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Cloud computing has been a study hot spot of computer network technology at home and abroad, since it was proposed in 2007. GIS raster data has amount of data, so when a large number of users access, traditional file mapping and network database, etc will have problems such as server overload, lower sharing efficiency. Cloud computing is undoubtedly the best ideas to solve storage and display of huge amount of raster data. At present, managing and display raster data on the public cloud platform have developed methods and techniques, in which Google Earth is one of the best. But using public cloud to manage massive raster data within the enterprise, it will bring security issues such as leakage of confidential data, so we need to build private clouds under LAN environment for enterprises. This paper, first, discussed the internal private cloud framework and the design of distributed file system under the LAN environment, and analyzed how to storage image pyramids for raster data in the distributed file system, and then proposed the Map/Reduce technology based on G/S mode, to achieve load balancing strategy for data download. Studies show that the private cloud framework in this paper, the grid download ability continuously improved, as the data nodes increases, it can meet internal management and shared purpose of raster data, the research results have a theoretical value and practical significance.