does anyone find Cascading for Hadoop Map Reduce useful?

Question

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

Answer 1

Cascading is a wrapper around Hadoop that provides Taps and Sinks to and from Hadoop.

Writing Mappers and Reducers for all your tasks is going to be tedious. Try writing one Cascading job and then you're all set to avoiding writing any mappers and reducers.

You also want to look at cascading Taps and Schemes (this is how you input data into your cascading processing job).

With these two, i.e. Ability to avoid writing ad-hoc Hadoop Mappers with Reducers and the ability to consume a wide variety of data sources, you can solve a lot of your data processing very fast and effective.

Cascading is more than just a simple wrapper around hadoop, I am trying to keep the answer simple. For example, I've ported a huge mysql database containing terabytes of data to log files using cascading jdbc tap