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RSkycube: Efficient Skycube Computation by Reusing Principle

机译:RSkycube:通过重用原理进行高效的Skycube计算

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Over the past years, the skyline query has already attracted wide attention in database community. In order to meet different preferences for users, the skycube computation is proposed to compute skylines, or cuboids, on all possible non-empty dimension subsets. The key issue of computing skycube is how to share computation among multiple related cuboids, which classified into sharing strict space dominance and sharing space incomparability. However, state-of-the-art algorithm only leverages sharing strict space dominance to compute skycube. This paper aims to design a more efficient skycube algorithm that shares computation among multiple related cuboids. We first propose a set of rules named identical partitioning (IP) for constructing a novel structure VSkyTree. Moreover, we present the reusing principle, which utilizes both sharing strict space dominance and sharing space incomparability by reusing VSkyTree on parent cuboids to compute child cuboids. Then, in top-down fashion, we design an efficient skycube computation algorithm RSkycube based on the reusing principle. Our experimental results indicate that our algorithm RSkycube significantly outperforms state-of-the-art skycube computation algorithm on both synthetic and real datasets.
机译:在过去的几年中,天际线查询已引起数据库社区的广泛关注。为了满足用户的不同偏好,建议使用skycube计算来在所有可能的非空维子集上计算天际线或长方体。计算skycube的关键问题是如何在多个相关的长方体之间共享计算,这些长方体分为共享严格的空间优势和共享空间不可比性。但是,最新的算法仅利用共享严格的空间优势来计算skycube。本文旨在设计一种更高效的Skycube算法,该算法在多个相关的长方体之间共享计算。我们首先提出一组名为相同分区(IP)的规则,用于构造新颖的结构VSkyTree。此外,我们提出了重用原理,它通过在父长方体上重用VSkyTree来计算子长方体,从而利用共享严格的空间优势和共享空间不可比性。然后,以自上而下的方式,基于重用原理,设计了一种高效的skycube计算算法RSkycube。我们的实验结果表明,我们的算法RSkycube在合成数据集和实际数据集上均明显优于最新的skycube计算算法。

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