Note:

* Input to the Reducer is the sorted output of the mappers. 

* The framework calls the application's Reduce function once for each unique key in the sorted order.

* Example:

For the given sample input the first map emits:

< Hello, 1>

< World, 1>

< Bye, 1>

< World, 1>

The second map emits:

< Hello, 1>

< Hadoop, 1>

< Goodbye, 1>

< Hadoop, 1>

JobTracker is the daemon service for submitting and tracking MapReduce jobs in Hadoop. There is only One Job Tracker process run on any hadoop cluster. Job Tracker runs on its own JVM process. In a typical production cluster its run on a separate machine. Each slave node is configured with job tracker node location. The JobTracker is single point of failure for the Hadoop MapReduce service. If it goes down, all running jobs are halted. JobTracker in Hadoop performs following actions(from Hadoop Wiki:)

Client applications submit jobs to the Job tracker.

The JobTracker talks to the NameNode to determine the location of the data

The JobTracker locates TaskTracker nodes with available slots at or near the data

The JobTracker submits the work to the chosen TaskTracker nodes.

The TaskTracker nodes are monitored. If they do not submit heartbeat signals often enough, they are deemed to have failed and the work is scheduled on a different TaskTracker.

A TaskTracker will notify the JobTracker when a task fails. The JobTracker decides what to do then: it may resubmit the job elsewhere, it may mark that specific record as something to avoid, and it may may even blacklist the TaskTracker as unreliable.

When the work is completed, the JobTracker updates its status.

Client applications can poll the JobTracker for information.