MapReduce is a massive parallel processing framework that processes faster, scalable, and fault tolerant data of a distributed environment. Similar to HDFS, Hadoop MapReduce can also be executed even in commodity hardware, and assumes that nodes can fail anytime and still process the job. MapReduce can process a large volume of data in parallel, by dividing a task into independent sub-tasks. MapReduce also has a master-slave architecture.
The input and output, even the intermediary output in a MapReduce job, are in the form of <Key, Value> pair. Key and Value have to be serializable and do not use the Java serialization package, but have an interface, which has to be implemented, and which can be efficiently serialized, as the data process has to move from one node to another. Key has to be a class that implements a WritableComparable interface, which is necessary for sorting the key, and Value has to be a class that implements a Writable interface.
