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An Efficient Join Algorithm for Data Streams with Overlapping Window  

Kim, Hyeon-Gyu (KAIST 전산학과)
Kang, Woo-Lam (KAIST 전산학과)
Kim, Myoung-Ho (KAIST 전산학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.15, no.5, 2009 , pp. 365-369 More about this Journal
Abstract
Overlapping windows are generally used for queries to process continuous data streams. Nevertheless, existing approaches discussed join algorithms only for basic types of windows such as tumbling windows and tuple-driven windows. In this paper, we propose an efficient join algorithm for overlapping windows, which are considered as a more general type of windows. The proposed algorithm is based on an incremental window join. It focuses on producing join results continuously when the memory overflow frequently occurs. It consists of (1) a method to use both of the incremental and full joins selectively, (2) a victim selection algorithm to minimize latency of join processing and (3) an idle time professing algorithm. We show through our experiments that the selective use of incremental and full joins provides better performance than using one of them only.
Keywords
Data streams; Hybrid join; Overlapping windows;
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