Thank you for sharing it, Ian. Dongjoon.
On Fri, May 20, 2022 at 9:27 AM Ian Joiner <iajoiner...@gmail.com> wrote: > There is already a Rust ORC reader: > https://rustrepo.com/repo/travisbrown-orcrs > We still need a writer though. If I have 6 months to do so I can write one. > Then I can also integrate it into Arrow Rust. > > Ian > > On Friday, May 20, 2022, Dongjoon Hyun <dongjoon.h...@gmail.com> wrote: > > > +1 for Owen's advice. > > > > BTW, Rust ORC reader & writer sounds like a great idea. > > > > Dongjoon. > > > > > > On Thu, May 19, 2022 at 10:28 PM Owen O'Malley <owen.omal...@gmail.com> > > wrote: > > > > > This is interesting, but it sounds like it corresponds more to the rle > > > encoding that we do rather than the generic compression code. > > > > > > Has anyone done a Java version of the library? It is faster to iterate > on > > > this kind of design in Java. On the other hand, I’ve heard that someone > > is > > > thinking about doing a Rust ORC reader & writer, but it isn’t done yet. > > 😊 > > > > > > .. Owen > > > > > > > On May 19, 2022, at 17:16, Dongjoon Hyun <dongjoon.h...@gmail.com> > > > wrote: > > > > > > > > Thank you for sharing, Martin. > > > > > > > > For codec one, you can take advantage of our benchmark suite > > > > (NONE/ZLIB/SNAPPY/ZSTD) to show the benefits in ORC format. > > > > > > > > > > > https://github.com/apache/orc/blob/main/java/bench/core/src/ > > java/org/apache/orc/bench/core/CompressionKind.java#L34-L37 > > > > > > > > For the Spark connector one, I'd like to recommend you to send > > dev@spark > > > > too. You will get attention in both parts (codec and connector). > > > > > > > > Then, I'm looking forward to seeing your benchmark result. > > > > > > > > Dongjoon. > > > > > > > > > > > >> On Thu, May 19, 2022 at 4:12 PM Martin Loncaric < > > m.w.lonca...@gmail.com > > > > > > > >> wrote: > > > >> > > > >> I've developed a stable codec for numerical columns called Quantile > > > >> Compression <https://github.com/mwlon/quantile-compression>. > > > >> It has about 30% higher compression ratio than even Zstd for similar > > > >> compression and decompression time. It achieves this by tailoring to > > the > > > >> data type (floats, ints, timestamps, bools). > > > >> > > > >> I'm using it in my own projects, and a few others have adopted it, > but > > > it > > > >> would also be perfect for ORC columns. Assuming a 50-50 split > between > > > >> text-like and numerical data, it could reduce the average ORC file > > size > > > by > > > >> over 10% with no extra compute cost. Incorporating it into ORC would > > be > > > >> quite powerful since the codec by itself only works on a single flat > > > column > > > >> of non-nullable numbers. > > > >> > > > >> Would the ORC community be interested in this? How can we make this > > > >> available to users? I've already built a Spark connector > > > >> <https://github.com/pancake-db/spark-pancake-connector> for a > project > > > >> using > > > >> this codec and gotten fast query times. > > > >> > > > >> Thanks, > > > >> Martin > > > >> > > > > > >
