Parallel spatial nearest neighbour query based on grid index

In recent years, with the mobile device starting to carry sensors, the spatial data grows rapidly in the cloud. How to effectively store and query big spatial data to improve the ability of spatial data processing becomes a core problem of the big data era. This paper proposed a version of improving indexing mechanism, the parallelization grid index, by doing research on several kinds of traditional spatial data index, and we designed spatial RNN data query algorithm basing on it. Extensive experiments using both real and synthetic datasets demonstrated that our proposed methods outperform the state-of-the-art algorithms in spatial RNN queries.