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Optimizing storage utilization in R-tree dynamic index structure for spatial databases

机译:优化空间数据库R树动态索引结构的存储利用率

摘要

Spatial databases have been increasingly and widely used in recent years. The R-tree proposed by Guttman is probably the most popular dynamic index structure for efficiently retrieving objects from a spatial database according to their spatial locations. However, experiments show that only about 70% storage utilization can be achieved in Guttman's R-tree and its variants. In this paper, we propose a compact R-tree structure which can achieve almost 100% storage utilization. Our experiments also show that the search performance of compact R-trees is very competitive as compared to Guttman's R-trees. In addition, the overhead cost of building a compact R-tree is much lower than that of a Guttman's R-tree because the frequency of node splitting is reduced significantly. (C) 2001 Elsevier Science Inc. All rights reserved.
机译:近年来,空间数据库已越来越广泛地被广泛使用。 Guttman提出的R树可能是最流行的动态索引结构,用于根据对象的空间位置有效地从空间数据库中检索对象。但是,实验表明,在Guttman的R树及其变体中只能实现约70%的存储利用率。在本文中,我们提出了一种紧凑的R树结构,可以实现几乎100%的存储利用率。我们的实验还表明,与Guttman的R树相比,紧凑型R树的搜索性能非常有竞争力。另外,构建紧凑的R树的开销成本比Guttman的R树的开销成本低得多,因为节点拆分的频率大大降低了。 (C)2001 Elsevier Science Inc.保留所有权利。

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