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An improved Hilbert curve for parallel spatial data partitioning

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Geo-spatial Information Science

Abstract

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.

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Authors and Affiliations

  1. School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China

    Meng Lingkui

Authors
  1. Meng Lingkui
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  2. Huang Changqing
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  3. Zhao Chunyu
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  4. Lin Zhiyong
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Additional information

Funded by the National 863 Program of China (No. 2005AA113150), and the National Natural Science Foundation of China (No.40701158).

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Meng, L., Huang, C., Zhao, C. et al. An improved Hilbert curve for parallel spatial data partitioning. Geo-spat. Inf. Sci. 10, 282–286 (2007). https://doi.org/10.1007/s11806-007-0107-z

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  • DOI: https://doi.org/10.1007/s11806-007-0107-z

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