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针对我国铁路机车定位数据丢失时有发生的现象,阐述了以现有较成熟的GNSS/INS/DR(Global Navigation Satellite System/Inertial Navigation System/Dead Reckoning)组合定位装置构建铁路机车定位的系统架构。在此基础上,针对海量位置数据,引入Hadoop技术,给出了采用HBase存储海量位置信息数据的方法,采用MapReduce校正位置信息数据及安全距离计算的方法。经实验验证,该方案在需要大量数据存取的情况下,采用MapReduce进行分布式数据分析效率更高,扩展性更好。
Aiming at the phenomenon that locomotive data of locomotive locates at the time of loss in our country, this paper describes the system architecture of locomotive locomotive positioning based on the combination of existing GPS / INS / DR (Global Navigation Satellite System / Inertial Navigation System / Dead Reckoning) locating device. Based on this, Hadoop technology is introduced for mass location data. The method of using HBase to store mass location information data and the method of using MapReduce to correct location information data and calculating the safety distance are given. The experimental results show that the proposed scheme is more efficient and scalable with MapReduce for distributed data analysis when it requires a large amount of data access.