The Research of MapReduce Load Balancing Based on Multiple Partition Algorithm

Suzhen Wang, Haowei Zhou
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引用次数: 4

Abstract

In this paper, we propose a strategy to solve the load imbalance problem at MapReduce stage that caused from using the default partition algorithm of Hadoop platform. Through using multiple partitioning technique, this proposed strategy can refine the tasks and balance the inputs of reduce stage in the map phase. Furthermore, this proposed strategy can fully employ idle nodes to balance the high load nodes, in order to achieve the optimized job scheduling during the execution process of reduce stage.
基于多分区算法的MapReduce负载均衡研究
在本文中,我们提出了一种策略来解决由于使用Hadoop平台的默认分区算法而导致的MapReduce阶段的负载失衡问题。通过使用多重分区技术,该策略可以细化任务,平衡reduce阶段在map阶段的输入。此外,该策略可以充分利用空闲节点来平衡高负载节点,从而在reduce阶段的执行过程中实现最优的作业调度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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