Abstract
Digital Elevation Model (DEM) has been widely used in various sectors. But its data structure is special, and the amount of data is large. When it comes to big data or large-scale data simulation, the data processing of stand-alone mode often fails to meet the needs of users. This paper focuses on the Hadoop cloud computing platform for large data parallel processing and its built-in data types is limited, study the organization method of the regular grid DEM in the cloud computing platform, and designs the data types that applicable to the regular grid DEM processing in MapReduce framework. Finally, realize the parallelization processing of DEM and use non-source flood analysis as an example to verify the feasibility of data types.
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