Counting distinct objects over sliding windows

Authors:
Wenjie Zhang;Ying Zhang;Muhammad Aamir Cheema;Xuemin Lin
Affiliations:
The University of New South Wales and NICTA;The University of New South Wales;The University of New South Wales;The University of New South Wales and NICTA
Venue:
ADC '10 Proceedings of the Twenty-First Australasian Conference on Database Technologies - Volume 104
Year:
2010

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Abstract

Aggregation against distinct objects has been involved in many real applications with the presence of duplicates, including real-time monitoring moving objects. In this paper, we investigate the problem of counting distinct objects over sliding windows with arbitrary lengths. We present novel, time and space efficient, one scan algorithms to continuously maintain a sketch so that the counting can be approximately conducted with a relative error guarantee ε in the presence of object duplicates. Efficient query algorithms have also been developed by effectively utilizing the skyband property. Moreover, the proposed techniques may be immediately applied to the range counting aggregation and heavy hitter problem against distinct elements. A comprehensive performance study demonstrates that our algorithms can support real-time computation against high speed data streams.