A Workload-Driven Vertical Partitioning Approach Based on Streaming Framework

摘要：

　　In cloud computing environment,data information is growing exponentially.Which raises new challenges in efficient distributed data storage and management for large scale OLTP and OLAP applications.Horizontal and vertical database partitioning can improve the performance and manageability for shared-nothing systems which are popular in nowadays.However,the existing partitioning techniques cant deal with dynamic information efficiently and cant get the real-time partitioning strategies.In this paper,we present WSPA: a workload-driven stream vertical partitioning approach based on streaming framework.We construct an affinity matrix to get the mapping information from a workload and cluster attributes according to the attribute affinity,then obtain the optimal partitioning scheme by a cost model.The experimental results show that WSPA has good partitioning quality and lower time complexity than existing vertical partitioning method.It is an efficient partitioning method for processing the dynamic and large scale queries.

关键词： Database partitioning Streaming framework Workload-driven

作者: Hong Kang Mengyu Guo Xiaojie Yuan

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

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 68-81

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）