors <code>Split</code> and <code>Sum</code>, and then weave them together.</p>
<h4 id="about-message-type">About message type</h4>
<p>User are allowed to send message of type AnyRef(map to Object in java).</p>
<div class="highlight"><pre><code>case class Message(msg: AnyRef, timestamp: TimeStamp = Message.noTimeStamp)
</code></pre></div>
<p>If user want to send primitive types like Int, Long, then he should box it explicitly with asInstanceOf. For example:</p>
<div class="highlight"><pre><code>new Message(3.asInstanceOf[AnyRef])
</code></pre></div>
<h4 id="split-processor">Split processor</h4>
<p>In the Split processor, we simply split a predefined text (the content is simplified for conciseness) and send out each split word to Sum.</p>
<p>Scala:</p>
<div class="highlight"><pre><code class="language-scala"><span class="k">class</span> <span class="nc">Split</span><span class="o">(</span><span class="n">taskContext</span> <span class="k">:</span> <span class="kt">TaskContext</span><span class="o">,</span> <span class="n">conf</span><span class="k">:</span> <span class="kt">UserConfig</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">Task</span><span class="o">(</span><span class="n">taskContext</span><span class="o">,</span> <span class="n">conf</span><span class="o">)</span> <span class="o">{</span>
<span class="k">import</span> <span class="nn">taskContext.output</span>
<span class="k">override</span> <span class="k">def</span> <span class="n">onStart</span><span class="o">(</span><span class="n">startTime</span> <span class="k">:</span> <span class="kt">StartTime</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="n">self</span> <span class="o">!</span> <span class="nc">Message</span><span class="o">(</span><span class="s">&quot;start&quot;</span><span class="o">)</span>
<span class="o">}</span>
<span class="k">override</span> <span class="k">def</span> <span class="n">onNext</span><span class="o">(</span><span class="n">msg</span> <span class="k">:</span> <span class="kt">Message</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="nc">Split</span><span class="o">.</span><span class="nc">TEXT_TO_SPLIT</span><span class="o">.</span><span class="n">lines</span><span class="o">.</span><span class="n">foreach</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;[\\s]+&quot;</span><span class="o">).</span><span class="n">filter</span><span class="o">(</span><span class="k">_</span><span class="o">.</span><span class="n">nonEmpty</span><span class="o">).</span><span class="n">foreach</span> <span class="o">{</span> <span class="n">msg</span> <span class="k">=&gt;</span>
<span class="n">output</span><span class="o">(</span><span class="k">new</span> <span class="nc">Message</span><span class="o">(</span><span class="n">msg</span><span class="o">,</span> <span class="nc">System</span><span class="o">.</span><span class="n">currentTimeMillis</span><span class="o">()))</span>
<span class="o">}</span>
<span class="o">}</span>
<span class="n">self</span> <span class="o">!</span> <span class="nc">Message</span><span class="o">(</span><span class="s">&quot;continue&quot;</span><span class="o">,</span> <span class="nc">System</span><span class="o">.</span><span class="n">currentTimeMillis</span><span class="o">())</span>
<span class="o">}</span>
<span class="o">}</span>
<span class="k">object</span> <span class="nc">Split</span> <span class="o">{</span>
<span class="k">val</span> <span class="nc">TEXT_TO_SPLIT</span> <span class="k">=</span> <span class="s">&quot;some text&quot;</span>
<span class="o">}</span></code></pre></div>
<p>Like Split, every processor extends a <code>TaskActor</code>. The <code>onStart</code> method is called once before any message comes in; <code>onNext</code> method is called to process every incoming message. Note that GearPump employs the message-driven model and that&#8217;s why Split sends itself a message at the end of <code>onStart</code> and <code>onNext</code> to trigger next message processing.</p>
<h4 id="sum-processor">Sum Processor</h4>
<p>The structure of Sum processor looks much alike. Sum does not need to send messages to itself since it receives messages from Split.</p>
<p>Scala:</p>
<div class="highlight"><pre><code class="language-scala"><span class="k">class</span> <span class="nc">Sum</span> <span class="o">(</span><span class="n">taskContext</span> <span class="k">:</span> <span class="kt">TaskContext</span><span class="o">,</span> <span class="n">conf</span><span class="k">:</span> <span class="kt">UserConfig</span><span class="o">)</span> <span class="k">extends</span> <span class="nc">Task</span><span class="o">(</span><span class="n">taskContext</span><span class="o">,</span> <span class="n">conf</span><span class="o">)</span> <span class="o">{</span>
