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基于Hadoop的高速公路OD数据存储模型和计算方法

何家辉^1,2, 赵卓峰^1,2, 张宽^1,2, 张智^1,2

(1. 北方工业大学数据工程研究院, 北京 100144;2.
2. 大规模流数据集成与分析技术北京市重点实验室, 北京 100144)

Highway OD Data Storage Model and Calculation Method Based on Hadoop

HE Jia-Hui^1,2, ZHAO Zhuo-Feng^1,2, ZHANG Kuan^1,2, ZHANG Zhi^1,2

(1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China;2.
2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China)

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本文已被：浏览 2177次下载 2893次
Received:September 26, 2019 Revised:October 22, 2019

中文摘要: 高速公路OD数据是高速公路运营管理和状况分析的一类重要数据，如何利用海量的收费数据快速生成并有效管理高速公路OD数据是当前高速公路智能化建设中的一个重要问题.针对高速公路OD数据的种类多、周期长等问题，提出一种基于Hadoop的高速公路OD矩阵存储模型和相应的计算方法.建立统计高速公路车辆旅行时间、统计高速公路车流量两类OD矩阵作为存储模型.通过基于海量真实的高速公路收费数据的实验和传统的存储高速公路收费数据对比表明本文的存储方法相对于传统的关系数据存储，拥有更高效的存储效率并节省了存储空间.

中文关键词: OD矩阵存储模型 MapReduce

Abstract:Highway OD data is a kind of important data for highway operation management and condition analysis. How to use massive toll data to quickly generate and effectively manage highway OD data is an important problem in the current highway intelligent construction. Aiming at the problems of various types and long periods of highway OD data, a storage model of highway OD matrix based on Hadoop and corresponding calculation method are proposed. Two kinds of OD matrices are established as storage models, i.e. statistics of highway vehicle travel time and statistics of highway traffic flow. The comparison between the experiment based on massive real highway toll data and the traditional storage of highway toll data shows that the storage method proposed has better storage efficiency and saves storage space compared with the traditional relational data storage.

keywords: OD matrix storage model MapReduce

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Author Name	Affiliation	E-mail
HE Jia-Hui	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China	360963674@qq.com
ZHAO Zhuo-Feng	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China
ZHANG Kuan	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China
ZHANG Zhi	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China

Author Name	Affiliation	E-mail
HE Jia-Hui	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China	360963674@qq.com
ZHAO Zhuo-Feng	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China
ZHANG Kuan	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China
ZHANG Zhi	1. Institute of Data Engineering, North China University of Technology, Beijing 100144, China 2. Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data, Beijing 100144, China

引用文本：
何家辉,赵卓峰,张宽,张智.基于Hadoop的高速公路OD数据存储模型和计算方法.计算机系统应用,2020,29(5):159-166
HE Jia-Hui,ZHAO Zhuo-Feng,ZHANG Kuan,ZHANG Zhi.Highway OD Data Storage Model and Calculation Method Based on Hadoop.COMPUTER SYSTEMS APPLICATIONS,2020,29(5):159-166