基于Hadoop的海量城市道路交通流数据的分布式存储与分析

Li Zhu, Yun Li
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引用次数: 4

摘要

针对传统方法无法解决海量交通流数据的高效存储和分析快速增长的问题,本文采用Hadoop的分布式数据库HBase来存储海量的城市道路交通流数据。应用MapReduce的分布式计算框架,对交通流数据进行统计分析。实验结果验证了Hadoop集群高效的存储、计算和可扩展性,能够解决海量交通流数据的存储和处理问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Storage and Analysis of Massive Urban Road Traffic Flow Data Based on Hadoop
Because of the traditional methods failing to solve the efficient storage and analyze the problems with rapid growth of the massive traffic flow data, This paper adopts the distributed database HBase of Hadoop to store huge amounts of the urban road traffic flow data. By applying the distributed computing framework of MapReduce, statistical analysis of the traffic flow data is carried out. The experimental results validate the ability of Hadoop cluster, whose efficient storage, computing, scalability can deal with the problem of storing and processing the massive traffic flow data.
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