计算机应用 ›› 2015, Vol. 35 ›› Issue (5): 1290-1295.DOI: 10.11772/j.issn.1001-9081.2015.05.1290

• 先进计算 • 上一篇    下一篇

分布式系统中局部处理机的设计与实现

魏敏, 刘以安, 吴鸿雁   

  1. 江南大学 数字媒体学院, 江苏 无锡 214122
  • 收稿日期:2014-12-19 修回日期:2015-02-07 出版日期:2015-05-10 发布日期:2015-05-14
  • 通讯作者: 魏敏
  • 作者简介:魏敏(1979-),女,江苏扬州人,讲师,硕士,主要研究方向:模式识别、图像处理; 刘以安(1963-),男,江苏涟水人,教授,博士,CCF会员,主要研究方向:数据融合、雷达对抗、模式识别、智能系统; 吴鸿雁(1961-), 女,上海人,副教授,硕士, 主要研究方向:人机界面、数据挖掘.

Design and implementation of local processor in a distributed system

WEI Min, LIU Yi'an, WU Hongyan   

  1. School of Digital Media, Jiangnan University, Wuxi Jiangsu 214122, China
  • Received:2014-12-19 Revised:2015-02-07 Online:2015-05-10 Published:2015-05-14

摘要:

针对企业生产过程中存在大量原始数据需要实时处理的问题,设计并实现了一个基于自定义架构的局部处理机.在设计之初以Hadoop的并行架构为参考,对MapReduce的工作原理和缓存方式进行了分析,在此基础上根据实际生产环境设计了一个"多类线程协同处理"的程序架构,并辅以两类自定义的数据缓存方式,保证了分布式系统中的局部处理机在接收、计算、上传各环节的并发性和正确性.该系统投入实际生产并连续使用一年有余,实现了将企业多个车间生成的原始数据进行实时处理的预期目标,具有很好的稳定性、有效性和可扩展性.实际应用结果表明,自定义的程序架构和有效的缓存方式能实现大量数据的同步处理及分析.

关键词: Hadoop, MapReduce, 数据缓存, 并发, 局部处理机, 分布式系统

Abstract:

Concerning the problem that there is a lot of data which need to be real-time processed during the production process, the local processor, based on multi-thread and co-processing architecture and two data buffer mechanisms was accomplished. As a reference, multi-functional thread in Hadoop's parallel architecture has an impressed impact on the design of the local processor, especially MapReduce principle. Based on the user-defined architecture, the local processor ensures data concurrency and correctness during receiving, computing and uploading. The system has been put into production for over one year. It can meet the enterprise requirements and has good stability, real-time, effectiveness and scalablility. The application result shows that the local processor can achieve synchronized analysis and processing of mass data.

Key words: Hadoop, MapReduce, data buffer, concurrency, local processor, distributed system

中图分类号: