I can imagine a few reasons. Adding workers might cause fewer tasks to execute locally (?) So you may be execute more remotely.
Are you increasing parallelism? for trivial jobs, chopping them up further may cause you to pay more overhead of managing so many small tasks, for no speed up in execution time. Can you provide any more specifics though? you haven't said what you're running, what mode, how many workers, how long it takes, etc. On Sat, Feb 21, 2015 at 2:37 PM, Deep Pradhan <pradhandeep1...@gmail.com> wrote: > Hi, > I have been running some jobs in my local single node stand alone cluster. I > am varying the worker instances for the same job, and the time taken for the > job to complete increases with increase in the number of workers. I repeated > some experiments varying the number of nodes in a cluster too and the same > behavior is seen. > Can the idea of worker instances be extrapolated to the nodes in a cluster? > > Thank You --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
