作者: Xiang, LG (Xiang, Longgang); Huang, JT (Huang, Juntao); Shao, XT (Shao, Xiaotian); Wang, DH (Wang, Dehao)
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摘要: This 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.
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