With the coming era of big data, SuperMap realizes the technological innovation of all aspects of the spatial big data process. SuperMap deeply integrates big data storage management, big data spatial analysis and big data real-time stream processing with SuperMap GIS. This fully improves the capability of big data supporting, and forms a new spatial big data GIS technology system with following characteristics.
SuperMap GIS improves the efficient and stable storage management capability of spatial big data by extended support to the distributed files systems and distributed databases.
SuperMap provides SuperMap iObjects for Spark spatial big data components. The Spark spatial data model is extended from the kernel. This not only reconstructs the existing spatial analysis algorithm based on distributed computing technology which improves the efficiency of massive spatial data analysis, but also develops a series new spatial analysis algorithms that can be directly embedded into Spark to solve the analysis and application problems for spatial big data.
SuperMap iServer provides new web services such as spatial big data storage, spatial big data analysis, real-time streaming data processing, and built-in Spark runtime library which reduces the environment threshold of big data deploying.
SuperMap provides spatial big data visualization technologies such as various aggregation maps, density maps, relationship maps, and heat maps with rich expressions of 2D and 3D images. It makes breakthrough in massive dynamic target 2D and 3D visualization technologies and supports real-time dynamic tracking and management of 500,000-level targets in one screen.
SuperMap iManager can easily realize big data operation and maintenance management through intelligent resource allocation, task automation scheduling, resource monitoring and pre-warning actions.
SuperMap is committed to offer users the powerful spatial big data GIS platform software and services by creating and developing GIS technologies.
SuperMap Big Data GID Platform Software Framework
Ship Data Visualization
The SuperMap iObjects 9D SDX+ spatial data engine imports the ship data in csv format into the SuperMap iServer DataStore cluster for distributed storage. The real-time location of 2.8 million ships will be visualized by small-scale super-preview with the SuperMap iServer 9D multi-process pre-caching process. Also the historical data query will be realized through Elasticsearch's range index in large-scale, and the response time is less than 1 second.
Visualization of Ship Location in Small-scale
Visualization of Ship Location in Large-scale
Ship-tracking Playback in Different Time Period
Location query and trajectory playback of the ship in different time period and zone can be realized according to the historical data, and also the trajectory drawing will be quickly responded. Through the SuperMap iObjects for Spark distributed computing framework, the existing 1.6 billion ships historical data will be thinned and filtered to generate the point data set of the ships’ last locations. Then, the Spark processing result set will be handled by ElasticSearch to maintain its persistence and fast retrieval supports, and the daily ship location will be provided by daily simulation through timeline.
Ship Trajectory Playback in User-defined Time Period
Ship Quantity Statistics
Analysis of ship quantity statistics and distribution in sensitive areas.
The Ship Distribution and Quantity Statistics in User-defined Areas and Time Periods
SuperMap big data GIS solution plays an important role in satellite ship-tracking big data project. With this solution, the ground station big data platform construction work can enable users to solve the massive data storage and visualization problem and saves the cost of data storage and mining. The SuperMap iObjects for Spark attains the goal of user massive historical data cleaning and improves the data quality in data warehouse by filtering the historical data from two dimensions of attribute and space. Also, SuperMap iServer DataStore can be used to realize the distributed storage and the efficient real-time retrieval of users' massive data. Then, users can monitor the ship position distribution and track trajectory by map through the spatial-temporal big data visualization of SuperMap iClient 9D.