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The growth of data used by data-intensive computations, e.g. Geographical Information Systems (GIS), has far outpaced the growth of the power of a single processor. The increasing demand of data-intensive applications calls for distributed computing. In this paper, the authors propose a high performance workflow system MRGIS, a parallel and distributed computing platform based on MapReduce clusters, to execute GIS applications efficiently. MRGIS consists of a design interface, a task scheduler, and a runtime support system.
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