The patch we use in production is for 1.5. We're porting the patch to master (and downstream to 2.0, which is presently very similar) with the intention of submitting a PR "soon". We'll push it here when it's ready: https://github.com/VideoAmp/spark-public.
Regarding benchmarking, we have a suite of Spark SQL regression tests which we run to check correctness and performance. I can share our findings when I have them. Cheers, Michael > On Jun 29, 2016, at 2:39 PM, Maciej Bryński <mac...@brynski.pl> wrote: > > 2016-06-29 23:22 GMT+02:00 Michael Allman <mich...@videoamp.com>: >> I'm sorry I don't have any concrete advice for you, but I hope this helps >> shed some light on the current support in Spark for projection pushdown. >> >> Michael > > Michael, > Thanks for the answer. This resolves one of my questions. > Which Spark version you have patched ? 1.6 ? Are you planning to > public this patch or just for 2.0 branch ? > > I gladly help with some benchmark in my environment. > > Regards, > -- > Maciek Bryński --------------------------------------------------------------------- To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
