And I will have to look at Onyx much more closely :)
On Thursday, October 19, 2017 at 2:01:52 PM UTC-7, Christopher Small wrote:
>
> Onyx has been very well maintained, has excellent documentation, and
> doesn't suffer any of the AOT issues.
>
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Check out https://www.youtube.com/watch?v=OxUHgP4Ox5Q for his talk about it.
On Thursday, October 19, 2017 at 4:01:52 PM UTC-5, Christopher Small wrote:
>
> Thanks for the helpful information Christopher. I'll have to look at
> Powderkeg.
>
> The AOT issue is a big one. Being able to launch thing
Thanks for the helpful information Christopher. I'll have to look at
Powderkeg.
The AOT issue is a big one. Being able to launch things from the REPL is
huge. That's actually one of the many advantages of Onyx over Storm (if
you're looking at the streaming side of things). Towards the end of my
us
> 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 compac
FWIW, I filed an issue and submitted a PR against flambo this summer.
It was merged on the same day and released two weeks later, so flambo seems
active when needed.
Erik.
> On 18 Oct 2017, at 13:02, Ray Miller wrote:
>
> This is partly prompted by the lack of activity on the Github repos. Are
Perhaps it is an obvious point, but I'll mention that like other Java
libraries, it is possible to use libraries from the Java Big Data ecosystem
e.g. Spark directly from Clojure using interop, or to consume Clojure code
as part of processing infrastructure written in other JVM languages. We've
Hi Ray
> This is partly prompted by the lack of activity on the Github repos.
Maybe you have higher standards here than I do... last commits on Flambo
and Sparkling were 3 and 2 months ago, respectively. That doesn't raise any
alarm bells for me personally. Moreover, looking at the contributor
Hi,
Here at Metail we have been using Clojure for medium-sized data processing
on AWS EMR. We started out with Cascalog about 5 years ago, switched to
Parkour 2 years ago, and are now considering a move to Spark.
My question is: is Clojure still a good choice for medium/large data
processing on E