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                 <p>We'll use <a href="https://github.com/apache/incubator-gearpump/blob/master/examples/distributedshell">Distributed Shell</a> as an example to illustrate how to do that.</p>
 <p>What Distributed Shell do is that user send a shell command to the cluster and the command will the executed on each node, then the result will be return to user.</p>
 <h3 id="mavensbt-settings">Maven/Sbt Settings</h3>
 <p>Repository and library dependencies can be found at <a href="http://gearpump.incubator.apache.org/downloads.html#maven-dependencies">Maven Setting</a></p>
 <h3 id="define-executor-class">Define Executor Class</h3>
 <pre class="codehilite"><code class="language-scala">class ShellExecutor(executorContext: ExecutorContext, userConf : UserConfig) extends Actor{
   import executorContext._

   override def receive: Receive = {
     case ShellCommand(command, args) =&gt;
       val process = Try(s&quot;$command $args&quot; !!)
       val result = process match {
         case Success(msg) =&gt; msg
         case Failure(ex) =&gt; ex.getMessage
       }
       sender ! ShellCommandResult(executorId, result)
   }
 }</code></pre>


 <p>So ShellExecutor just receive the ShellCommand and try to execute it and return the result to the sender, which is quite simple.</p>
 <h3 id="define-appmaster-class">Define AppMaster Class</h3>
 <p>For a non-streaming application, you have to write your own AppMaster.</p>
 <p>Here is a typical user defined AppMaster, please note that some trivial codes are omitted.</p>
 <pre class="codehilite"><code class="language-scala">class DistShellAppMaster(appContext : AppMasterContext, app : Application) extends ApplicationMaster {
   protected var currentExecutorId = 0

   override def preStart(): Unit = {
     ActorUtil.launchExecutorOnEachWorker(masterProxy, getExecutorJvmConfig, self)
   }

   override def receive: Receive = {
     case ExecutorSystemStarted(executorSystem) =&gt;
       import executorSystem.{address, worker, resource =&gt; executorResource}
       val executorContext = ExecutorContext(currentExecutorId, worker.workerId, appId, self, executorResource)
       val executor = context.actorOf(Props(classOf[ShellExecutor], executorContext, app.userConfig)
           .withDeploy(Deploy(scope = RemoteScope(address))), currentExecutorId.toString)
       executorSystem.bindLifeCycleWith(executor)
       currentExecutorId += 1
     case StartExecutorSystemTimeout =&gt;
       masterProxy ! ShutdownApplication(appId)
       context.stop(self)
     case msg: ShellCommand =&gt;
       Future.fold(context.children.map(_ ? msg))(new ShellCommandResultAggregator) { (aggregator, response) =&gt;
         aggregator.aggregate(response.asInstanceOf[ShellCommandResult])
       }.map(_.toString()) pipeTo sender
   }

   private def getExecutorJvmConfig: ExecutorSystemJvmConfig = {
     val config: Config = Option(app.clusterConfig).map(_.getConfig).getOrElse(ConfigFactory.empty())
     val jvmSetting = Util.resolveJvmSetting(config.withFallback(context.system.settings.config)).executor
     ExecutorSystemJvmConfig(jvmSetting.classPath, jvmSetting.vmargs,
       appJar, username, config)
   }
 }</code></pre>


 <p>So when this <code>DistShellAppMaster</code> started, first it will request resources to launch one executor on each node, which is done in method <code>preStart</code></p>
 <p>Then the DistShellAppMaster's receive handler will handle the allocated resource to launch the <code>ShellExecutor</code> we want. If you want to write your application, you can just use this part of code. The only thing needed is replacing the Executor class.</p>
 <p>There may be a situation that the resource allocation failed which will bring the message <code>StartExecutorSystemTimeout</code>, the normal pattern to handle that is just what we do: shut down the application.</p>
 <p>The real application logic part is in <code>ShellCommand</code> message handler, which is specific to different applications. Here we distribute the shell command to each executor and aggregate the results to the client.</p>
 <p>For method <code>getExecutorJvmConfig</code>, you can just use this part of code in your own application.</p>
 <h3 id="define-application">Define Application</h3>
 <p>Now its time to launch the application.</p>
 <pre class="codehilite"><code class="language-scala">object DistributedShell extends App with ArgumentsParser {
   private val LOG: Logger = LogUtil.getLogger(getClass)

   override val options: Array[(String, CLIOption[Any])] = Array.empty

   LOG.info(s&quot;Distributed shell submitting application...&quot;)
   val context = ClientContext()
   val appId = context.submit(Application[DistShellAppMaster](&quot;DistributedShell&quot;, UserConfig.empty))
   context.close()
   LOG.info(s&quot;Distributed Shell Application started with appId $appId !&quot;)
 }</code></pre>