<span class="k">private</span><span class="o">[</span><span class="kt">wordcount</span><span class="o">]</span> <span class="k">val</span> <span class="n">map</span> <span class="k">:</span> <span class="kt">mutable.HashMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Long</span><span class="o">]</span> <span class="k">=</span> <span class="k">new</span> <span class="n">mutable</span><span class="o">.</span><span class="nc">HashMap</span><span class="o">[</span><span class="kt">String</span>, <span class="kt">Long</span><span class="o">]()</span>
<span class="k">private</span><span class="o">[</span><span class="kt">wordcount</span><span class="o">]</span> <span class="k">var</span> <span class="n">wordCount</span> <span class="k">:</span> <span class="kt">Long</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">private</span> <span class="k">var</span> <span class="n">snapShotTime</span> <span class="k">:</span> <span class="kt">Long</span> <span class="o">=</span> <span class="nc">System</span><span class="o">.</span><span class="n">currentTimeMillis</span><span class="o">()</span>
<span class="k">private</span> <span class="k">var</span> <span class="n">snapShotWordCount</span> <span class="k">:</span> <span class="kt">Long</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">private</span> <span class="k">var</span> <span class="n">scheduler</span> <span class="k">:</span> <span class="kt">Cancellable</span> <span class="o">=</span> <span class="kc">null</span>
<span class="k">override</span> <span class="k">def</span> <span class="n">onStart</span><span class="o">(</span><span class="n">startTime</span> <span class="k">:</span> <span class="kt">StartTime</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="n">scheduler</span> <span class="k">=</span> <span class="n">taskContext</span><span class="o">.</span><span class="n">schedule</span><span class="o">(</span><span class="k">new</span> <span class="nc">FiniteDuration</span><span class="o">(</span><span class="mi">5</span><span class="o">,</span> <span class="nc">TimeUnit</span><span class="o">.</span><span class="nc">SECONDS</span><span class="o">),</span>
<span class="k">new</span> <span class="nc">FiniteDuration</span><span class="o">(</span><span class="mi">5</span><span class="o">,</span> <span class="nc">TimeUnit</span><span class="o">.</span><span class="nc">SECONDS</span><span class="o">))(</span><span class="n">reportWordCount</span><span class="o">)</span>
<span class="o">}</span>
<span class="k">override</span> <span class="k">def</span> <span class="n">onNext</span><span class="o">(</span><span class="n">msg</span> <span class="k">:</span> <span class="kt">Message</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="k">if</span> <span class="o">(</span><span class="kc">null</span> <span class="o">==</span> <span class="n">msg</span><span class="o">)</span> <span class="o">{</span>
<span class="k">return</span>
<span class="o">}</span>
<span class="k">val</span> <span class="n">current</span> <span class="k">=</span> <span class="n">map</span><span class="o">.</span><span class="n">getOrElse</span><span class="o">(</span><span class="n">msg</span><span class="o">.</span><span class="n">msg</span><span class="o">.</span><span class="n">asInstanceOf</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span> <span class="mi">0L</span><span class="o">)</span>
<span class="n">wordCount</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="n">map</span><span class="o">.</span><span class="n">put</span><span class="o">(</span><span class="n">msg</span><span class="o">.</span><span class="n">msg</span><span class="o">.</span><span class="n">asInstanceOf</span><span class="o">[</span><span class="kt">String</span><span class="o">],</span> <span class="n">current</span> <span class="o">+</span> <span class="mi">1</span><span class="o">)</span>
<span class="o">}</span>
<span class="k">override</span> <span class="k">def</span> <span class="n">onStop</span><span class="o">()</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="k">if</span> <span class="o">(</span><span class="n">scheduler</span> <span class="o">!=</span> <span class="kc">null</span><span class="o">)</span> <span class="o">{</span>
<span class="n">scheduler</span><span class="o">.</span><span class="n">cancel</span><span class="o">()</span>
<span class="o">}</span>
<span class="o">}</span>
<span class="k">def</span> <span class="n">reportWordCount</span><span class="o">()</span> <span class="k">:</span> <span class="kt">Unit</span> <span class="o">=</span> <span class="o">{</span>
