Ziyu Lin, Dongzhan Zhang, Chen Lin, Yongxuan Lai, Quan Zou. Performance Optimization of Analysis Rules in Real-time Active Data Warehouses. In Proceedings of APWeb2012, Kunming, China, LNCS 7235, pp. 669–676, 2012.(CCF C 类会议)
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Performance Optimization of Analysis Rules in Real-time Active Data Warehouses
Ziyu Lin1, Dongzhan Zhang1, Chen Lin1, Yongxuan Lai2, and Quan Zou1
1 School of Information Science and Technology, Xiamen University, Xiamen, China
{ziyulin,zdz,chenlin,zouquan}@xmu.edu.cn
2 School of Software, Xiamen University, Xiamen, China
laiyx@xmu.edu.cn
Abstract. Analysis rule is an important component of a real-time active data warehouse. Performance optimization of analysis rules may greatly improve the system response time when a new event occurs. In this paper, we carry out the optimization work through the following three ways: (1)initiating non-real-time analysis rules as less as possible during rush hour of real-time analysis rules; (2) executing non-real-time analysis rules using the same cube at the same time interval; and (3) preparing frequent cubes for the use of real-time analysis rules ahead of time. We design the LADE system to get all the reference information required by optimization work. A new algorithm, called ARPO, is proposed to carry out the optimization work. Empirical studies show that our methods can effectively improve the performance of analysis rules.
Keywords: analysis rules, real-time active data warehouses.
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