Sunday 1 January 2017

Map Reduce Architecture for Grid

Vol. 10  Issue 1
Year:2015
Issue:Jul-Sep
Title:Map Reduce Architecture for Grid
Author Name:Neeraj Rathore
Synopsis:
Recently many large scale computer systems are built in order to meet the high storage and processing demands of compute and data-intensive applications. MapReduce is one of the most popular programming models designed to support the development of such applications. MapReduce is a software framework for easily writing applications which process vast amount of data in-parallel, by using multiple CPUs on various machines, in a reliable, and fault tolerant manner. The various input and output parameters, that are part of this model have been identified. The proposed architecture is implemented in open source Java. The Map Reduce programming model is easy to use, even for programmers without experience with parallel and distributed systems, since it hides the details of parallelization, faulttolerance, locality optimization, and load balancing. It has a large variety of problems which are easily expressible as MapReduce computations. Finally, an implementation of MapReduce that scales to large clusters of machines comprising thousands of machines has been developed. The implementation makes efficient use of these machine resources and therefore is suitable for use on many of the large computational problems encountered.

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