Browse > Article

Linear Resource Sharing Method for Query Optimization of Sliding Window Aggregates in Multiple Continuous Queries  

Baek, Seong-Ha (인하대학교 컴퓨터정보공학과)
You, Byeong-Seob (인하대학교 컴퓨터정보공학과)
Cho, Sook-Kyoung (인하대학교 컴퓨터정보공학과)
Bae, Hae-Young (인하대학교 컴퓨터정보공학과)
Publication Information
Journal of KIISE:Databases / v.33, no.6, 2006 , pp. 563-577 More about this Journal
Abstract
A stream processor uses resource sharing method for efficient of limited resource in multiple continuous queries. The previous methods process aggregate queries to consist the level structure. So insert operation needs to reconstruct cost of the level structure. Also a search operation needs to search cost of aggregation information in each size of sliding windows. Therefore this paper uses linear structure for optimization of sliding window aggregations. The method comprises of making decision, generation and deletion of panes in sequence. The decision phase determines optimum pane size for holding accurate aggregate information. The generation phase stores aggregate information of data per pane from stream buffer. At the deletion phase, panes are deleted that are no longer used. The proposed method uses resources less than the method where level structures were used as data structures as it uses linear data format. The input cost of aggregate information is saved by calculating only pane size of data though numerous stream data is arrived, and the search cost of aggregate information is also saved by linear searching though those sliding window size is different each other. In experiment, the proposed method has low usage of memory and the speed of query processing is increased.
Keywords
resource sharing; stream; sliding window; aggregate; query optimization;
Citations & Related Records
연도 인용수 순위
  • Reference
1 P.B. Gibbons and S. Tirthapura, 'Distributed streams algorithms for sliding windows,' In Proc. of the 14th Annual ACM Symp. On Parallel Algs. And Architectures, pp. 63-72, Aug. 2002   DOI
2 R. Zhang, Nich. Koudas, 'Multiple Aggregations Over Data Streams,' In Proc, of the 2005 ACM SIGMOD IntI. Conf. on Management of Data, pp. 299-310, June 2005   DOI
3 Arvind Arasu, Jennifer Widom, 'Resource Sharing in Continuous Sliding-Window Aggregates,' In Proc. of the 30th VLDB 2004
4 J. Li, D. Maier, 'Semantics and Evaluation Techniques for Window Aggregates in Data Streams,' In Proc of ACM SIGMOD International Conference on the management of Data, 2005   DOI
5 Hammand, M., Franklin, M., Aref, W., and Elmagarmid, 'A. Scheduling for shared window joins over data streams,' In Proc of the 29th VLDB Sep, 2003
6 S. Chandrasekharan and M. J. Franklin., 'Streaming Queries over streaming data,' In Proc of the 28th Intl. Conf. On VLDB, pp. 203-214, Aug. 2002
7 Abadi, D. J, Carney, D., Centintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., Zdonik, S., 'Aurora: A New Model and Architecture for Data Stream Management,' VLDB Journal, 2003   DOI
8 N. Koudas and D. Srivastava, 'Data stream query processing: A tutorial,' In VLDB, 2003
9 M. Datar, A Gionis, P. Indyk, and R. Motwani. 'Maintaining stream statistics over sliding windows,' In Proc. of the 13th Annual ACM SIAM Symp. On Discrete Algorithms, pp. 635-644, Jan. 2002
10 J. Gehrke, F. Korn, and D. Srivastava. 'On computing correlated aggregates over continual data streams,' In Proc. of the 2001 ACM SIGMOD IntI. Conf. on Management of Data, pp. 13-24, May 2001   DOI
11 B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom., 'Models and Issues in Data Stream Systems,' Invited paper in Proc of PODS, 2002   DOI
12 R. Motwani, J. Widom, A. Arasu, B. Babcock, S. Babu, M. Datar, G. Manku, C. Olston, J. Rosenstein, and R. Varma., 'Query Processing, Resource Management, and Approximation in a Data Stream Management System,' In Proc of CIDR, 2003
13 R. E. Gruber. B. Krishanmurthy, and E. Panagos 'READY: A high performance event notification system,' In proc. of the 16th IntI. Conf. on Data Engineering, pp. 668-669, Mar. 2000   DOI
14 Hammand, M., Aref, W., Franklin, M., Mokbel, M., and Elmagarmid, A.K. 'Efficient Execution of Sliding Window Queries over Data Streams,' Purdue University Department of Computer Sciences Technical Report Number CSD TR 03-035, Dec 2003
15 A. Dobra, M. N. Garofalakis, J. Gehrke, and R. Rastogi, 'Sketch-based multi-query processing over data streams,' In EDBT, 2004
16 Tucker, P., Maier, D., Sherad, T. and Fegaras, L. 'Exploiting Punctuation Semantics in Continuous Data Streams,' Transactions on Knowledge and Data Engineering, 15,3, May 2003   DOI   ScienceOn
17 J. Li, D. Maier, 'No Pane, No Gain : Efficient Evaluation of Sliding-Window Aggregates over Data Streams,' SIGMOD Record, Vol. 34, No. 1, March 2005   DOI   ScienceOn
18 A. Arasu, S. Babu, and J. Widom. The CQL Continuous Query Language : Semantic Foundations and Query Execution. Stanford University Technical Report, 2003