Abstract
Aiming at the problem of spatio-textual skyline query processing in cloud computing systems, we propose a Spark-based spatio-textual skyline query processing algorithm. In which, the spatial objects irrelevant to query points are filtered out according to the text relevance, and an integration function is used to compute the spatio-textual distances between spatial objects and query points. Then the data space consisting of dynamic spatio-textual distances is divided into same-sized cells by using a grid partitioning method, and the cell dominant relation is used to filter out the cells and related spatial objects, thus reducing the computation cost. A local spatial skyline algorithm is used to compute local skyline results for each cell in parallel, in which, spatial objects having strong dominant capacity are selected as the initial dominating set to further reduce the computing cost and speed up the execution of the algorithm. Experimental results show that the proposed algorithm has good performance and scalability.
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References
Borzsony, S., Kossmann, D., Stocker, K.: The skyline operator data engineering. In: International Conference on Data Engineering, pp. 421–430 (2001)
Sharifzadeh, M., Shahabi, C.: The spatial skyline queries. In: Proceedings of the International Conference on Very Large Databases, pp. 751–762 (2006)
Shi, J., Wu, D., Mamoulis, N.: Textually relevant spatial skylines. IEEE Trans. Knowl. Data Eng. 28, 224–237 (2015)
Kodama, K., Iijima, Y., Guo, X., et al.: Skyline queries based on user locations and preferences for making location-based recommendations. In: International Workshop on LBSN 2009
Regalado, A., Goncalves, M., Abad-Mota, S.: Evaluating skyline queries on spatial web objects. DEXA 2012, pp. 416–423 (2012)
Li, J., Wang, H., Li, J., et al.: skyline for geo-textual data. Geoinformatica 20(3), 453–469 (2016)
Zhang, J., Jiang, X., Ku, W.S., et al.: Efficient parallel skyline evaluation using MapReduce. IEEE Trans. Parallel Distrib. Syst. 27(7), 1996–2009 (2016)
Sohail, A., Cheema, M.A., Taniar, D.: Social-aware spatial top-k and skyline queries. Comput. J. 61(11), 1620–1638 (2018)
Acknowledgements
This research was supported by the National Key R&D Program of China (NO. 2016YFC1401900 and 2018YFB1004402) and National Natural Science Foundation of China (No. 61872072 and 61073063).
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Qiao, B., Zhang, J., Qiao, X., Hu, B., Zheng, Y., Wu, G. (2020). An Efficient Spatio-Textual Skyline Query Processing Algorithm Based on Spark. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_70
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DOI: https://doi.org/10.1007/978-3-030-32591-6_70
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