MapReduce based scalable range query architecture for big spatial data

Finding all objects that overlap a given range query is very important in terms of extraction useful information from big spatial data. In this study, in order to be able to realize range query on large amounts of spatial data, three datasets are created with different size and a MapReduce computation model is set up to test scalability of range queries. Experimental results show that process times for range query reduce with increase of conventional machines.