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 t...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.展开更多
基金Funded by the National 863 Program of China （No. 2005AA113150）, and the National Natural Science Foundation of China （No.40701158）.
文摘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.
