Spatial big data acts as a important key role in wireless networks applications. In that spatial and spatio temporal problems contains the distinct role in big data and it's compared to common relational problems. If we are solving those problems means describing the three applications for spatial big data. In each applications imposing the specific design and we are developing our work on highly scalable parallel processing for spatial big data in Hadoop frameworks by using map reduce computational model. Our results show that enables highly scalable implementations of algorithms using Hadoop for the purpose of spatial data processing problems. Inspite of developing these implementations requires specialized knowledge and user friendly.
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