Augmented Dynamic Skyline Query Processing Method Based on MapReduce

被引：0
作者：
Ding L.-L. [1 ]
Cui Z.-Q. [1 ]
Yin X.-K. [1 ]
Wang J.-L. [1 ]
Song B.-Y. [1 ]
机构：
[1] School of Information, Liaoning University, Shenyang, 110036, Liaoning
来源：
Song, Bao-Yan (bysong@lnu.edu.cn) | 2018年 / Chinese Institute of Electronics卷 / 46期
关键词：
Big data; Dynamic skyline query; MapReduce; User tolerance;
D O I：
10.3969/j.issn.0372-2112.2018.05.006
中图分类号：
学科分类号：
摘要：
Skyline query can compute the optimal solution which meets the multiple standards in large-scale dataset. It has been widely applied for multi-objective decisions. Dynamic skyline query, as an important variant of skyline, its result can be dynamically changed with choosing different query points, providing more flexibility when the users make some specified needs. However, dynamic skyline query can return a large number of query results and ignore the directionality of query point and data integrality, making difficult for users to choose. It is necessary to optimize the result set of dynamic skyline, improving the whole data integrality and filtering a large number of redundant data. Focusing on these problems, we propose the augmented dynamic skyline query method based on MapReduce. The algorithm partitions the original data according to dimensional information, parallel computes dynamic skyline points in multiple nodes, optimizes the result set of the traditional dynamic skyline and at the same time provides the more global optimal results for the user to choose. In addition, when the users provide the tolerance of some dimensions, we propose the augmented dynamic skyline query with user tolerance. The algorithm reduces the original dataset according to the user tolerance and reduces the comparison times of intermediate results with improving the accuracy of the result set. The experiment results show that the augmented dynamic skyline query method based on MapReduce is efficient, accurate and scalable. © 2018, Chinese Institute of Electronics. All right reserved.
引用
收藏
页码：1062 / 1070
页数：8
相关论文
共 18 条
  • [1] Zaman A., Siddique M.A., Annisa, Morimoto Y., Finding Key Persons on Social Media by Using MapReduce skyline, International Journal of Networking and Computing, 7, 1, pp. 86-104, (2017)
  • [2] Koh J.-L., Chen C.-C., Chan C.-Y., Et al., MapReduce skyline query processing with partitioning and distributed dominance tests, Information Sciences, 375, pp. 114-137, (2017)
  • [3] Wang S., Yang X., Li K., Skyline computing on MapReduce with hyperplane-projections-based Partition, Journal of Computer Research and Development, 51, 12, pp. 2702-2710, (2014)
  • [4] Wang W., Zhang J., Sun M.-T., Et al., Efficient parallel skyline evaluation using MapReduce, International Conference on Extending Database Technology, pp. 426-437, (2017)
  • [5] Park Y., Min J.-K., Shim K., Efficient processing of skyline queries using MapReduce, IEEE Transactions on Knowledge & Data Engineering, 29, 5, pp. 1031-1044, (2017)
  • [6] Li Y., Qu W., Et al., Parallel dynamic skyline query using MapReduce, International Conference on Cloud Computing and Big Data, pp. 95-100, (2015)
  • [7] Ahmed K., Nafi N.S., Et al., Enhanced distributed dynamic skyline query for wireless sensor networks, J Sensor and Actuator Networks, 5, 1, (2016)
  • [8] Islam M., Liu C., Rahayu J., Et al., Q+Tree: an efficient quad tree based data indexing for parallelizing dynamic and reverse skylines, International on Conference on Information and Knowledge Management, pp. 1291-1300, (2016)
  • [9] Benouaret K., Benslimane D., Hadjali A., Selecting skyline web services for multiple users preferences, International Conference on Web Services, pp. 635-636, (2012)
  • [10] Bouadi T., Cordier M.-O., Et al., Computing skyline incrementally in response to online preference modification, Trans Large-Scale Data-and Knowledge-Centered Systems, 10, pp. 34-59, (2013)
12