On Friday, January 30, 2015 at 5:00:31 PM UTC-5, Jason Wolfe wrote:

Thanks for the recommendation.  For now we're looking for a simple 
> low-level interface to MR, but we're also keeping an eye on parkour and 
> pigpen for more complex tasks down the road.  Can you explain why I might 
> prefer parkour to pigpen or vice-versa? 
>

Parkour actually *is* a low-level interface to MR.  It just exposes that 
interface though relatively Clojure-idiomatic and composable abstractions, 
which can make it look higher-level than it really is.  At Parkour's core 
is the support required for MR tasks to invoke a regular Clojure var-bound 
function in place of the `.run` method of a `Mapper` or `Reducer` class. 
 Everything else in Parkour is built to make using that primitive, 
low-level interface more composable, convenient, and pleasant; but 
ultimately nothing *replaces* that interface -- your Parkour MR Clojure 
task code runs in exactly the way equivalent raw Hadoop MR Java task code 
would.

Parkour's documentation includes a "motivation" document describing the 
project motivation in the face of the Clojure-Hadoop integration projects 
which existed when I started Parkour (including 
clojure-hadoop): 
https://github.com/damballa/parkour/blob/master/doc/motivation.md 
. It doesn't yet cover PigPen, although I certainly should add a section. I 
honestly haven't evaluated PigPen in detail, but the approach of compiling 
Clojure code to Pig seems excessively complex to me, to the point of only 
be worth it for organizations which have already made a significant 
investment in Pig.

-Marshall
 

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