Abstract:

With the growth of the application of spatial information,distributed spatial query has become an important question of the spatial database research field,of which the most widely used and most complex is the distributed spatial join queries,and the computational cost and transport cost are very high.The common methods to dissolve this question requires a spatial index on the data sets and sensitivity to distributed data, which is not satisfied in most cases. Considering this issue, the paper proposes a distributed spatial join strategy based on the Kdtree Recursive Partitioning Join, which is aimed at minimizing the cost of network data transmission, and recursively divides the adjacent regions based on task partitioning. The experiments demonstrate that this strategy is better than the traditional ones in different data distribution cases, which is effective in reducing network transmission costs and presents better performance.

Key words: saptial join query;kdtree;distribute