Since the MapReduce library is designed to help process very large amounts of data using hundreds or thousands of machines, the library must tolerate machine failures gracefully.

Hadoop MapReduce is a software framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) of commodity …

Using these two functions, MapReduce parallelizes the computation across thousands of machines, automatically load balancing, recovering from failures, and producing the correct result.

MapReduce: Simplified Data Processing on Large Clusters Authors: Jeffrey Dean and Sanjay Ghemawat

Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same …

Issues come from above conditions How to parallelize the computation How to distribute the data How to handle machine failure MapReduce allows developer to express the simple computation, but hides …

MAPREDUCE IS A programming model for processing and generating large data sets.4 Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs and a …