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MapReduce system productivity measurement model and measuring approach

机译:MapReduce系统生产力测量模型和测量方法

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How to effectively utilize the computing resource remains a longstanding challenge in MapReduce application, and MapReduce system productivity has become a major issue in research field. In the paper, we explored the productivity mathematical models for MapReduce system, defining the productivity as the ratio of the workload and energy consumption per unit time, and proposed the measurement approach for MapReduce system productivity. Based on the measurement model and approach, this paper selected CPU intensive and I/O intensive computing in MapReduce to measure and evaluate MapReduce system productivity. Finally the measurement and evaluation result showed that productivity model and approach in the paper is reasonable and valid for architecture design of MapReduce system in production environment.
机译:如何有效利用计算资源仍然是MapReduce应用中的长期挑战,MapReduce系统的生产率已成为研究领域的主要问题。在本文中,我们探索了MapReduce系统的生产率数学模型,将生产率定义为工作量与单位时间能耗之间的比率,并提出了MapReduce系统生产率的度量方法。基于测量模型和方法,本文在MapReduce中选择了CPU密集型和I / O密集型计算,以测量和评估MapReduce系统的生产率。最后的测量和评估结果表明,本文的生产率模型和方法对于生产环境中的MapReduce系统的体系结构设计是合理有效的。

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