MapReduce Tutorial - Apache Hadoop Hadoop Map Reduce 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 hardware in a reliable, fault-tolerant manner. Typically both the input and the output of the job are stored in a file-system. 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 hardware in a reliable, fault-tolerant manner.
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How to Write a MapReduce Program MapR The Map Reduce framework consists of a single master per cluster-node. In this blog post we detail how data is transformed as it executes in the MapReduce framework, how to design and implement the Mapper, Reducer, and Driver classes; and execute the MapReduce program. Note The material from this blog post is from our free on-demand training course, Developing Hadoop Applications.