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MapReduce is presently established as an important distributed and parallel programming model with wide acclaim for large scale computing. Intelligent scheduling decisions can help in reducing the overall runtime of the jobs. MapReduce performance is currently limited by its default scheduler, which does not adapt well in heterogeneous environments. Heterogeneous environments were considered in Longest...
MapReduce is currently a significant model for distributed processing of large-scale data intensive applications. MapReduce default scheduler is limited by the assumption that nodes of the cluster are homogeneous and that tasks progress linearly. This model of MapReduce scheduler is used to decide speculatively re-execution of straggler tasks. The assumption of homogeneity does not always hold in...
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