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The computations in MapReduce are composed of map and reduce tasks. Although performance of map tasks has been investigated extensively, most researches ignore the scheduling of reduce tasks. This paper proposes a divisible load scheduling model for reduce tasks in a MapReduce job. By analyzing intermediate data transmission and reduce task execution in reduce phase, reduce tasks are abstracted as...
MapReduce is a programming model for data-intensive applications. The performance of MapReduce is greatly affected by the scheduling efficiency, which needs to consider both the parallelism of processing and overhead of data transmission. Lots of researches only focus on optimizing scheduling mechanisms or data storage strategies to reduce the overhead of data transmission in big data applications...
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