This could also have utility in memory via things like zram/zswap, right? Mac also has a memory compressor?
I don't think Parquet is an option for me unless the integration with Arrow is tighter than I imagine (i.e. zero-copy). That said, I confess I know next to nothing about Parquet. On Thu, Jan 23, 2020 at 11:23 AM Antoine Pitrou <anto...@python.org> wrote: > > > Le 23/01/2020 à 18:16, John Muehlhausen a écrit : > > Perhaps related to this thread, are there any current or proposed tools to > > transform columns for fixed-length data types according to a "shuffle?" > > For precedent see the implementation of the shuffle filter in hdf5. > > https://support.hdfgroup.org/ftp/HDF5//documentation/doc1.6/TechNotes/shuffling-algorithm-report.pdf > > > > For example, the column (length 3) would store bytes 00 00 00 00 00 00 00 > > 00 00 01 02 03 to represent the three 32-bit numbers 00 00 00 01 00 00 00 > > 02 00 00 00 03 (I'm writing big-endian even if that is not actually the > > case). > > > > Value(1) would return 00 00 00 02 by referring to some metadata flag that > > the column is shuffled, stitching the bytes back together at call time. > > > > Thus if the column pages were backed by a memory map to something like > > zfs/gzip-9 (my actual use-case), one would expect approx 30% savings in > > underlying disk usage due to better run lengths. > > > > It would enable a space/time tradeoff that could be useful? The filesystem > > itself cannot easily do this particular compression transform since it > > benefits from knowing the shape of the data. > > For the record, there's a pull request adding this encoding to the > Parquet C++ specification. > > Regards > > Antoine.
