The traditional CPIR algorithm needs to scan the whole data space with a large amount of computation so it's not suitable for big data. This thesis proposes that the parallel grouping range privacy query algorithm based on Spark. The range privacy query algorithm divides the grid into different groups in order to reduce the amount of computing and parallelizing computation to improve the efficiency based on Spark. It has a big improvement on server execution time, client execution time and communication cost.
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