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Selective Materialization: An Efficient Method for Spatial Data Cube Construction

机译:选择性算法:一种有效的空间数据立方体建设方法

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On-line analytical processing (OLAP) has gained its popularity in database industry. With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and on-line analytical processing of sptial data. In this paper, we study methods for spatial OLAP, by integration of nonspatial on-line analytical processing (OLAP) methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies proposed, including approximation and partial materialization of the spatial objects resulted from spatial OLAP operations. Some techniques for selective materialization of the spatial computation results are worked out, and the performance study has demonstrated the effectiveness of these techniques.
机译:在线分析处理(OLAP)在数据库行业中取得了普及。通过存储在空间数据库中的大量数据以及将空间组件引入许多关系或对象关系数据库,研究空间数据仓库和在线数据的在线分析处理是很重要的。本文通过使用空间数据库实现技术的非缺点在线分析处理(OLAP)方法集成了空间OLAP的研究方法。提出了一种空间数据仓库模型,包括空间和非缺点尺寸和措施。研究了用于计算这些空间数据多维数据集的空间数据多维数据集和分析处理的方法,提出了几种策略,包括空间OLAP操作导致的空间物体的近似和部分实现。解决了空间计算结果的选择性实现的一些技术,并且性能研究表明了这些技术的有效性。

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