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MapReduce is an important programming paradigm on big data-intensive computing using share-nothing cluster containing ten of thousands of nodes, in which computing nodes also acts as storage nodes. Since tasks belonging to different jobs are physical executing entities scattered among the whole cluster, task scheduling plays a crucial role in MapReduce systems. For data consolidation and utilization,...
Scheduling algorithms place a crucial role in MapReduce systems. Several recent scheduling algorithms, however, are all under Job-Task scheduling model which makes task scheduling confined, leading to poor task scheduling preference such as data locality, scan sharing and etc. These characteristics are very important heuristics on data intensive computing and helpful in improving system throughput...
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