 <p>The application class extends <code>App</code> and `ArgumentsParser which make it easier to parse arguments and run main functions. This part is similar to the streaming applications.</p>
 <p>The main class <code>DistributeShell</code> will submit an application to <code>Master</code>, whose <code>AppMaster</code> is <code>DistShellAppMaster</code>.</p>
 <h3 id="define-an-optional-client-class">Define an optional Client class</h3>
 <p>Now, we can define a <code>Client</code> class to talk with <code>AppMaster</code> to pass our commands to it.</p>
 <pre class="codehilite"><code class="language-scala">object DistributedShellClient extends App with ArgumentsParser  {
   implicit val timeout = Constants.FUTURE_TIMEOUT
   import scala.concurrent.ExecutionContext.Implicits.global
   private val LOG: Logger = LoggerFactory.getLogger(getClass)

   override val options: Array[(String, CLIOption[Any])] = Array(
     &quot;master&quot; -&gt; CLIOption[String](&quot;&lt;host1:port1,host2:port2,host3:port3&gt;&quot;, required = true),
     &quot;appid&quot; -&gt; CLIOption[Int](&quot;&lt;the distributed shell appid&gt;&quot;, required = true),
     &quot;command&quot; -&gt; CLIOption[String](&quot;&lt;shell command&gt;&quot;, required = true),
     &quot;args&quot; -&gt; CLIOption[String](&quot;&lt;shell arguments&gt;&quot;, required = true)
   )

   val config = parse(args)
   val context = ClientContext(config.getString(&quot;master&quot;))
   val appid = config.getInt(&quot;appid&quot;)
   val command = config.getString(&quot;command&quot;)
   val arguments = config.getString(&quot;args&quot;)
   val appMaster = context.resolveAppID(appid)
   (appMaster ? ShellCommand(command, arguments)).map { reslut =&gt;
     LOG.info(s&quot;Result: $reslut&quot;)
     context.close()
   }
 }</code></pre>


 <p>In the <code>DistributedShellClient</code>, it will resolve the appid to the real appmaster(the application id will be printed when launching <code>DistributedShell</code>).</p>
 <p>Once we got the <code>AppMaster</code>, then we can send <code>ShellCommand</code> to it and wait for the result.</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="../../introduction/commandline">Application submission tool</a> to command line tool syntax.</p>

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	<p>We'll use <a href="https://github.com/apache/incubator-gearpump/blob/master/examples/distributedshell">Distributed Shell</a> as an example to illustrate how to do that.</p>
	<p>What Distributed Shell do is that user send a shell command to the cluster and the command will the executed on each node, then the result will be return to user.</p>
	<h3 id="mavensbt-settings">Maven/Sbt Settings</h3>
	<p>Repository and library dependencies can be found at <a href="http://gearpump.incubator.apache.org/downloads.html#maven-dependencies">Maven Setting</a></p>
	<h3 id="define-executor-class">Define Executor Class</h3>
	<pre class="codehilite"><code class="language-scala">class ShellExecutor(executorContext: ExecutorContext, userConf : UserConfig) extends Actor{
	import executorContext._

	override def receive: Receive = {
	case ShellCommand(command, args) =>
	val process = Try(s"$command $args" !!)
	val result = process match {
	case Success(msg) => msg
	case Failure(ex) => ex.getMessage
	}
	sender ! ShellCommandResult(executorId, result)
	}
	}</code></pre>


	<p>So ShellExecutor just receive the ShellCommand and try to execute it and return the result to the sender, which is quite simple.</p>
	<h3 id="define-appmaster-class">Define AppMaster Class</h3>
	<p>For a non-streaming application, you have to write your own AppMaster.</p>
	<p>Here is a typical user defined AppMaster, please note that some trivial codes are omitted.</p>
	<pre class="codehilite"><code class="language-scala">class DistShellAppMaster(appContext : AppMasterContext, app : Application) extends ApplicationMaster {
	protected var currentExecutorId = 0

	override def preStart(): Unit = {
	ActorUtil.launchExecutorOnEachWorker(masterProxy, getExecutorJvmConfig, self)
	}

