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Management: Processing High-speed Data Streams, edited by Minos Garofolakis,Johannes Gehrhz and Rajeev Rastogi, published by Springer- Verlag lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark 150 DATA STREAMS: MODELS AND ALGORITHMS assumption is not true, particularly those that ascribe more importance to recent data items One way to discount old data items and only consider recent... for classifying data streams In Proceedings o the 2005 SIAM f International Data Mining Conference, April 2005 lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark Load Shedding in Data Stream Systems 147 [5] A Das, J Gehrke, and M Riedwald Approximate join processing over f data streams In Proceedings o the 2003 ACM SIGMOD International Con$ on Management o Data, pages 40-5... BASICCOUNTING problem and the associated space lower bound in sections 1 and 2 respectively, we present a modified version of the algorithm in Section 3 that solves the following generalization of the BASICCOUNTING problem: lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark 152 DATA STREAMS: MODELS AND ALGORITHMS PROBLEM0.2 ( S U M ) Given a stream of data elements that are... Principles ofDatabase Systems, pages 286-296, June 2004 [3] B Babcock, M Datar, and R Motwani Sampling from a moving window over streaming data In Proc o the 2002 Annual ACM-SIAM Symp on f Discrete Algorithms, pages 633-634,2002 [4] B Babcock, M Datar, R Motwani, and L O'Callaghan Maintaining variance and k-medians over data stream windows In Proc o the 2003 f ACMSymp on Principles ofDatabase Systems,... www.verypdf.com to remove this watermark Chapter 8 THE SLIDING-WINDOW COMPUTATION MODEL AND RESULTS* Mayur Datar Google, Inc datar@cs.stanford.edu Rajeev Motwani Department of Computer Science Stanford University Abstract The sliding-window model of computation is motivated by the assumption that, in certain data- stream processing applications, recent data is more useful and pertinent than older data. .. (positive or negative) that appear as stream of data elements is equal to O(N) lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark The Sliding- Window ComputationModel and Results 4 163 References and Related Work The EH technique, that we demonstrate through solutions to the BASICCOUNTING SUM and problem, is by Datar, Gionis, Indyk and Motwani [8] The space lower bounds, presented... a single data point, which in this case is a point from some metric space, is e assumed to be O(1) words lease purchase PDF Split-Merge on www.verypdf.com to remove this watermark 164 DATA STREAMS: MODELS AND ALGORITHMS to adapt the EH technique to such a time-based sliding-window model See [8,7] for details One may argue that the sliding-window model is not the right model to discount old data, in... aggregation f queries over data streams In Proceedings o the 2004 International Conference on Data Engineering, pages 350-361, March 2004 [3] D Carney, U Cetintemel, M Cherniack, C Convey, S Lee, G Seidman, M Stonebraker,N Tatbul, and S Zdonik Monitoring streams- a new class of data management applications In Proc 28th Intl Con$ on Very Large Data Bases, August 2002 [4] Y Chi, P S Yu, H Wang, and R R Muntz Loadstar:... 234-243, June 2003 [5] E Cohen and M Strauss Maintaining time-decaying stream aggregates In Proc o the 2003 ACM Symp on Principles ofDatabase Systems, pages f 223-233, June 2003 [6] A Das, J Gehrke, and M Riedwald Approximatejoin processing over data streams In Proc o the 2003 ACM SIGMOD Intl Con$ on Management f o Data, pages 40-51,2003 f [7] M Datar Algorithms for Data Stream Systems PhD thesis,... December 2003 [8] M Datar, A Gionis, P Indyk, and R Motwani Maintaining stream statistics over sliding windows SIAM Journal on Computing, 3 l(6): 1794-1 813, 2002 [9] M Datar and S Muthukrishnan Estimating rarity and similarity over f data stream windows In Proc o the 2002 Annual European Symp on Algorithms, pages 323-334, September 2002 lease purchase PDF Split-Merge on www.verypdf.com to remove this . Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark. Please purchase PDF Split-Merge on www.verypdf.com to remove this. watermark. Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark. Please purchase PDF Split-Merge on www.verypdf.com to remove this