The Implementation of Database Partitioning Based on Streaming Framework

摘要：

　　Horizontal and vertical partitioning can increase the performance of the database and simplify data management.However traditional partitioning techniques cant deal with stream queries efficiently.In this paper we present WSPS: a workload-driven stream partitioning system to solve the above problem by the integration of partitioning technology and streaming framework.We construct a dynamic data model, cluster and merge nodes according to the node affinity, then get the optimal partitioning scheme according to a cost model.WSPS can deal with stream data and obtain real time partitioning scheme.Experimental results show that WSPS can improve the partitioning efficiency and reduce the computing complexity.Additionally, WSPS has good performance on horizontal scaling and high-throughput adaption.

关键词： database partitioning stream data workload-driven streaming framework

作者: Mengyu Guo Hong Kang

作者单位: College of Computer and Control Engineering, Nankai University

会议类型: 国际会议

会议名称: The 13th Web Information Systems and Applications Conference(第十三届全国web信息系统及其应用学术会议)(WISA2016)、The 1st Symposium on Big Data Processing and Analysis)( BDPA 2016)第一届全国大数据处理与分析学术研讨会、The 1st Workshop on Information System Security)(ISS2016)(第一届全国信息系统安全研讨会

会议地点: 武汉

会议语种:英文

页码: 157-162

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）