摘要
笔者阐述了应用大数据技术和并行计算技术,存储、处理物流业务中的车货配载数据,物流业务中配货数据的海量数据问题和货源车源数据高效智能匹配问题,阻碍了系统运行和后续业务功能的开展。基于此,阐述了采用并行计算技术解决车源数据和货源数据的智能匹配问题,并提出应采用CMD-Worker-Handler编程框架构建系统,保证软件模块具有高可靠性。
The author elaborates on the application of large data technology and parallel computing technology to store and process the vehicle and cargo stowage data in logistics business, the massive data in logistics business and the efficient and intelligent matching of vehicle source data, which hinder the system operation and the development of subsequent business functions. Based on this, this paper expounds how to use parallel computing technology to solve the problem of intelligent matching between vehicle source data and vehicle source data, and puts forward the application of CMD-Worker-Handler programming framework to build the system, so as to achieve high reliability of software modules.
引文
[1]邓子云,黄友森,杨晓峰,等.基于SOA-BPM组合架构的第三方物流企业信息系统集成平台[J].计算机系统应用,2010,19(3):1-6.