<span class="k">val</span> <span class="n">current</span> <span class="k">:</span> <span class="kt">Long</span> <span class="o">=</span> <span class="nc">System</span><span class="o">.</span><span class="n">currentTimeMillis</span><span class="o">()</span>
<span class="nc">LOG</span><span class="o">.</span><span class="n">info</span><span class="o">(</span><span class="n">s</span><span class="s">&quot;Task ${taskContext.taskId} Throughput: ${(wordCount - snapShotWordCount, (current - snapShotTime) / 1000)} (words, second)&quot;</span><span class="o">)</span>
<span class="n">snapShotWordCount</span> <span class="k">=</span> <span class="n">wordCount</span>
<span class="n">snapShotTime</span> <span class="k">=</span> <span class="n">current</span>
<span class="o">}</span>
<span class="o">}</span></code></pre></div>
<p>Besides counting the sum, we also define a scheduler to report throughput every 5 seconds. The scheduler should be cancelled when the computation completes, which could be accomplished overriding the <code>onStop</code> method. The default implementation of <code>onStop</code> is a no-op.</p>
<h4 id="partitioner">Partitioner</h4>
<p>A processor could be parallelized to a list of tasks. A <code>Partitioner</code> defines how the data is shuffled among tasks of Split and Sum. GearPump has already provided two partitioners</p>
<ul>
<li><code>HashPartitioner</code>: partitions data based on the message&#8217;s hashcode</li>
<li><code>ShufflePartitioner</code>: partitions data in a round-robin way.</li>
</ul>
<p>You could define your own partitioner by extending the <code>Partitioner</code> trait and overriding the <code>getPartition</code> method.</p>
<div class="highlight"><pre><code class="language-scala"><span class="k">trait</span> <span class="nc">Partitioner</span> <span class="k">extends</span> <span class="nc">Serializable</span> <span class="o">{</span>
<span class="k">def</span> <span class="n">getPartition</span><span class="o">(</span><span class="n">msg</span> <span class="k">:</span> <span class="kt">Message</span><span class="o">,</span> <span class="n">partitionNum</span> <span class="k">:</span> <span class="kt">Int</span><span class="o">)</span> <span class="k">:</span> <span class="kt">Int</span>
<span class="o">}</span></code></pre></div>
<h3 id="define-taskdescription-and-appdescription">Define TaskDescription and AppDescription</h3>
<p>Now, we are able to write our application class, weaving the above components together.</p>
<p>The application class extends <code>App</code> and `ArgumentsParser which make it easier to parse arguments and run main functions.</p>
<div class="highlight"><pre><code class="language-scala"><span class="k">object</span> <span class="nc">WordCount</span> <span class="k">extends</span> <span class="nc">App</span> <span class="k">with</span> <span class="nc">ArgumentsParser</span> <span class="o">{</span>
<span class="k">private</span> <span class="k">val</span> <span class="nc">LOG</span><span class="k">:</span> <span class="kt">Logger</span> <span class="o">=</span> <span class="nc">LogUtil</span><span class="o">.</span><span class="n">getLogger</span><span class="o">(</span><span class="n">getClass</span><span class="o">)</span>
<span class="k">val</span> <span class="nc">RUN_FOR_EVER</span> <span class="k">=</span> <span class="o">-</span><span class="mi">1</span>
<span class="k">override</span> <span class="k">val</span> <span class="n">options</span><span class="k">:</span> <span class="kt">Array</span><span class="o">[(</span><span class="kt">String</span>, <span class="kt">CLIOption</span><span class="o">[</span><span class="kt">Any</span><span class="o">])]</span> <span class="k">=</span> <span class="nc">Array</span><span class="o">(</span>
<span class="s">&quot;split&quot;</span> <span class="o">-&gt;</span> <span class="nc">CLIOption</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">&quot;&lt;how many split tasks&gt;&quot;</span><span class="o">,</span> <span class="n">required</span> <span class="k">=</span> <span class="kc">false</span><span class="o">,</span> <span class="n">defaultValue</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">1</span><span class="o">)),</span>
<span class="s">&quot;sum&quot;</span> <span class="o">-&gt;</span> <span class="nc">CLIOption</span><span class="o">[</span><span class="kt">Int</span><span class="o">](</span><span class="s">&quot;&lt;how many sum tasks&gt;&quot;</span><span class="o">,</span> <span class="n">required</span> <span class="k">=</span> <span class="kc">false</span><span class="o">,</span> <span class="n">defaultValue</span> <span class="k">=</span> <span class="nc">Some</span><span class="o">(</span><span class="mi">1</span><span class="o">))</span>
