Abstract
Skyline query on multiple relations, known as skyline join query processing, attracts much attention recently. However, most of the existing algorithms perform skyline join just on two relations. In this paper, we propose an efficient algorithm Skyjog, which is applicable for skyline join on two or even more relations. Skyjog divides each relation into two or three partitions. Based on the proposed group division approach, tuples generated by several join combinations of these partitions definitely are skyline points. Skyjog only has to examine tuples of other join combinations. Thus, Skyjog achieves performance efficiency by avoiding much skyline computation. Experiments demonstrate that Skyjog has an outstanding performance on all datasets, and outperforms the state-of-the-art skyline join algorithms on both two relations and more than two relations.
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- 1.
Small values are preferable in this paper.
- 2.
Join referred in this paper indicates equi-join operation.
- 3.
LSS, LSN and LNN are denoted as LS(S), LS(N) and LN(N) in original paper.
- 4.
The symbol ‘\(\cdot \)’ is the join operator for two tuples.
- 5.
Join rate indicates the proportion of the dataset that will be involved in join result.
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Acknowledgments
This work is supported by the National KeJiZhiCheng Project (2012BAH46B03), the National HeGaoJi Key Project (2013ZX01039-002-001-001), the National Natural Science Foundation of China (61502478), and “Strategic Priority Research Program” of the Chinese Academy of Sciences (XDA06030200).
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Zhang, J., Lin, Z., Li, B., Wang, W., Meng, D. (2016). Skyline Join Query Processing over Multiple Relations. In: Gao, H., Kim, J., Sakurai, Y. (eds) Database Systems for Advanced Applications. DASFAA 2016. Lecture Notes in Computer Science(), vol 9645. Springer, Cham. https://doi.org/10.1007/978-3-319-32055-7_29
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DOI: https://doi.org/10.1007/978-3-319-32055-7_29
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