Spark Mesos Cluster Mode using Dispatcher

Question

I have only a single machine and want to run spark jobs with mesos cluster mode. It might make more sense to run with a cluster of nodes, but I mainly want to test out mesos first to check if it's able to utilize resources more efficiently (run multiple spark jobs at the same time without static partitioning). I have tried a number of ways but without success. Here is what I did:

1. Build mesos and run both mesos master and slaves (2 slaves in same machines).

   sudo ./bin/mesos-master.sh --ip=127.0.0.1 --work_dir=/var/lib/mesos
   sudo ./bin/mesos-slave.sh --master=127.0.0.1:5050 --port=5051 --work_dir=/tmp/mesos1
   sudo ./bin/mesos-slave.sh --master=127.0.0.1:5050 --port=5052 --work_dir=/tmp/mesos2
   

2. Run the spark-mesos-dispatcher

   sudo ./sbin/start-mesos-dispatcher.sh --master mesos://localhost:5050
   

3. The submit the app with dispatcher as master url.

   spark-submit  --master mesos://localhost:7077 <other-config> <jar file>
   

But it doesnt work:

    E0925 17:30:30.158846 807608320 socket.hpp:174] Shutdown failed on fd=61: Socket is not connected [57]
    E0925 17:30:30.159545 807608320 socket.hpp:174] Shutdown failed on fd=62: Socket is not connected [57]

If I use spark-submit --deploy-mode cluster, then I got another error message:

    Exception in thread "main" org.apache.spark.deploy.rest.SubmitRestConnectionException: Unable to connect to server

It work perfectly if I don't use dispatcher but using mesos master url directly: --master mesos://localhost:5050 (client mode). According to the documentation , cluster mode is not supported for Mesos clusters, but they give another instruction for cluster mode here. So it's kind of confusing? My question is:

1. How I can get it works?
2. Should I use client mode instead of cluster mode if I submit the app/jar directly from the master node?
3. If I have a single computer, should I spawn 1 or more mesos slave processes. Basically, I have a number of spark job and dont want to do static partitioning of resources. But when using mesos without static partitioning, it seems to be much slower?

Thanks.

Answer 1

Try using the 6066 port instead of 7077. The newer versions of Spark prefer the REST api for submitting jobs.

See https://issues.apache.org/jira/browse/SPARK-5388

Answer 2

I use your scenario to try, it could be work. One thing different , I use ip address to instead of "localhost" and "127.0.0.1" So just try again and to check http://your_dispatcher:8081 (on browser) if exist.

This is my spark-submit command:

$spark-submit --deploy-mode cluster --master mesos://192.168.11.79:7077 --class "SimpleApp"  SimpleAppV2.jar

If success, you can see as below

{
  "action" : "CreateSubmissionResponse",
  "serverSparkVersion" : "1.5.0",
  "submissionId" : "driver-20151006164749-0001",
  "success" : true
}

When I got your error log as yours, I reboot the machine and retry your step. It also work.

Answer 3

There seem to be two things you're confusing: launching a Spark application in a cluster (as opposed to locally) and launching the driver into the cluster.

From the top of Submitting Applications:

The spark-submit script in Spark’s bin directory is used to launch applications on a cluster. It can use all of Spark’s supported cluster managers through a uniform interface so you don’t have to configure your application specially for each one.

So, Mesos is one of the supported cluster managers and hence you can run Spark apps on a Mesos cluster.

What Mesos as time of writing does not support is launching the driver into the cluster, this is what the command line argument --deploy-mode of ./bin/spark-submitspecifies. Since the default value of --deploy-mode is client you can just omit it, or if you want to explicitly specify it, then use:

./bin/spark-submit --deploy-mode client ...