Hi, I am using a mesos cluster to run my spark jobs. I have one mesos-master and two mesos-slaves setup on 2 machines. On one machine, master and slave are setup and on the second machine mesos-slave is setup I run these on m3-large ec2 instances.
1. When i try to submit two jobs using spark-submit in parallel, one job hangs with the message : "Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources". But when i check on the mesos cluster UI which runs at 5050 port, i can see idle memory which can be used by the hanging job. But number of idle cores is 1. So, does this mean that cores are pinned to spark-submit and no other spark-submit can get the core till the running spark-submit completes ? 2. Assumption : "submitting multiple spark-jobs using spark-submit has the above mentioned problem ". Now my task is to run a spark-streaming job which reads from kafka and does some precomputation. The nature of my pre-computation jobs are in such a way that, each pre-compute jobs has few mutually exclusive tasks to complete where all the tasks have inherent tree structure in them. i.e A task initiates few other tasks and they initiate further more tasks. I already have spark jobs which run as a batch job to perform the pre-computations mentioned above. Now, is it a good idea to convert these precompuations jobs into akka actors ? 3. If at all running multiple spark-submit jobs with shared CPU is possible, for the scenario explained in Point.2, which approach is better : "precomputation jobs as actors" vs "multiple spark-submits" ? Any pointers to clear my above doubts is highly appreciated. -- /Vamsi
