MapReduce在云计算中的应用

Gaizhen Yang
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引用次数: 27

摘要

Hadoop为云平台程序员提供了一个复杂的框架,其中MapReduce是一个用于大规模数据集并行计算的编程模型。通过MapReduce分布式处理框架,我们不仅能够处理大规模的数据,而且可以隐藏很多繁琐的细节,可扩展性也很棒。本文分析了Hadoop架构和MapReduce的工作原理,描述了如何在云平台上执行MapReduce作业,如何编写Mapper和Reducer类,以及如何使用对象,提出了一个基于MapReduce框架的程序,实现分布式编程,对比结果表明使用MapReduce架构简化了分布式编程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Application of MapReduce in the Cloud Computing
Hadoop provides a sophisticated framework for cloud platform programmers, which, MapReduce is a programming model for large-scale data sets of parallel computing. By MapReduce distributed processing framework, we are not only capable of handling large-scale data, and can hide a lot of tedious details, scalability is also wonderful. This paper analyzes the Hadoop architecture and MapReduce Working principle, described how to perform a MapReduce job in the cloud platform, how to write Mapper and Reducer classes, and how to use the object, proposed a program based on the MapReduce framework that enables distributed programming, Comparison results show that use of MapReduce architecture simplifies distributed programming.
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