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RSkycube: Efficient Skycube Computation by Reusing Principle

机译:rskycube:通过重用原则高效的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:在过去几年中,天际线查询已经引起了数据库社区的广泛关注。为了满足用户的不同偏好,建议在所有可能的非空维度子集上计算天际线或长方体的天空计算。计算Skycube的关键问题是如何在多个相关的长方体中共享计算,该数据归类为共享严格的空间优势和共享空间不可统奏。然而,最先进的算法仅利用分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,可以在多个相关长方体之间分享计算。我们首先提出了一系列名为相同的分区(IP)的规则,用于构建一个新颖的结构vskytree。此外,我们提出了重用原则,它利用严格的空间优势和共享空间,通过重用父母长方体来计算儿童长方体。然后,以自上而下的方式,我们根据重用原理设计一个高效的Skycube计算算法RSKYCube。我们的实验结果表明,我们的算法RskyCube在合成和实际数据集中显着优于最先进的Skycube计算算法。

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