> The #bigdata channel over on Clojurians slack is also suspiciously quiet,
> as are many of the Google groups.
>
> Ray.
>
I worked with Sparkling and Flambo about a year ago, while Mr. Macbeth is a
fellow Portlander and has a solid API, I found Sparkling to be somewhat
more direct and compact. For ETL via Hadoop I wouldn't hesitate to try
either of these libraries. I found them to be stable and preferable to
using Spark in Scala. However, I used Powderkeg
(https://github.com/HCADatalab/powderkeg) a bit and found it the most
intriguing. Christophe Grand last updated PowderKeg three hours ago (from
time of my posting obviously). Powderkeg relies heavily on Clojure
transducers and is the only Clojure Spark library I am aware of which
doesn't require AOT compilation -- you can use a Clojure repl to directly
spawn jobs on a Spark cluster. If you are interested in Clojure
interoperability with Spark, I would look at Powderkeg first.
If you require Spark Streaming, you might be better off writing Scala, or
considering another streaming solution such as Storm. The closest I have
come to getting Spark Streaming to work in Clojure was with Powderkeg. It
might be worth seeing if Powderkeg has made progress in this area.
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