Abstract:

We proposed a Skyline query algorithm based on Rtree index in MapReduce parallel computing model, which solved the low execution efficiency problems of Skyline query in the massive spatial data sets. Through the establishment of Rtree index to realize spatial data of different size range pruning, the algorithm effectively reduced the size of the data required to scan the distributed Skyline query, and improved the execution efficiency of Skyline query in MapReduce model. Comparative tests in different data distribution shows the proposed method has more advantages on efficiency than the existing algorithms.

Key words: MapReduce model, Rtree index, Skyline query, spatial data