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Cooperation between Data Modeling and Simulation Modeling for Performance Analysis of Hadoop

机译:Hadoop性能分析数据建模与仿真建模的合作

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摘要

Performance analysis of a complex computing system requires a lot of time and effort. Many studies related to performance analysis have been conducted. Firstly, there are studies about workload modeling that model and analyze the observed workloads using statistical summaries. Also, there are studies to analyze system behavior and procedures through simulation modeling. However, there are some disadvantages to using only one approach for analyzing the complex system more accurately. Therefore, this paper presents cooperation between data modeling and simulation modeling for performance analysis of the system. The target system, Hadoop, is one of the representative big data platforms that can demonstrate the complexity of the analysis. Firstly, we identify the characteristics of Hadoop and divide them into two parts according to their characteristics. Then, we model and integrate them using each modeling approach. This paper presents the experiment to show the advantages of the cooperative modeling in the accuracy, execution time, and modeling extensibility.
机译:复杂计算系统的性能分析需要大量的时间和精力。已经进行了许多与性能分析相关的研究。首先,有关使用统计摘要的模型和分析观察工作负载的工作负载建模的研究。此外,还通过仿真建模分析系统行为和程序的研究。然而,使用一种方法可以更准确地使用一种方法来分析复杂系统。因此,本文介绍了数据建模与仿真建模与系统性能分析之间的合作。目标系统Hadoop是能够展示分析的复杂性的代表性大数据平台之一。首先,我们确定Hadoop的特征,并根据其特征将它们分成两部分。然后,我们模拟并使用每个建模方法集成它们。本文介绍了在准确性,执行时间和建模可扩展性中的协同建模的优势。

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