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How to Use Special Keys in UNIX

UNIX operating system has some special keys. These you can use to interrupt the program processing or to resume it. The file management and keys totally different in UNIX kinds of operating systems. 

An example of a UNIX special key and its use.
Why You Need Interruption
A scenario where you made some mistake in the input command and you need to stop the further process. Then you can use the CTRL+C command. It is equal to the DELETE command.

List of UNIX Special Keys

RETURN key — The RETURN key signifies the end of a line of input. On any terminal, RETURN has a key of its own, or return may be typed by holding down the control key and typing a 'm'.Ctrl-m
Hint: Ctrl-m command is equal to RETURN key in Unix systems

DELETE: The DELETE key stops a program/command immediately, without waiting for it to finish. DELETE can be achieved equivalently with ctrl-c.
Hint: Ctrl-c Command you can use to interrupt the process.

Ctrl-s: Ctrl-s pauses the output and the program is suspended until you sta…

Top requirements for successful MapReduce jobs

The following techniques are needed to be successful of your map reduce jobs:
  • The mapper must be able to ingest the input and process the input record, sending forward the records that can be passed to the reduce task or to the final output directly, if no reduce step is required.
Mapreduce Jobs in Hadoop
  • The reducer must be able to accept the key and value groups that passed through the mapper, and generate the final output of this MapReduce step.
  • The job must be configured with the location and type of the input data, the mapper class to use, the number of reduce tasks required, and the reducer class and I/O types.
  • The TaskTracker service will actually run your map and reduce tasks, and the JobTracker service will distribute the tasks and their input split to the various trackers.
  • The cluster must be configured with the nodes that will run the TaskTrackers, and with the number of TaskTrackers to run per node. The TaskTrackers need to be configured with the JVM parameters, including the classpath for both the TaskTracker and the JVMs that will execute the individual tasks.
  • There are three levels of configuration to address to configure MapReduce on your cluster. From the bottom up, you need to configure the machines, the Hadoop MapReduce framework, and the jobs themselves.
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