I\'ve been trying Cascading, but I cannot see any advantage over the classic map reduce approach for writing jobs.
Map Reduce jobs gives me more freedom and Cascading se
I teach the Hadoop Boot Camp course for Scale Unlimited, and also make extensive use of Cascading in Bixo and for building web mining apps at Bixo Labs - so I think I've got a good appreciation for both approaches.
The biggest single advantage I see in Cascading is that it allows you to think about your data processing workflow in terms of operations on fields, and to (mostly) avoid worrying about how to transpose this view of the world onto the key/value model that's intrinsically part of any map-reduce implementation.
The biggest challenge with Cascading is that it is a different way of thinking about data processing workflows, and there's a corresponding conceptual "hump" you need to get over before it all starts making sense. Plus the error messages can remind one of the output from lex/yacc ("conflict in shift/reduce") :)
-- Ken