> 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. -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en --- You received this message because you are subscribed to the Google Groups "Clojure" group. To unsubscribe from this group and stop receiving emails from it, send an email to clojure+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
