Astronomical Data Application Research Based on MapReduce

Qingfa Cui, Sheng-Chuan Wu
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引用次数: 1

Abstract

MapReduce as an abstract distributed computing programming model could solve the issues of parallel computing, such as load balancing, network storage, data distribution, resource allocation, fault tolerance. This makes it easy for people to manipulate large scale cluster systems without considering hardware details. The paper discusses completely how to apply MapReduce. In the construction of the experimental platform, this paper successfully designs and implements the cone search service based on MapReduce, The final result proves that the astronomical data application method based on MapReduce greatly improves the processing capacity.
基于MapReduce的天文数据应用研究
MapReduce作为一种抽象的分布式计算编程模型,可以解决并行计算中的负载均衡、网络存储、数据分布、资源分配、容错等问题。这使得人们可以轻松地操作大规模集群系统,而无需考虑硬件细节。本文对MapReduce的应用进行了全面的论述。在实验平台的搭建中,本文成功地设计并实现了基于MapReduce的圆锥搜索服务,最终结果证明基于MapReduce的天文数据应用方法大大提高了处理能力。
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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