<span class="o">)</span>
<span class="k">def</span> <span class="n">application</span><span class="o">(</span><span class="n">config</span><span class="k">:</span> <span class="kt">ParseResult</span><span class="o">)</span> <span class="k">:</span> <span class="kt">StreamApplication</span> <span class="o">=</span> <span class="o">{</span>
<span class="k">val</span> <span class="n">splitNum</span> <span class="k">=</span> <span class="n">config</span><span class="o">.</span><span class="n">getInt</span><span class="o">(</span><span class="s">&quot;split&quot;</span><span class="o">)</span>
<span class="k">val</span> <span class="n">sumNum</span> <span class="k">=</span> <span class="n">config</span><span class="o">.</span><span class="n">getInt</span><span class="o">(</span><span class="s">&quot;sum&quot;</span><span class="o">)</span>
<span class="k">val</span> <span class="n">partitioner</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">HashPartitioner</span><span class="o">()</span>
<span class="k">val</span> <span class="n">split</span> <span class="k">=</span> <span class="nc">Processor</span><span class="o">[</span><span class="kt">Split</span><span class="o">](</span><span class="n">splitNum</span><span class="o">)</span>
<span class="k">val</span> <span class="n">sum</span> <span class="k">=</span> <span class="nc">Processor</span><span class="o">[</span><span class="kt">Sum</span><span class="o">](</span><span class="n">sumNum</span><span class="o">)</span>
<span class="k">val</span> <span class="n">app</span> <span class="k">=</span> <span class="nc">StreamApplication</span><span class="o">(</span><span class="s">&quot;wordCount&quot;</span><span class="o">,</span> <span class="nc">Graph</span><span class="o">[</span><span class="kt">Processor</span><span class="o">[</span><span class="k">_</span> <span class="k">&lt;:</span> <span class="kt">Task</span><span class="o">]</span>, <span class="kt">Partitioner</span><span class="o">](</span><span class="n">split</span> <span class="o">~</span> <span class="n">partitioner</span> <span class="o">~&gt;</span> <span class="n">sum</span><span class="o">),</span> <span class="nc">UserConfig</span><span class="o">.</span><span class="n">empty</span><span class="o">)</span>
<span class="n">app</span>
<span class="o">}</span>
<span class="k">val</span> <span class="n">config</span> <span class="k">=</span> <span class="n">parse</span><span class="o">(</span><span class="n">args</span><span class="o">)</span>
<span class="k">val</span> <span class="n">context</span> <span class="k">=</span> <span class="nc">ClientContext</span><span class="o">()</span>
<span class="k">val</span> <span class="n">appId</span> <span class="k">=</span> <span class="n">context</span><span class="o">.</span><span class="n">submit</span><span class="o">(</span><span class="n">application</span><span class="o">(</span><span class="n">config</span><span class="o">))</span>
<span class="n">context</span><span class="o">.</span><span class="n">close</span><span class="o">()</span>
<span class="o">}</span></code></pre></div>
<p>We override <code>options</code> value and define an array of command line arguments to parse. We want application users to pass in masters&#8217; hosts and ports, the parallelism of split and sum tasks, and how long to run the example. We also specify whether an option is <code>required</code> and provide <code>defaultValue</code> for some arguments.</p>
<p>Given the <code>ParseResult</code> of command line arguments, we create <code>TaskDescription</code>s for Split and Sum processors, and connect them with <code>HashPartitioner</code> using DAG API. The graph is wrapped in an <code>AppDescrition</code> , which is finally submit to master.</p>
<h3 id="submit-application">Submit application</h3>
<p>After all these, you need to package everything into a uber jar and submit the jar to Gearpump Cluster. Please check <a href="commandline.html">Application submission tool</a> to command line tool syntax.</p>
<h3 id="advanced-topic">Advanced topic</h3>
<p>For a real application, you definitely need to define your own customized message passing between processors.
Customized message needs customized serializer to help message passing over wire.
Check <a href="dev-connectors.html">this guide</a> for how to customize serializer.</p>
<h3 id="gearpump-for-non-streaming-usage">Gearpump for Non-Streaming Usage</h3>
<p>Gearpump is also able to as a base platform to develop non-streaming applications. See <a href="dev-non-streaming-example.html">this guide</a> on how to use Gearpump to develop a distributed shell.</p>
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