Stefan, Does your source data contain varchar columns? We've seen instances where Drill isn't as efficient as it can be when Parquet is dealing with variable length columns.
-- Zelaine On Fri, May 13, 2016 at 9:26 AM, Stefan Sedich <stefan.sed...@gmail.com> wrote: > Thanks for getting back to me so fast! > > I was just playing with that now, went up to 8GB and still ran into it, > trying to go higher to see if I can find the sweet spot, only got 16GB > total RAM on this laptop :) > > Is this an expected amount of memory for not an overly huge table (16 > million rows, 6 columns of integers), even now at a 12GB heap seems to have > filled up again. > > > > Thanks > > On Fri, May 13, 2016 at 9:20 AM Jason Altekruse <ja...@dremio.com> wrote: > > > I could not find anywhere this is mentioned in the docs, but it has come > up > > a few times one the list. While we made a number of efforts to move our > > interactions with the Parquet library to the off-heap memory (which we > use > > everywhere else in the engine during processing) the version of the > writer > > we are using still buffers a non-trivial amount of data into heap memory > > when writing parquet files. Try raising your JVM heap memory in > > drill-env.sh on startup and see if that prevents the out of memory issue. > > > > Jason Altekruse > > Software Engineer at Dremio > > Apache Drill Committer > > > > On Fri, May 13, 2016 at 9:07 AM, Stefan Sedich <stefan.sed...@gmail.com> > > wrote: > > > > > Just trying to do a CTAS on a postgres table, it is not huge and only > has > > > 16 odd million rows, I end up with an out of memory after a while. > > > > > > Unable to handle out of memory condition in FragmentExecutor. > > > > > > java.lang.OutOfMemoryError: GC overhead limit exceeded > > > > > > > > > Is there a way to avoid this without needing to do the CTAS on a subset > > of > > > my table? > > > > > >
