A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree
AbstractThis paper addresses how to manage planar spatial data using MongoDB, a popular NoSQL database characterized as a document-oriented, rich query language and high availability. The core idea is to flatten a hierarchical R-tree structure into a tabular MongoDB collection, during which R-tree nodes are represented as collection documents and R-tree pointers are expressed as document identifiers. By following this strategy, a storage schema to support R-tree-based create, read, update, and delete (CRUD) operations is designed and a module to manage planar spatial data by consuming and maintaining flattened R-tree structure is developed. The R-tree module is then seamlessly integrated into MongoDB, so that users could manipulate planar spatial data with existing command interfaces oriented to geodetic spatial data. The experimental evaluation, using real-world datasets with diverse coverage, types, and sizes, shows that planar spatial data can be effectively managed by MongoDB with our flattened R-tree and, therefore, the application extent of MongoDB will be greatly enlarged. Our work resulted in a MongoDB branch with R-tree support, which has been released on GitHub for open access. View Full-Text
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Xiang, L.; Huang, J.; Shao, X.; Wang, D. A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree. ISPRS Int. J. Geo-Inf. 2016, 5, 119.
Xiang L, Huang J, Shao X, Wang D. A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree. ISPRS International Journal of Geo-Information. 2016; 5(7):119.Chicago/Turabian Style
Xiang, Longgang; Huang, Juntao; Shao, Xiaotian; Wang, Dehao. 2016. "A MongoDB-Based Management of Planar Spatial Data with a Flattened R-Tree." ISPRS Int. J. Geo-Inf. 5, no. 7: 119.
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