MapReduce (MR) framework enables you to write distributed applications to process large amounts of data from a filesystem such as HDFS in a reliable and fault-tolerant manner. When you want to use the MapReduce Framework to process data, it works through the creation of a job, which then runs on the framework to perform the tasks needed.
A MapReduce job usually works by splitting the input data across worker nodes running Mapper tasks in a parallel manner. At this time, any failures that happen either at the HDFS level or the failure of a Mapper task are handled automatically to be fault-tolerant. Once the Mappers are completed, the results are copied over the network to other machines running Reducer tasks.
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