Hi I don't have a lot of experience with the fine-grained scheduler. It's deprecated and fairly old now. CPUs should be relinquished as tasks complete, so I'm not sure why you're seeing what you're seeing. There have been a few discussions on the spark list regarding deprecating the fine-grained scheduler, and no one seemed too dead-set on keeping it. I'd recommend you move over to coarse-grained.
On Fri, Dec 16, 2016 at 8:41 AM, Chawla,Sumit <sumitkcha...@gmail.com> wrote: > Hi > > I am using Spark 1.6. I have one query about Fine Grained model in Spark. > I have a simple Spark application which transforms A -> B. Its a single > stage application. To begin the program, It starts with 48 partitions. > When the program starts running, in mesos UI it shows 48 tasks and 48 CPUs > allocated to job. Now as the tasks get done, the number of active tasks > number starts decreasing. How ever, the number of CPUs does not decrease > propotionally. When the job was about to finish, there was a single > remaininig task, however CPU count was still 20. > > My questions, is why there is no one to one mapping between tasks and cpus > in Fine grained? How can these CPUs be released when the job is done, so > that other jobs can start. > > > Regards > Sumit Chawla > > -- Michael Gummelt Software Engineer Mesosphere
