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Processing Constrained K Closest Pairs Query in Spatial Databases

机译:在空间数据库中处理约束K最近对查询

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摘要

In this paper, constrained K closest pairs query is introduced, which retrieves the K closest pairs satisfying the given spatial constraint from two datasets. For data sets indexed by R-trees in spatial databases, three algorithms are presented for answering this kind of query. Among of them, two-phase Range+ Join and Join+Range algorithms adopt the strategy that changes the execution order of range and closest pairs queries, and constrained heap-based algorithm utilizes extended distance functions to prune search space and minimize the pruning distance. Experimental results show that constrained heap-base algorithm has better applicability and performance than two-phase algorithms.
机译:本文引入约束的K对最接近查询,从两个数据集中检索满足给定空间约束的K对最接近对。对于空间数据库中由R树索引的数据集,提出了三种算法来回答这种查询。其中两阶段的Range + Join和Join + Range算法采用改变范围和最接近对查询的执行顺序的策略,基于约束的基于堆的算法利用扩展距离功能来修剪搜索空间并最小化修剪距离。实验结果表明,约束堆基算法比两阶段算法具有更好的适用性和性能。

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