ABSTRACT
In this paper, we study the evaluation of skyline queries with partially-ordered attributes. Because such attributes lack a total ordering, traditional index-based evaluation algorithms (e.g., NN and BBS) that are designed for totally-ordered attributes can no longer prune the space as effectively. Our solution is to transform each partially-ordered attribute into a two-integer domain that allows us to exploit index-based algorithms to compute skyline queries on the transformed space. Based on this framework, we propose three novel algorithms: BBS+ is a straightforward adaptation of BBS using the framework, and SDC (Stratification by Dominance Classification) and SDC+ are optimized to handle false positives and support progressive evaluation. Both SDC and SDC+ exploit a dominance relationship to organize the data into strata. While SDC generates its strata at run time, SDC+ partitions the data into strata offline. We also design two dominance classification strategies (MinPC and MaxPC) to further optimize the performance of SDC and SDC+. We implemented the proposed schemes and evaluated their efficiency. Our results show that our proposed techniques outperform existing approaches by a wide margin, with SDC+-MinPC giving the best performance in terms of both response time as well as progressiveness. To the best of our knowledge, this is the first paper to address the problem of skyline query evaluation involving partially-ordered attribute domains.
- R. Agrawal, A. Borgida, and H. V. Jagadish. Efficient management of transitive relationships in large data and knowledge bases. In SIGMOD'89 Google ScholarDigital Library
- R. Agrawal and E. Wimmers. A framework for expressing and combining preferences. In SIGMOD'00. Google ScholarDigital Library
- W. Balke, U. Güntzer, and X. Zheng. Efficient distributed skylining for web information systems. In EDBT'04.Google Scholar
- S. Börzsönyi, D. Kossmann, and K. Stocker. The skyline operator. In ICDE'01.Google Scholar
- M. Carey and D. Kossmann. On saying "enough already!" in SQL. In SIGMOD'97 Google ScholarDigital Library
- J. Chomicki. Querying with intrinsic preferences. In EDBT'02. Google ScholarDigital Library
- J. Chomicki. Preference formulas in relational queries. ACM TODS, 24(4), 2003. Google ScholarDigital Library
- V. Hristidis, N. Koudas, and Y. Papakonstantinou. PREFER: a system for the efficient execution of multi-parametric ranked queries. In SIGMOD'01. Google ScholarDigital Library
- W. Kießling. Foundations of preferences in database systems. In VLDB'02. Google ScholarDigital Library
- W. Kießling and G. Köstler. Preference SQL - design, implementation, experiences. In VLDB'02. Google ScholarDigital Library
- D. Kossmann, F. Ramsak, and S. Rost. Shooting stars in the sky: an online algorithm for skyline queries. In VLDB'02. Google ScholarDigital Library
- H. Kung, F. Luccio, and F. Preparata. On finding the maxima of a set of vectors. JACM, 22(4), 1975. Google ScholarDigital Library
- J. Matousek. Computing dominances in En. Information Processing Letters, 38(5):277--278, 1991. Google ScholarDigital Library
- D. Papadias, Y. Tao, G. Fu, and B. Seeger. An optimal and progressive algorithm for skyline queries. In SIGMOD'03. Google ScholarDigital Library
- C. H. Papadimitriou and M. Yannakakis. Multiobjective query optimization. In PODS'01. Google ScholarDigital Library
- F. P. Preparata and M. I. Shamos. Computational Geometry: An Introduction. Springer-Verlag, 1985. Google ScholarDigital Library
- I. Stojmenovic and M. Miyakawa. An optimal parallel algorithm for solving the maximal elements problem in the plane. Parallel Computing, 7(2), June 1988.Google Scholar
- K. L. Tan, P. K. Eng, and B. C. Ooi. Efficient progressive skyline computation. In VLDB'01. Google ScholarDigital Library
- R. Torlone and P. Ciaccia. Which are my preferred items? In Workshop on Recommendation and Personalization in E-Commerce, May 2002.Google Scholar
- Y. Zibin and J. Y. Gil. Efficient subtyping tests with PQ-encoding. In OOPSLA'01. Google ScholarDigital Library
- Stratified computation of skylines with partially-ordered domains
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