International Journal of Database Theory and Application · 2013 · 17 citations · 8 references
ComputingCloud ComputingComputer ScienceData ManagementGeographic Information SystemsStorage SystemsCluster Storage SystemsData Storage SystemsSpatial Data ModelsSpatial Data StructuresSpatial Database SystemsSpatial DatabasesData Access ServicesHigh PerformanceSpatial Data StorageSpatial Data WarehousingSpatial Schema DesignTopological Data StructuresVector Data Storage
Cloud computing technology is changing the mode of the spatial information industry which is applied and provides new ideas for it. Since Hadoop platform provides easy expansion, high performance, high fault tolerance and other advantages, we propose a novel vector spatial data storage schema based on it to solve the problems on how to use cloud computing technology to directly manage spatial data and present data topological relations. Firstly, vector spatial data storage schema is designed based on column-oriented storage structures and key/value mapping to express spatial topological relations. Secondly, we design middleware and merge with vector spatial data storage schema in order to directly store spatial data and present geospatial data access refinement schemes based on GeoTools toolkit. Thirdly, we verify the middleware and the data storage schema through Hadoop cluster experiments. Comprehensive experiments demonstrate that our proposal is efficient and applicable to directly storing large-scale vector spatial data and timely express spatial topological relations.
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