An Improved Hilbert Curve for Parallel Spatial Data Partitioning

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...

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Bibliographic Details
Published inGeo-spatial information science Vol. 10; no. 4; pp. 282 - 286
Main Authors Meng, Lingkui, Huang, Changqing, Zhao, Chunyu, Lin, Zhiyong
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.01.2007
Subjects
data imbalance
Hilbert curve
P208
parallel spatial database
spatial data partitioning
希耳伯特曲线
并行空间数据库
数据不均衡
数据划分算法
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Summary: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.
Bibliography:parallel spatial database; spatial data partitioning; data imbalance; Hilbert curve
Hilbert curve
42-1610/P
data imbalance
spatial data partitioning
parallel spatial database
P208
ISSN:1009-5020
1993-5153
DOI:10.1007/s11806-007-0107-z