Spark submit using mesos dcos cli

I'm trying to start a spark streaming job on mesos using the DCOS cli. I'm able to start the job. My program expects a config file to be passed as cli parameter. How do I achieve this with dcos spark run --submit-args?

I tried --files http://server/path/to//file hoping it will download files but that didn't work. Driver starts but fails because config file is missing.

I also tried to roll up the jar and config file as tar and submitted it. I can see in Mesos logs that the tar was fetched and untar. Both config and jar file are seen in the working directory. But job fails with ClassNotFoundException. I suspect something was not right about how spark-submit was started.

dcos spark run --submit-args="--supervise --deploy-mode cluster --class package.name.classname http://file-server:8000/Streaming.tar.gz Streaming.conf"

Any hint on how to proceed? Also, in which log file can I see the underlying spark-submit command used by DCOS?

Solution

Here is the example of a command you should launch in order to make it work:

dcos spark run --submit-args='--conf spark.mesos.uris=https://s3-us-west-2.amazonaws.com/andrey-so-36323287/pi.conf --class JavaSparkPiConf https://s3-us-west-2.amazonaws.com/andrey-so-36323287/sparkPi_without_config_file.jar /mnt/mesos/sandbox/pi.conf'

Where

--conf spark.mesos.uris=... A comma-separated list of URIs to be downloaded to the sandbox when driver or executor is launched by Mesos. This applies to both coarse-grained and fine-grained mode.

/mnt/mesos/sandbox/pi.conf A path to the downloaded file which your main class receives as a 0th parameter (see the code snippet below). /mnt/mesos/sandbox/ is a standard path inside a container which is mapped to a corespondent mesos-task sandbox.

public final class JavaSparkPiConf {

  public static void main(String[] args) throws Exception {
    SparkConf sparkConf = new SparkConf().setAppName("JavaSparkPi");
    JavaSparkContext jsc = new JavaSparkContext(sparkConf);

    Scanner scanner = new Scanner(new FileInputStream(args[0]));
    int slices;
    if (scanner.hasNextInt()) {
      slices = scanner.nextInt();
    } else {
      slices = 2;
    }
    int n = 100000 * slices;
    List<Integer> l = new ArrayList<>(n);
    for (int i = 0; i < n; i++) {
      l.add(i);
    }

    JavaRDD<Integer> dataSet = jsc.parallelize(l, slices);

    int count = dataSet.map(new Function<Integer, Integer>() {
      @Override
      public Integer call(Integer integer) {
        double x = Math.random() * 2 - 1;
        double y = Math.random() * 2 - 1;
        return (x * x + y * y < 1) ? 1 : 0;
      }
    }).reduce(new Function2<Integer, Integer, Integer>() {
      @Override
      public Integer call(Integer integer, Integer integer2) {
        return integer + integer2;
      }
    });

    System.out.println("Pi is roughly " + 4.0 * count / n);

    jsc.stop();
  }
}