Map and Reduce have become buzzwords for bigdata processing, although they are not new concepts to computer scientists. Ever since the invention of functional languages, map and reduce have been the delight of computer scientists. The problem is big data stopped at incorporating only these two concepts from functional languages while ignoring several other interesting ones like first-class functions, filter, recursion etc. Some of these can be easily incorporated into bigdata processing techniques.

A nice way to deal with this is by building a parallel interpreter of functional languages. That will help building of parallel algorithms very straight forward. A classic example is using first class functions for building symbolic logic, optimization etc.

Follow

• 
• 
•