Yuanquan Fan

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An approach based on Virtual Partition is proposed to improve the load balance in Reduce phase in MapReduce-based system in cloud computing. After each Map task finished, the output keys are partitioned to different virtual partitions according to Hash Function. And LBVP (a load balance algorithm based on continuous virtual partition) is designed to combine(More)
MapReduce has emerged as a popular computing model for parallel processing of big data. However, we observe that the native hash partitioning of MapReduce systems leads to frequent uneven data distribution among reduce tasks. The uneven data distribution results in load imbalance among reduce tasks, and thus hampers the performance of MapReduce systems.(More)
Map Reduce has emerged as a popular computing model for parallel processing of cloud computing. Map Reduce performance analysis and modeling is needed to guide performance optimization and job scheduling. However, we observed that it is difficult to build a performance model due to various aspects of workload behavior and heterogeneity among cluster nodes(More)
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