文献类型：期刊文献

英文题名：An Effective NoSQL-Based Vector Map Tile Management Approach

作者：Wan, Lin[1];Huang, Zhou[2];Peng, Xia[3,4]

第一作者：Wan, Lin

通讯作者：Huang, Z[1]

机构：[1]China Univ Geosci, Fac Informat Engn, Wuhan 430074, Peoples R China;[2]Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China;[3]Beijing Union Univ, Inst Tourism, Beijing 100101, Peoples R China;[4]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China

第一机构：China Univ Geosci, Fac Informat Engn, Wuhan 430074, Peoples R China

通讯机构：[1]corresponding author), Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China.

年份：2016

卷号：5

期号：11

外文期刊名：ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION

收录：;Scopus(收录号：2-s2.0-85016085705);WOS:【SSCI(收录号:WOS:000390104200022)，SCI-EXPANDED(收录号:WOS:000390104200022)】；

基金：This research was supported by the grants from the National Natural Science Foundation of China (41401449, 41501162, 41625003), Scientific Research Key Program of Beijing Municipal Commission of Education (KM201611417004), New Starting Point Program of Beijing Union University (ZK10201501), State Key Laboratory of Resources and Environmental Information System, and Key Laboratory of Satellite Surveying Technology and Application, Chinese National Administration of Surveying, Mapping and Geoinformation.

语种：英文

外文关键词：digital map; map tile; NoSQL; MapReduce; cloud computing

摘要：Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL) databases has resulted in a new data storage and management model for scalable spatial data deployments and fast tracking. They better suit the scenario of high-volume, low-latency network map services than traditional standalone high-performance computer (HPC) or relational databases. In this paper, we propose a flexible storage framework that provides feasible methods for tiled map data parallel clipping and retrieval operations within a distributed NoSQL database environment. We illustrate the parallel vector tile generation and querying algorithms with the MapReduce programming model. Three different processing approaches, including local caching, distributed file storage, and the NoSQL-based method, are compared by analyzing the concurrent load and calculation time. An online geological vector tile map service prototype was developed to embed our processing framework in the China Geological Survey Information Grid. Experimental results show that our NoSQL-based parallel tile management framework can support applications that process huge volumes of vector tile data and improve performance of the tiled map service.