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An Improved Hilbert Curve for Parallel Spatial Data Partitioning

机译:改进的希尔伯特曲线用于并行空间数据划分

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摘要

A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.
机译:考虑空间信息的巨大性质和矢量数据项的可变长度特性,提出了一种新颖的希尔伯特曲线用于并行空间数据划分。基于改进的希尔伯特曲线,可以将算法设计为在并行空间数据库中的多个磁盘之间实现几乎均匀的空间数据分区。因此,可以显着避免数据不平衡的现象,并且可以提高搜索和查询效率。

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