mesos.md

Table of Contents generated with DocToc

• Configuring Job Server for Mesos
  • Mesos client mode
  • Mesos cluster mode
• Configuring Job Server for supervised cluster mode

Configuring Job Server for Mesos

See also running on cluster, YARN in client mode and running on EMR.

Mesos client mode

Configuring job-server for Mesos client mode is straight forward. All you need to change is spark.master config to point to Mesos master URL in job-server config file.

Example config file (important settings are marked with # important):

spark {
  master = <mesos master URL here> # example: mesos://mesos-master:5050
}

Mesos cluster mode

Configuring job-server for Mesos cluster mode is a bit tricky as compared to client mode.

You need to start Mesos dispatcher in your cluster by running ./sbin/start-mesos-dispatcher.sh available in spark package. This step is not specific to job-server and as mentioned in official spark documentation this is needed to submit spark job in Mesos cluster mode.

Add the following config to you job-server config file:

• set spark.master property to messos dispatcher URL (example: mesos://mesos-dispatcher:7077)
• set spark.submit.deployMode property to cluster
• set spark.jobserver.context-per-jvm to true
• set akka.remote.netty.tcp.hostname to the cluster interface of the host running the frontend
• set akka.remote.netty.tcp.maximum-frame-size to support big remote jars fetch
• set spark.jobserver.network-address-resolver to a suitable value according to your environment. akka is recommended.

Example job server config (replace CLUSTER-IP with the internal IP of the host running the job server frontend):

spark {
  master =  <mesos dispatcher URL> # example: mesos://mesos-dispatcher:7077
  submit.deployMode = cluster

  jobserver {
    context-per-jvm = true

    # start a H2 DB server, reachable in your cluster
    sqldao {
      jdbc {
        url = "jdbc:h2:tcp://CLUSTER-IP:9092/h2-db;AUTO_RECONNECT=TRUE"
      }
    }
    startH2Server = false
  }
}

# start akka on this interface, reachable from your cluster
akka {
  remote.netty.tcp {
    hostname = "CLUSTER-IP"

    # This controls the maximum message size, including job results, that can be sent
    maximum-frame-size = 100 MiB
  }
}

• Required: Replace MANAGER_* variables with

MANAGER_JAR_FILE="$appdir/spark-job-server.jar"
MANAGER_CONF_FILE="$(basename $conffile)"
MANAGER_EXTRA_JAVA_OPTIONS=
MANAGER_EXTRA_SPARK_CONFS="spark.yarn.submit.waitAppCompletion=false|spark.files=$appdir/log4jcluster.properties,$conffile"
MANAGER_LOGGING_OPTS="-Dlog4j.configuration=log4j-cluster.properties"

• Optional: Add following config at the end of job-server's settings.sh file:

  REMOTE_JOBSERVER_DIR=<path to job-server directory> # copy of job-server directory on all mesos agent nodes 
  

Configuring Job Server for supervised cluster mode

• See the supervise-mode document