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From DB Tsai <>
Subject Re: trying to understand yarn-client mode
Date Thu, 19 Jun 2014 18:33:28 GMT
We are submitting the spark job in our tomcat application using
yarn-cluster mode with great success. As Kevin said, yarn-client mode
runs driver in your local JVM, and it will have really bad network
overhead when one do reduce action which will pull all the result from
executor to your local JVM. Also, since you can only have one spark
context object in one JVM, it will be tricky to run multiple spark
jobs concurrently with yarn-clinet mode.

This is how we submit spark job with yarn-cluster mode. Please use the
current master code, otherwise, after the job is finished, spark will
kill the JVM and exit your app.

We setup the configuration of spark in a scala map.

  def getArgsFromConf(conf: Map[String, String]): Array[String] = {
      "--jar", conf.get("app.jar").getOrElse(""),
      "--addJars", conf.get("spark.addJars").getOrElse(""),
      "--class", conf.get("spark.mainClass").getOrElse(""),
      "--num-executors", conf.get("spark.numWorkers").getOrElse("1"),
      "--driver-memory", conf.get("spark.masterMemory").getOrElse("1g"),
      "--executor-memory", conf.get("spark.workerMemory").getOrElse("1g"),
      "--executor-cores", conf.get("spark.workerCores").getOrElse("1"))

      System.setProperty("SPARK_YARN_MODE", "true")
      val sparkConf = new SparkConf
      val args = getArgsFromConf(conf)
      new Client(new ClientArguments(args, sparkConf), hadoopConfig,


DB Tsai
My Blog:

On Thu, Jun 19, 2014 at 11:22 AM, Kevin Markey <> wrote:
> Yarn client is much like Spark client mode, except that the executors are
> running in Yarn containers managed by the Yarn resource manager on the
> cluster instead of as Spark workers managed by the Spark master.  The driver
> executes as a local client in your local JVM.  It communicates with the
> workers on the cluster.  Transformations are scheduled on the cluster by the
> driver's logic.  Actions involve communication between local driver and
> remote cluster executors.  So, there is some additional network overhead,
> especially if the driver is not co-located on the cluster.  In yarn-cluster
> mode -- in contrast, the driver is executed as a thread in a Yarn
> application master on the cluster.
> In either case, the assembly JAR must be available to the application on the
> cluster.  Best to copy it to HDFS and specify its location by exporting its
> location as SPARK_JAR.
> Kevin Markey
> On 06/19/2014 11:22 AM, Koert Kuipers wrote:
> i am trying to understand how yarn-client mode works. i am not using
> spark-submit, but instead launching a spark job from within my own
> application.
> i can see my application contacting yarn successfully, but then in yarn i
> get an immediate error:
> Application application_1403117970283_0014 failed 2 times due to AM
> Container for appattempt_1403117970283_0014_000002 exited with exitCode:
> -1000 due to: File file:/home/koert/test-assembly-0.1-SNAPSHOT.jar does not
> exist
> .Failing this attempt.. Failing the application.
> why is yarn trying to fetch my jar, and why as a local file? i would expect
> the jar to be send to yarn over the wire upon job submission?

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