We have been busy here working with our little dataset library and I wanted
to talk about some of the upgrades that I think are important/interesting.

We have first class support of Apache Arrow now which means I took the time
to actually understand, byte-by-byte, the binary on-disk format. I also
found a memory mapping library that I think is great, larray
<https://github.com/xerial/larray>.

Arrow files are really sequences of datasets and we have a brand new
namespace
<https://github.com/techascent/tech.ml.dataset/blob/master/src/tech/ml/dataset/reductions.clj>
which will grow over time devoted to really large (multiple GB, out of
memory) reductions over sequences of datasets which have competitive
performance characteristics with anything out there.

Lastly, we have a (great!) blog post exploring memory mapping, apache
arrow, and the tech.datatype bindings
<https://github.com/techascent/tech.datatype/blob/master/src/tech/v2/datatype/mmap.clj>
to larray. It specifically highlights how nice Clojure is for exploring
binary file formats — doing this brought back memories of doing similar
things in C++ and wow, with Clojure I get the same performance and I can
actually see what I am working with! Much appreciation to Alex, Rich, and
the team!

https://techascent.com/blog/memory-mapping-arrow.html

Enjoy!

Chris

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