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Did you know? MapReduce as a concept  is the heart of Hadoop. It is a programming concept that allows vast scalability across several servers in the cluster. If you are familiar with the clustered of scale out data processing solutions, then it is easier for you to understand the MapReduce concept.

MapReduce is a part of two tasks that the Hadoop programme performs. The MapReduce takes a set of data and then converts it into another set of data. Here, the individual elements are broken down into value pairs. This is known as the Map Job. The next function is the reduce job. Here it takes the output from a map, which is in the form of an input and then combines these data pairs into a smaller set of pairs. Therefore, just as the name states the reduce job is performed only after the map job. Several organisations solve their problems using the designs created by MapReduce, in order to yield performance gains of several orders of magnitude.

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