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A Generic Approach to Bulk Loading Multidimensional Index Structures

机译:批量加载多维索引结构的通用方法

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Recently there has been an increasing interest in supporting bulk operations on multidimensional index structures. Bulk loading refers to the process of creating an initial index structure for a presumably very large data set. In this paper, we present a generic algorithm for bulk loading which is applicable to a broad class of index structures. Our approach differs completely from previous ones for the following reasons. First, sorting multidimensional data according to a predefined global ordering is completely avoided. Instead, our approach is based on the standard routines for splitting and merging pages which are already fully implemented in the corresponding index structure. Second, in contrast to inserting records one by one, our approach is based on the idea of inserting multiple records simultaneously. As an example we demonstrate in this paper how to apply our technique to the R-tree family. For R-trees we show that the I/O performance of our generic algorithm meets the lower bound of external sorting. Empirical results demonstrate that performance improvements are also achieved in practice without sacrificing query performance.
机译:最近,人们对在多维索引结构上支持批量操作越来越感兴趣。批量加载是指为可能非常大的数据集创建初始索引结构的过程。在本文中,我们提出了一种用于批量加载的通用算法,该算法适用于广泛的索引结构类。由于以下原因,我们的方法与以前的方法完全不同。首先,完全避免了根据预定义的全局排序对多维数据进行排序。相反,我们的方法基于用于拆分和合并页面的标准例程,这些例程已在相应的索引结构中完全实现。其次,与一个记录一个一个地插入相反,我们的方法基于同时插入多个记录的想法。作为示例,我们在本文中演示如何将我们的技术应用于R-tree系列。对于R树,我们证明了通用算法的I / O性能符合外部排序的下限。实验结果表明,在不牺牲查询性能的情况下,在实践中也可以提高性能。

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