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A Two Pass Scheduling Policy Based Resource Allocation for MapReduce
2015
Procedia Computer Science
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Big Data and parallel computing are used extensively for processing large quantities of data, structured, semi structured or totally unstructured. MapReduce and Hadoop are used for the parallel data processing of these kinds of data. Various scheduling policies are used for MapReduce scheduling which is discussed in detail and a new scheduling technique Two Phase Scheduling Policy (TPSP) based resource allocation for MapReduce is implemented and the efficiency is verified.
doi:10.1016/j.procs.2015.02.110
fatcat:hcvxi2rf7ra5nochiklaq5rndm