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Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment

机译:多磁盘环境中天际线查询的并行渐进计算

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摘要

Given a set of d-dimensional points, skyline query returns the points that are not dominated by any other point on all dimensions. In this paper, we study an interesting scenario of skyline retrieval, where multi-dimensional points are distributed among multiple disks. Efficient algorithms for parallelizing progressive skyline computation are developed, using the parallel R-trees. The core of our scheme is to visit more entries from some disks simultaneously and enable effective pruning strategies with dominance checking to prune away the non-qualifying entries. Extensive experiments with synthetic data confirm that our proposed algorithms are both efficient and scalable.
机译:给定一组d维点,天际线查询将返回在所有维上均不受任何其他点支配的点。在本文中,我们研究了一种有趣的天际线检索方案,其中多维点分布在多个磁盘中。使用并行R树,开发了用于并行化渐进式天际线计算的高效算法。我们方案的核心是从某些磁盘上同时访问更多条目,并通过有效检查启用有效的修剪策略,以删除不合格的条目。使用合成数据进行的大量实验证实,我们提出的算法既高效又可扩展。

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