Brandon,
how much memory are you giving to your executors - did you check if there
were dead executors in your application logs.. Most likely you require
higher memory for executors..
Ashish
On Sun, May 8, 2016 at 1:01 PM, Brandon White <bwwintheho...@gmail.com>
wrote:
> Hello all,
>
> I am running a Spark application which schedules multiple Spark jobs.
> Something like:
>
> val df = sqlContext.read.parquet("/path/to/file")
>
> filterExpressions.par.foreach { expression =>
> df.filter(expression).count()
> }
>
> When the block manager fails to fetch a block, it throws an exception
> which eventually kills the exception: http://pastebin.com/2ggwv68P
>
> This code works when I run it on one thread with:
>
> filterExpressions.foreach { expression =>
> df.filter(expression).count()
> }
>
> But I really need the parallel execution of the jobs. Is there anyway
> around this? It seems like a bug in the BlockManagers doGetRemote function.
> I have tried the HTTP Block Manager as well.
>
