We present a novel load shedding technique over sliding window joins. We first construct a dual window architectural model including join-windows and aux-windows. With the statistics built on aux-windows, an effective load shedding strategy is developed to produce maximum subset join outputs. For the streams with high arrival rates, we propose an approach incorporating front-shedding and rearshedding, and then address the problem of how to cooperate these two shedding processes through a series of calculations. Based on extensive experimentation with synthetic data and real life data, we show that our load shedding strategy delivers superb join output performance, and dominates the existing strategies.
Lecture Notes in Computer Science: proceedings of the 7th International Conference on Web-Age Information Management (WAIM 2006), Hong Kong, China, 17-19 June 2006 / Jeffrey Xu Yu, Masaru Kitsuregawa and Hong Va Leong (eds.),
Vol. 4016, pp. 472-483
The authors acknowledge support from the National Natural Science Foundation of China (Grant No. 60273079 and 60573089) and the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP).