Abstract
The data stream systems provide sliding windows to preserve the arrival of recent streaming data in order to support continuous queries in real-time. In this paper, we consider the problem of adjusting the buffer size of sliding windows dynamically when the rate of streaming data changes or when queries start or end. Based on the status of available memory resource and the requirement of queries for memory, we propose the corresponding algorithms of adjustment with greedy method and dynamic programming method, which minimize the total error of queries or achieve low memory overhead. The analytical and experimental results show that our algorithms can be applied to the data stream systems efficiently.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Guha, S., Koudas, N.: Approximating a Data Stream for Querying and Estimation: Algorithms and Performance Evaluation. In: ICDE (2002)
Golab, L., Ozsu, M.T.: Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams. In: VLDB (2003)
Viglas, S.D., Naughton, J.F., Burger, J.: Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources. In: VLDB (2003)
Hammad, M.A., Franklin, M.J., Aref, W.G., Elmagarmid, A.K.: Scheduling for shared window joins over data streams. In: VLDB (2003)
Babcock, B., Babu, S., Datar, M., Motwani, R.: Chain: Operator Scheduling for Memory Minimization in Data Stream Systems. In: SIGMOD (2003)
Haas, P.J.: Large-Sample and Deterministic Confidence Intervals for Online Aggregation. In: 9th International Conference on Scientific and Statistical Database Management, SSDBM (1997)
Hellerstein, J.M., Hass, P.J., Wang, H.J.: Online Aggregation. In: SIGMOD (1997)
Arasu, A., Babcock, B., Babu, S.: Characterizing Memory Requirements for Queries over Continuous Data Streams. In: PODS (2002)
Kang, J., Naughton, J.F., Viglas, S.D.: Evaluating Window Joins over Unbounded Streams. In: ICDE (2003)
Araru, A., Babu, S., Widom, J.: An Abstract Semantics and Concrete Language for Continuous Queries over Streams and Relations. Technical Report, Stanford University Database Group (November 2002). Available at http://dbpubs.stanford.edu/pub/2002-57
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, D., Li, J., Zhang, Z., Wang, W., Guo, L. (2004). Dynamic Adjustment of Sliding Windows over Data Streams. 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_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-27772-9_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22418-1
Online ISBN: 978-3-540-27772-9
eBook Packages: Springer Book Archive