Could you try to disable the new feature of reused worker by: spark.python.worker.reuse = false
On Tue, Jan 20, 2015 at 11:12 PM, Tassilo Klein <tjkl...@bwh.harvard.edu> wrote: > Hi, > > It's a bit of a longer script that runs some deep learning training. > Therefore it is a bit hard to wrap up easily. > > Essentially I am having a loop, in which a gradient is computed on each node > and collected (this is where it freezes at some point). > > grads = zipped_trainData.map(distributed_gradient_computation).collect() > > > The distributed_gradient_computation mainly contains a Theano derived > function. The theano function itself is a broadcast variable. > > Let me know if you need more information. > > Best, > Tassilo > > On Wed, Jan 21, 2015 at 1:17 AM, Davies Liu <dav...@databricks.com> wrote: >> >> Could you provide a short script to reproduce this issue? >> >> On Tue, Jan 20, 2015 at 9:00 PM, TJ Klein <tjkl...@gmail.com> wrote: >> > Hi, >> > >> > I just recently tried to migrate from Spark 1.1 to Spark 1.2 - using >> > PySpark. Initially, I was super glad, noticing that Spark 1.2 is way >> > faster >> > than Spark 1.1. However, the initial joy faded quickly when I noticed >> > that >> > all my stuff didn't successfully terminate operations anymore. Using >> > Spark >> > 1.1 it still works perfectly fine, though. >> > Specifically, the execution just freezes without any error output at one >> > point, when calling a joint map() and collect() statement (after having >> > it >> > called many times successfully before in a loop). >> > >> > Any clue? Or do I have to wait for the next version? >> > >> > Best, >> > Tassilo >> > >> > >> > >> > -- >> > View this message in context: >> > http://apache-spark-user-list.1001560.n3.nabble.com/Spark-1-1-slow-working-Spark-1-2-fast-freezing-tp21278.html >> > Sent from the Apache Spark User List mailing list archive at Nabble.com. >> > >> > --------------------------------------------------------------------- >> > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> > For additional commands, e-mail: user-h...@spark.apache.org >> > > > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
