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A New Double Sorting-Based Node Splitting Algorithm for R-Tree

机译:一种新的基于双重排序的R树节点拆分算法

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摘要

A storing of spatial data and processing of spatial queries are important tasks for modern databases. The execution efficiency of spatial query depends on underlying index structure. R-tree is a well-known spatial index structure. Currently there exist various versions of R-tree, and one of the most common variations between them is node splitting algorithm. The problem of node splitting in one-dimensional R-tree may seem to be too trivial to be considered separately. One-dimensional intervals can be split on the base of their sorting. Some of the node splitting algorithms for R-tree with two or more dimensions comprise one-dimensional split as their part. However, under detailed consideration, existing algorithms for one-dimensional split do not perform ideally in some complicated cases. This paper introduces a novel one-dimensional node splitting algorithm based on two sortings that can handle such complicated cases better. Also this paper introduces node splitting algorithm for R-tree with two or more dimensions that is based on the one-dimensional algorithm mentioned above. The tests show significantly better behavior of the proposed algorithms in the case of highly overlapping data.
机译:空间数据的存储和空间查询的处理是现代数据库的重要任务。空间查询的执行效率取决于基础索引结构。 R树是众所周知的空间索引结构。当前存在R树的各种版本,它们之间最常见的变体之一就是节点拆分算法。一维R树中的节点拆分问题似乎过于琐碎,无法单独考虑。一维间隔可以根据其排序进行拆分。具有二维或更多维的R-tree的某些节点拆分算法将一维拆分作为其一部分。但是,经过详细考虑,一维拆分的现有算法在某些复杂情况下不能理想地执行。本文介绍了一种基于两种排序的新颖的一维节点拆分算法,可以更好地处理此类复杂情况。本文还介绍了基于上述一维算法的二维R树的节点拆分算法。测试表明,在高度重叠的数据情况下,所提出算法的行为明显更好。

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  • 来源
    《Programming and Computer Software》 |2012年第3期|p.109-118|共10页
  • 作者

    A. Korotkov;

  • 作者单位

    National research nuclear university ME Phi, 115522, Moscow, Kashirskoe sh. 31;

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  • 原文格式 PDF
  • 正文语种 eng
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