Heuristic algorithm for periodic patterns discovery in a database workload reconstruction
Marcin Zimniak, Marta Burzańska, Piotr Wiśniewski, Bogdan Franczyk
Citation: Communication Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 32, pages 139–142 (2022)
Abstract. Information about the existence of periodic patterns in a database workload can play a big part in the process of database tuning. However, full analysis of audit trails can be cumbersome and time-consuming. This paper discusses a heuristic algorithm that focuses on workload reconstruction based on pattern discovery in a simplified workload notation. This notation is based on multisets representing database actions (such as user queries) requiring access to specific persistent objects, but without the access cost analysis. Each action in this notation is a multiset of accessed objects, which can be tables, system files, views, etc. The theoretical model for such an approach has been discussed in detail in the authors' previous work.This work is mostly proof-of-a-concept for the theoretical approach. Additionally, in order to test the performance of the proposed algorithm, a test-data generator has been constructed. Both the previous and the current papers are parts of a research project dealing with the application of periodic pattern theory to the field of database optimization and tuning.
- M. Zimniak, M. Burzanska, and B. Franczyk, “On some heuristic method for optimal workload reconstruction,” in Proceedings of the 27th International Workshop on Concurrency, Specification and Programming, Berlin, Germany, September 24-26, 2018, ser. CEUR Workshop Proceedings, B. Schlingloff and S. Akili, Eds., vol. 2240. CEUR-WS.org, 2018. [Online]. Available: http://ceur-ws.org/Vol-2240/paper5.pdf
- M. Zimniak, J. R. Getta, and W. Benn, “Predicting database workloads through mining periodic patterns in database audit trails,” Vietnam Journal of Computer Science, vol. 2, no. 4, pp. 201–211, 2015.
- M. Zimniak and J. R. Getta, “On systematic approach to discovering periodic patterns in event logs,” in Computational Collective Intelligence - 8th International Conference, ICCCI 2016, Halkidiki, Greece, September 28-30, 2016, Proceedings, Part I, ser. Lecture Notes in Computer Science, N. T. Nguyen, Y. Manolopoulos, L. S. Iliadis, and B. Trawinski, Eds., vol. 9875. Springer, 2016, pp. 249–259. [Online]. Available: https://doi.org/10.1007/978-3-319-45243-2_23
- M. Zimniak, J. R. Getta, and W. Benn, “Discovering periodic patterns in system logs,” in Proceedings of the LWA 2014 Workshops: KDML, IR, FGWM, Aachen, 2014, pp. 156–161.
- M. Zimniak, J. R. Getta, and W. Benn, “Deriving composite periodic patterns from database audit trails,” in Asian Conference on Intelligent Information and Database Systems. Springer, 2014, pp. 310–321.
- K. Pommerening, “Cryptology part i: Classic ciphers (mathematical version),” 2014.
- E. Lehtonen, “Reconstructing multisets over commutative groupoids and affine functions over nonassociative semirings,” International Journal of Algebra and Computation, vol. 24, no. 01, pp. 11–31, 2014. [Online]. Available: https://doi.org/10.1142/S0218196714500027
- E. Lehtonen, “Totally symmetric functions are reconstructible from identification minors,” The Electronic Journal of Combinatorics, vol. 21, no. 2, Apr. 2014. [Online]. Available: https://doi.org/10.37236/2863
- P. Wojtaszczyk, A Mathematical Introduction to Wavelets. Cambridge University Press, Feb. 1997. [Online]. Available: https://doi.org/10.1017/cbo9780511623790
- C. K. Chui, “Wavelets: A mathematical tool for signal analysis,” 1997.
- A. B. Matos, “Periodic sets of integers,” Theoretical Computer Science, vol. 127, no. 2, pp. 287–312, 1994.
- P. Serafini and W. Ukovich, “A mathematical model for periodic scheduling problems,” SIAM Journal on Discrete Mathematics, vol. 2, no. 4, pp. 550–581, 1989.