Research on Computing Efficiency of MapReduce in Big Data Environment

Tilei Gao, Ming Yang, Rong Jiang, Yu Li, Yao Yao
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Abstract

The emergence of big data has brought a great impact on traditional computing mode, the distributed computing framework represented by MapReduce has become an important solution to this problem. Based on the big data, this paper deeply studies the principle and framework of MapReduce programming. On the basis of mastering the principle and framework of MapReduce programming, the time consumption of distributed computing framework MapReduce and traditional computing model is compared with concrete programming experiments. The experiment shows that MapReduce has great advantages in large data volume.
大数据环境下MapReduce计算效率研究
大数据的出现给传统的计算模式带来了很大的冲击,以MapReduce为代表的分布式计算框架成为解决这一问题的重要途径。基于大数据,本文深入研究了MapReduce编程的原理和框架。在掌握MapReduce编程原理和框架的基础上,通过具体的编程实验,对分布式计算框架MapReduce和传统计算模型的耗时进行了比较。实验表明,MapReduce在大数据量方面具有很大的优势。
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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