Abstract
Skyline query has been an important issue in the database community. Many applications nowadays request the skyline after grouping tuples, such as fantasy sports, so that the group skyline problem becomes the research focus. Most previous algorithms intended to quickly sift through the numerous combinations but fail to address the problem of constraints. In practice, nearly all groupings are specified with constrains, which demand solutions of constrained group skyline. In this paper, we propose an algorithm called CGSky to efficiently solve the problem. CGSky utilizes a pre-processing method to exclude the unnecessary tuples and generate candidate groups incrementally. A pruning mechanism is devised in the algorithm to prevent non-qualifying candidates from the skyline computation. Our experimental results show that CGSky improves an order of magnitude over previous algorithms in average. It also shows that CGSky has good scale-up capability on different data distributions.
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References
Borzsonyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proceedings of the 17th International Conference on Data Engineering, pp. 421–430 (2001)
Chen, L., Cui, B., Lu, H.: Constrained skyline query processing against distributed data sites. IEEE Trans. Knowl. Data Eng. (TKDE) 23(2), 204–217 (2011)
Chen, L., Hwang, K., Wu, J.: MapReduce skyline query processing with a new angular partitioning approach. In: 26th IEEE International Parallel and Distributed Processing Symposium Workshops & PhD Forum, pp. 2262–2270 (2012)
Chomicki, J., Godfrey, P., Gryz, J., Liang, D.: Skyline with presorting. In: Proceedings of the 19th International Conference on Data Engineering, pp. 717–719 (2003)
Chomicki, J., Ciaccia, P., Meneghetti, N.: Skyline queries, front and back. SIGMOD Rec. 42(3), 6–18 (2013)
Chung, Y.C., Su, I.F., Lee, C.: Efficient computation of combinatorial skyline queries. Inf. Syst. 38(3), 369–387 (2013)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. In: 6th Symposium on Operating System Design and Implementation (OSDI), pp. 137–150 (2004)
Dellis, E., Seeger, B.: Efficient computation of reverse skyline queries. In: Proceedings of the 33rd International Conference on Very Large Data Bases, pp. 291–302 (2007)
Endres, M., Roocks, P., Kießling, W.: Scalagon: An Efficient Skyline Algorithm for All Seasons. In: Renz, M., Shahabi, C., Zhou, X., Cheema, M.A. (eds.) DASFAA 2015. LNCS, vol. 9050, pp. 292–308. Springer, Cham (2015). doi:10.1007/978-3-319-18123-3_18
Han, X., Li, J., Yang, D., Wang, J.: Efficient skyline computation on big data. IEEE Trans. Knowl. Data Eng. (TKDE) 25(11), 2521–2535 (2013)
Im, H., Park, S.: Group skyline computation. Inf. Syst. 188, 151–169 (2012)
Kossmann, D., Ramsak, F., Rost, S.: Shooting stars in the sky: an online algorithm for skyline queries. In: Proceedings of 28th International Conference on Very Large Data Bases, pp. 275–286 (2002)
Lee, J., Hwang, S.W.: Toward efficient multidimensional subspace skyline computation. VLDB J. 23(1), 129–145 (2014)
Liu, J., Xiong, L., Pei, J., Luo, J., Zhang, H.: Finding pareto optimal groups: group-based skyline. Proc. VLDB Endowment 8(13), 2086–2097 (2015)
Mortensen, M.L., Chester, S., Assent, I., Magnani, M.: Efficient caching for constrained skyline queries. In: Proceedings of the 18th International Conference on Extending Database Technology (EDBT), pp. 337–348 (2015)
Mullesgaard, K., Pedersen, J.L., Lu, H., Zhou, Y.: Efficient skyline computation in MapReduce. In: Proceedings of the 17th International Conference on Extending Database Technology (EDBT), pp. 37–48 (2014)
Magnani, M., Assent, I.: From stars to galaxies: skyline queries on aggregate data. In: Proceedings of the 16th International Conference on Extending Database Technology (EDBT), pp. 477–488 (2013)
Papadias, D., Tao, Y., Fu, G., Seeger, B.: An optimal and progressive algorithm for skyline queries. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 467–478 (2003)
Park, Y., Min, J.K., Shim, K.: Parallel computation of skyline and reverse skyline queries using MapReduce. Proceedings of the VLDB Endowment 6(14), 2002–2013 (2013)
Tan, K.L., Eng, P.K., Ooi, B.C.: Efficient progressive skyline computation. In: Proceedings of 27th International Conference on Very Large Data Bases, pp. 301–310 (2001)
Zhang, M., Alhajj, R.: Skyline queries with constraints: integrating skyline and traditional query operators. Data Knowl. Eng. 69(1), 153–168 (2010)
Zhang, N., Li, C., Hassan, N., Rajasekaran, S., Das, G.: On skyline groups. IEEE Trans. Knowl. Data Eng. (TKDE) 26(4), 942–956 (2014)
Acknowledgements
The authors appreciate the valuable comments from the reviewers. This research was supported partly by the Ministry of Science and Technology, R.O.C. under grant MOST 105-2634-E-004-001.
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Lin, MY., Lin, YL., Hsueh, SC. (2017). Discovering Group Skylines with Constraints by Early Candidate Pruning. In: Cong, G., Peng, WC., Zhang, W., Li, C., Sun, A. (eds) Advanced Data Mining and Applications. ADMA 2017. Lecture Notes in Computer Science(), vol 10604. Springer, Cham. https://doi.org/10.1007/978-3-319-69179-4_4
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DOI: https://doi.org/10.1007/978-3-319-69179-4_4
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