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Space Efficient Quantile Summary for Constrained Sliding Windows on a Data Stream

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Advances in Web-Age Information Management (WAIM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3129))

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Abstract

In many online applications, we need to maintain quantile statistics for a sliding window on a data stream. The sliding windows in natural form are defined as the most recent N data items. In this paper, we study the problem of estimating quantiles over other types of sliding windows. We present a uniform framework to process quantile queries for time constrained and filter based sliding windows. Our algorithm makes one pass on the data stream and maintains an ε-approximate summary. It uses \(O(\frac{1}{\epsilon^2}\log^2{\epsilon N})\) space where N is the number of data items in the window. We extend this framework to further process generalized constrained sliding window queries and proved that our technique is applicable for flexible window settings. Our performance study indicates that the space required in practice is much less than the given theoretical bound and the algorithm supports high speed data streams.

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© 2004 Springer-Verlag Berlin Heidelberg

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Xu, J., Lin, X., Zhou, X. (2004). Space Efficient Quantile Summary for Constrained Sliding Windows on a Data Stream. In: Li, Q., Wang, G., Feng, L. (eds) Advances in Web-Age Information Management. WAIM 2004. Lecture Notes in Computer Science, vol 3129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27772-9_5

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  • DOI: https://doi.org/10.1007/978-3-540-27772-9_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22418-1

  • Online ISBN: 978-3-540-27772-9

  • eBook Packages: Springer Book Archive

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