If you are running on Amazon, then it's always a crapshoot as well. M
> On Dec 21, 2015, at 4:41 PM, Josh Rosen <joshro...@databricks.com> wrote: > > @Eran, are Server 1 and Server 2 both part of the same cluster / do they have > similar positions in the network topology w.r.t the Spark executors? If > Server 1 had fast network access to the executors but Server 2 was across a > WAN then I'd expect the job to run slower from Server 2 duet to the extra > network latency / reduced bandwidth. This is assuming that you're running the > driver in non-cluster deploy mode (so the driver process runs on the machine > which submitted the job). > >> On Mon, Dec 21, 2015 at 1:30 PM, Igor Berman <igor.ber...@gmail.com> wrote: >> look for differences: packages versions, cpu/network/memory diff etc etc >> >> >>> On 21 December 2015 at 14:53, Eran Witkon <eranwit...@gmail.com> wrote: >>> Hi, >>> I know it is a wide question but can you think of reasons why a pyspark job >>> which runs on from server 1 using user 1 will run faster then the same job >>> when running on server 2 with user 1 >>> Eran >
