随着信息技术的发展，各种新技术层出不穷并运用到实际项目中，云计算技术是目前的热点技术之一，利用云计算平台提供的高并发、大存储、虚拟化等技术来处理高访问量的海量数据是大势所趋。对于海量数据存储来说，数据库的重要性越来越突出。近年来随着数据库领域的发展，非关系型数据库越来越得到广泛的应用，比较突出的有MonogoDB、Cassandra、Redis等，在云计算平台的设计实现中使用分布式可扩展的非关系型数据库已经成为趋势。 近年来GIS技术越发成熟，存储的数据量也越来越多，传统的地理信息系统在低成本解决数据应用平台的高并发、海量数据存储、可伸缩性方面显得力不从心。随着云计算技术的发展，可以使得GIS与云计算技术结合，构建新型的GIS云平台，以便简化GIS应用部署和管理，提高GIS数据平台和基础设施的灵活性，可以明显降低地理信息系统的投资和运营成本，同时很好地解决了高并发、海量数据存储与可伸缩性方面的问题。 MongoDB是近来应用比较广泛的非关系型数据库，它具有面向集合存储、模式自由、同时支持动态查询等优点，可以很好地存储具有复杂属性的GIS矢量数据，简化GIS云平台的部署。 本文以分布式集群数据库MonogDB为基础，设计并搭建了以存储GIS空间信息矢量数据的数据库平台，将GIS空间信息矢量数据处理后存储在集群节点中，并使用Python语言设计与实现了基于REST接口的操作GIS空间信息矢量数据的中间层。在Cacti基础上设计与实现了新的可视化的集群监控模块，并设计与实现了数据库综合数据管理模块。 本文设计的基于MongoDB的GIS云计算平台可以根据对数据的访问量进行动态伸缩集群节点，避免了传统GIS应用系统单点故障问题，可以快速的查询并返回数据结果，与传统单点GIS应用系统相比，本平台提高了数据使用的灵活性，节约了硬件资源的使用，降低了GIS应用系统的部署难度与运营成本。With the development of information technology, a variety of new technologies emerging and applied to projects, cloud computing technology is one of the current hot technology, the use of cloud computing platform provides high concurrency, storage, virtualization technology to deal with high access the amount of huge amounts of data is the trend. The importance of database is more prominent for mass data storage. In recent years, with the development of the database field, NoSQL database has been more widely used, such as MonogoDB, Cassandra, Redis, etc.. using distributed and scalable non-relationalThe database has become a trend in designing and implementing cloud computing platform.GIS technology is more and more mature in recent years, more and more amount of data is stored, the traditional geographic information system data applications platform appeared to be inadequate in high concurrency with low-cost, mass data storage, scalability.With the development of cloud computing technology, people can make GIS and cloud computing technology combine to build the new GIS Cloud platform in order to simplify the GIS applications deployment and management, improve the flexibility of GIS data platform and infrastructure, with significantly reducing the Geographic Information System investment and operating costs. It is a good solution to the high concurrency, mass data storage and scalability issues. MongoDB is a used widely NoSQL database, it has a set-oriented storage, free mode, while supporting dynamic queries, etc., it can be stored GIS vector data with complex attributes to simplify the deployment of GIS Cloud platform. The system designed and built a database to store spatial information of GIS vector data platform based on MonogDB. GIS spatial vector is stored in the cluster nodes after data processing. We use the Python language designing and implementing a REST-based the middle layer of the interface operation GIS spatial vector data. We design and implement the new visualization cluster monitoring module based on Cacti and the visual data management module. The system can expand cluster nodes flexibly. It can avoid single point failure of traditional GIS applications. It can quickly query and return the data results. Compared with the traditional single-point GSI applications, the system improves the flexibility use of data, saving the use of hardware resources, reducing the difficulty of deployment and operating costs of the GIS applications.学位：工程硕士院系专业：软件学院_软件工程学号：2432010115226
