nir树:一种不相交的r树

K. Langendoen, Brad Glasbergen, Khuzaima S. Daudjee
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引用次数: 1

摘要

基于R-Tree的多维数据索引被数据库广泛用于各种应用程序。这样的索引树支持点和范围查询,但在数百万个点的数据集上构建成本很高。我们提出了非相交r树(NIR-Tree),这是一种新的插入效率,内存中的多维索引,它使用边界多边形提供有效的点和范围查询性能,同时索引数据的速度至少提高了一个数量级。与现有的r族索引相比,NIR-Tree利用非相交的边界多边形来减少查询期间访问的节点数量。我们的实验表明,插入到NIR-Tree中的速度比普遍存在的R*-Tree快27倍,点查询完成速度快2倍,范围查询执行速度也一样快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NIR-Tree: A Non-Intersecting R-Tree
Indexes for multidimensional data based on the R-Tree are popularly used by databases for a wide range of applications. Such index trees support point and range queries but are costly to construct over datasets of millions of points. We present the Non-Intersecting R-Tree (NIR-Tree), a novel insert-efficient, in-memory, multidimensional index that uses bounding polygons to provide efficient point and range query performance while indexing data at least an order of magnitude faster. The NIR-Tree leverages non-intersecting bounding polygons to reduce the number of nodes accessed during queries, compared to existing R-family indexes. Our experiments demonstrate that inserting into a NIR-Tree is 27 × faster than the ubiquitous R*-Tree, with point queries completing 2 × faster and range queries executing just as quickly.
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