Although the Hadoop framework is implemented in Java is a simple application that counts the number of occurences of each word in a given input set.

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More details about the command line options are available at Commands Guide.

Running Here, will be placed and unzipped into a directory by the name "myarchive.zip".

Users can specify a different symbolic name for files and archives passed through -files and -archives option, using #.

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.

The framework takes care of scheduling tasks, monitoring them and re-executes the failed tasks.

Typically the compute nodes and the storage nodes are the same, that is, the Map Reduce framework and the Hadoop Distributed File System (see HDFS Architecture Guide) are running on the same set of nodes.This configuration allows the framework to effectively schedule tasks on the nodes where data is already present, resulting in very high aggregate bandwidth across the cluster.The Map Reduce framework consists of a single master per cluster-node.The master is responsible for scheduling the jobs' component tasks on the slaves, monitoring them and re-executing the failed tasks.The slaves execute the tasks as directed by the master.Minimally, applications specify the input/output locations and supply which then assumes the responsibility of distributing the software/configuration to the slaves, scheduling tasks and monitoring them, providing status and diagnostic information to the job-client.