Applying MapReduce Programming Model for Handling Scientific Problems

Yun-hee Kang, Y. B. Park
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Abstract

According to data volumes in scientific applications have grown exponentially, new scientific methods to analyze and organize the data are required. MapReduce programming is driving Internet services and those services operation in a cloud environment. Hence it is required to efficiently provide resources for handling diverse MapReduce applications. In this paper we show the Hadoop application with map and reduce functions for the data transformation.
应用MapReduce编程模型处理科学问题
随着科学应用中的数据量呈指数级增长,需要新的科学方法来分析和组织数据。MapReduce编程正在推动互联网服务和这些服务在云环境中运行。因此,需要有效地提供资源来处理不同的MapReduce应用程序。在本文中,我们展示了使用map和reduce函数进行数据转换的Hadoop应用程序。
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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