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Evaluation of Performance Saturation Using the Hadoop Framework

机译:使用Hadoop框架评估性能饱和度

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It is estimated that about 2.5 exabytes of data are produced daily. This large volume of data has brought new possibilities of applications, however, to manage this large volume of data, new technologies were needed. One of the most prominent technologies is the Hadoop framework, which implements a parallel task processing paradigm. The aim of this paper is to present the results of our group's research which analyzed the performance of the Hadoop framework for Big Data processing. The performance evaluation focused on finding the saturation point of Hadoop performance by varying the number of nodes in the cluster applying two benchmarks - TeraSort and Pi. The analysis was performed using a real infrastructure, implementing the system in a physical cluster, providing a general approach of performance analysis in the Hadoop framework for developers and researchers.
机译:据估计,每天生产约2.5个exabytes的数据。这种大量的数据带来了新的应用的可能性,但是,要管理这么大量的数据,所需的新技术。最突出的技术之一是Hadoop框架,它实现了一个并行任务处理范例。本文的目的是展示我们集团的研究结果,分析了Hadoop框架的大数据处理的表现。通过改变应用两个基准 - Terasort和PI的集群中的节点数来找到Hadoop性能的饱和度点的绩效评估专注于找到Hadoop性能的饱和点。使用实际基础设施进行分析,在物理群集中实现系统,提供开发人员和研究人员Hadoop框架的绩效分析的一般方法。

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