FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -MapReduce is an attractive model for parallel data processing in high-performance cluster computing environments. The scalability of MapReduce is proven to be high, because a job in the MapReduce model is partitioned into numerous small tasks running on multiple machines in a large-scale cluster.

Detailed explanation-2: -MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster.

Detailed explanation-3: -MapReduce facilitates concurrent processing by splitting petabytes of data into smaller chunks, and processing them in parallel on Hadoop commodity servers. In the end, it aggregates all the data from multiple servers to return a consolidated output back to the application.

Detailed explanation-4: -MapReduce is a processing technique and a program model for distributed computing based on java. The MapReduce algorithm contains two important tasks, namely Map and Reduce. Map takes a set of data and converts it into another set of data, where individual elements are broken down into tuples (key/value pairs).