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Available viahttp://dbpubs.stanford.edu/pub/2003-72
Submitted on 9th of December 2003
Author Arasu, Arvind; Manku, Gurmeet
Title Approximate Counts and Quantiles over Sliding Windows
Date of publication 9th of December 2003
Published in Technical Report
Citation Arasu, Arvind; Manku, Gurmeet. Approximate Counts and Quantiles over Sliding Windows, Technical Report
Number of pages 13
Language English
Project STREAM
Type Technical Report
Subject group Miscellaneous
Abstract We consider the problem of maintaining approximate counts and quantiles over fixed- and variable-size sliding windows in limited space. For quantiles, we present deterministic algorithms whose space requirements are O(1/e log(1/e)log N) and O(1/e log(1/e) log(eN) log N) in the worst-case for fixed- and variable-size windows, respectively, where N denotes the current number of elements in the window and e, the relative error. Our space bounds improve upon the previous best bounds of O(1/e^2 polylog (1/e,N)). For counts, we present both deterministic and randomized algorithms. The deterministic algorithms require O(1/e log^2 (1/e)) and O(1/e log^2 (1/e) log eN) for worst-case space for fixed- and variable-size windows, respectively, while the randomized ones require O(1/e log (1/(e d))) and O(1/e log(1/(ed)) log eN) worst-case space, where d denotes the probability of failure. We believe no previous work on space-efficient approximate counts for sliding windows exists.
Keywords Data Streams, Sliding Windows, Quantiles, Counts, Approximation, Limited Space
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