{"title":"基于Hadoop的海量城市道路交通流数据的分布式存储与分析","authors":"Li Zhu, Yun Li","doi":"10.1109/WISA.2015.29","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":198938,"journal":{"name":"2015 12th Web Information System and Application Conference (WISA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Distributed Storage and Analysis of Massive Urban Road Traffic Flow Data Based on Hadoop\",\"authors\":\"Li Zhu, Yun Li\",\"doi\":\"10.1109/WISA.2015.29\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":198938,\"journal\":{\"name\":\"2015 12th Web Information System and Application Conference (WISA)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 12th Web Information System and Application Conference (WISA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISA.2015.29\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 12th Web Information System and Application Conference (WISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISA.2015.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.