That was it! Thanks so much Andreas. Can't believe I had overlooked that drop down in the interpreter settings. Mohit and Mich probably assumed I had tried that already.
Thanks everyone. Mark On Thu, Oct 6, 2016 at 8:35 AM, Andreas Lang <andreas.l...@aquilainsight.com > wrote: > Hi Mark, > > you may want to check the spark interpreter settings. In the most recent > version of zeppelin you can set it to shared, isolated or scoped. > > Shared: single interpreter and spark context (and the queuing you see) > Isolated: every notebook has its own interpreter and spark context > Scoped: every notebook has its own interpreter but they share a spark > context > https://zeppelin.apache.org/docs/latest/interpreter/spark.html > > Isolated is the most stable for what you want to do and shared the more > resource efficient for the machine you run zeppelin on. > > The comment of Mohit might be important if you have > spark.dynamicAllocation.enabled set to true and no limits on the number > and resources of executors. > > Andreas > > On Thu, 6 Oct 2016 at 16:28 Mark Libucha <mlibu...@gmail.com> wrote: > >> Mich, thanks for the suggestion. I tried your settings, but they did not >> solve the problem. >> >> I'm running in yarn-client mode, not local or standalone, so the >> resources in the Spark cluster (which is very large) should not be an >> issue. Right? >> >> The problem seems to be that Zeppelin is not submitting the 2nd job to >> the Spark cluster. >> >
