Optimizing Spatial Databases

Anda Belciu, Stefan Olaru
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引用次数: 7

Abstract

This paper describes the best way to improve the optimization of spatial databases: through spatial indexes. The most commune and utilized spatial indexes are R-tree and Quadtree and they are presented, analyzed and compared in this paper. Also there are given a few examples of queries that run in Oracle Spatial and are being supported by an R-tree spatial index. Spatial databases offer special features that can be very helpful when needing to represent such data. But in terms of storage and time costs, spatial data can require a lot of resources. This is why optimizing the database is one of the most important aspects when working with large volumes of data.
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优化空间数据库
本文描述了提高空间数据库优化的最佳方法:通过空间索引。本文对r树和四叉树这两种空间指标进行了介绍、分析和比较。此外,还给出了一些在Oracle Spatial中运行的查询示例,这些查询由R-tree空间索引支持。空间数据库提供了一些特殊的特性,在需要表示此类数据时非常有用。但就存储和时间成本而言,空间数据可能需要大量资源。这就是为什么在处理大量数据时,优化数据库是最重要的方面之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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