Abstract
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.
Highlights
Digital maps, or online electronic maps, are the core components of modern Web geographic information systems (GIS)
With the rapid growth of various networked geospatial data sources, such as volunteered geographic information in social networks, real-time data acquired from sensor networks and large quantities of earth observation data from satellites, web-based electronic map service infrastructures have faced the big challenge of organization and processing strategies for the huge volume of spatial data and its inherent complexity
This is followed by an illustration of the extended vector map tile generation and locating algorithm, preparing for the Not Only SQL (NoSQL)-based tile data model
Summary
Online electronic maps, are the core components of modern Web geographic information systems (GIS). With the rapid growth of various networked geospatial data sources, such as volunteered geographic information in social networks, real-time data acquired from sensor networks and large quantities of earth observation data from satellites, web-based electronic map service infrastructures have faced the big challenge of organization and processing strategies for the huge volume of spatial data and its inherent complexity This has resulted in the pursuit of advanced high-performance computing architectures and sophisticated algorithms to achieve scalable map data storage and fast processing. In the remainder of the paper, we sequentially introduce applications of the cloud-based computing method, such as Hadoop, NoSQL, and MapReduce, in big geo-data processing This is followed by an illustration of the extended vector map tile generation and locating algorithm, preparing for the NoSQL-based tile data model.
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