MapReduce is a framework for processing huge datasets on certain kinds of distributable problems using a large number of computers (nodes), collectively referred to as a cluster (if all nodes use the same hardware) or as a grid (if the nodes use different hardware). Computational processing can occur on data stored either in a filesystem (unstructured) or within a database (structured).

“Map” step: The master node takes the input, partitions it up into smaller sub-problems, and distributes those to worker nodes. A worker node may do this again in turn, leading to a multi-level tree structure. The worker node processes that smaller problem, and passes the answer back to its master node.

“Reduce” step: The master node then takes the answers to all the sub-problems and combines them in some way to get the output — the answer to the problem it was originally trying to solve.

— Wikipedia on MapReduce

2011.04.27 Wednesday ACHK