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Big Data Analytics with R and Hadoop by Vignesh Prajapati

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Introducing Hadoop MapReduce

Basically, the MapReduce model can be implemented in several languages, but apart from that, Hadoop MapReduce is a popular Java framework for easily written applications. It processes vast amounts of data (multiterabyte datasets) in parallel on large clusters (thousands of nodes) of commodity hardware in a reliable and fault-tolerant manner. This MapReduce paradigm is divided into two phases, Map and Reduce, that mainly deal with key-value pairs of data. The Map and Reduce tasks run sequentially in a cluster, and the output of the Map phase becomes the input of the Reduce phase.

All data input elements in MapReduce cannot be updated. If the input (key, value) pairs for mapping tasks are changed, it will not be reflected ...

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