The Non-sql Spatial Data Management Model in Big Data Time
Published in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015
Recommended citation: Zhai Weixin, Yang Zhe, Wang Lin, Wu Feilong, Cheng Chengqi. The non-sql spatial data management model in big data time[C]. proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015. IEEE.
Abstract : This document is a first exploration on the feasibility of the Non-sql database HBase and GeoSOT grids on the management of spatial data in big data time of spatial database. The traditional methods to face the challenge is mainly on the downward expanding; and the consumption of time and storage space is huge, also with a high price. We combine the distributed database HBase and global subdivision grid for data management in this research. The geocodes of the grid can present the spatial position of a spatial object and be regarded as the keyvalue in HBase. The design changes the traditional object-oriented database to geography-oriented database and more geographical characteristics are taken into account. We also make a comparison experiment on our theory and the result turns out that our new method has more advantages of geographical in query when the data volumn is huge.