	override def receive: Receive = {
	case ExecutorSystemStarted(executorSystem) =>
	import executorSystem.{address, worker, resource => executorResource}
	val executorContext = ExecutorContext(currentExecutorId, worker.workerId, appId, self, executorResource)
	val executor = context.actorOf(Props(classOf[ShellExecutor], executorContext, app.userConfig)
	.withDeploy(Deploy(scope = RemoteScope(address))), currentExecutorId.toString)
	executorSystem.bindLifeCycleWith(executor)
	currentExecutorId += 1
	case StartExecutorSystemTimeout =>
	masterProxy ! ShutdownApplication(appId)
	context.stop(self)
	case msg: ShellCommand =>
	Future.fold(context.children.map(_ ? msg))(new ShellCommandResultAggregator) { (aggregator, response) =>
	aggregator.aggregate(response.asInstanceOf[ShellCommandResult])
	}.map(_.toString()) pipeTo sender
	}

	private def getExecutorJvmConfig: ExecutorSystemJvmConfig = {
	val config: Config = Option(app.clusterConfig).map(_.getConfig).getOrElse(ConfigFactory.empty())
	val jvmSetting = Util.resolveJvmSetting(config.withFallback(context.system.settings.config)).executor
	ExecutorSystemJvmConfig(jvmSetting.classPath, jvmSetting.vmargs,
	appJar, username, config)
	}
	}</code></pre>


	<p>So when this <code>DistShellAppMaster</code> started, first it will request resources to launch one executor on each node, which is done in method <code>preStart</code></p>
	<p>Then the DistShellAppMaster's receive handler will handle the allocated resource to launch the <code>ShellExecutor</code> we want. If you want to write your application, you can just use this part of code. The only thing needed is replacing the Executor class.</p>
	<p>There may be a situation that the resource allocation failed which will bring the message <code>StartExecutorSystemTimeout</code>, the normal pattern to handle that is just what we do: shut down the application.</p>
	<p>The real application logic part is in <code>ShellCommand</code> message handler, which is specific to different applications. Here we distribute the shell command to each executor and aggregate the results to the client.</p>
	<p>For method <code>getExecutorJvmConfig</code>, you can just use this part of code in your own application.</p>
	<h3 id="define-application">Define Application</h3>
	<p>Now its time to launch the application.</p>
	<pre class="codehilite"><code class="language-scala">object DistributedShell extends App with ArgumentsParser {
	private val LOG: Logger = LogUtil.getLogger(getClass)

	override val options: Array[(String, CLIOption[Any])] = Array.empty

	LOG.info(s"Distributed shell submitting application...")
	val context = ClientContext()
	val appId = context.submit(Application[DistShellAppMaster]("DistributedShell", UserConfig.empty))
	context.close()
	LOG.info(s"Distributed Shell Application started with appId $appId !")
	}</code></pre>


	<p>The application class extends <code>App</code> and `ArgumentsParser which make it easier to parse arguments and run main functions. This part is similar to the streaming applications.</p>
	<p>The main class <code>DistributeShell</code> will submit an application to <code>Master</code>, whose <code>AppMaster</code> is <code>DistShellAppMaster</code>.</p>
	<h3 id="define-an-optional-client-class">Define an optional Client class</h3>
	<p>Now, we can define a <code>Client</code> class to talk with <code>AppMaster</code> to pass our commands to it.</p>
	<pre class="codehilite"><code class="language-scala">object DistributedShellClient extends App with ArgumentsParser {
	implicit val timeout = Constants.FUTURE_TIMEOUT
	import scala.concurrent.ExecutionContext.Implicits.global
	private val LOG: Logger = LoggerFactory.getLogger(getClass)

	override val options: Array[(String, CLIOption[Any])] = Array(
	"master" -> CLIOption[String]("<host1:port1,host2:port2,host3:port3>", required = true),
	"appid" -> CLIOption[Int]("<the distributed shell appid>", required = true),
	"command" -> CLIOption[String]("<shell command>", required = true),
	"args" -> CLIOption[String]("<shell arguments>", required = true)
	)

	val config = parse(args)
	val context = ClientContext(config.getString("master"))
	val appid = config.getInt("appid")
	val command = config.getString("command")
	val arguments = config.getString("args")
	val appMaster = context.resolveAppID(appid)
	(appMaster ? ShellCommand(command, arguments)).map { reslut =>
	LOG.info(s"Result: $reslut")
	context.close()
	}
	}</code></pre>


	<p>In the <code>DistributedShellClient</code>, it will resolve the appid to the real appmaster(the application id will be printed when launching <code>DistributedShell</code>).</p>
	<p>Once we got the <code>AppMaster</code>, then we can send <code>ShellCommand</code> to it and wait for the result.</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="../../introduction/commandline">Application submission tool</a> to command line tool syntax.</p>

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