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Efficient Processing of Skyline Queries Using MapReduce www.ieeelatestprojects.com Contact for ieee latest projects:98451 66723 | 98866 92401
The skyline operator has attracted considerable attention recently due to its broad applications
computing a skyline is challenging today since we have to deal with big data. • For data intensive applications, the MapReduce framework has been widely used recently. • In this project, we propose the efficient parallel algorithm SKY-MR+ for processing skyline queries using MapReduce.
We first build a quadtree-based histogram for space partitioning by deciding whether to split each leaf node judiciously based on the benefit of splitting in terms of the estimated execution time. • In addition, we apply the dominance power filtering method to effectively prune non-skyline points in advance.
We next partition data based on the regions divided by the quadtree and compute candidate skyline points for each partition using MapReduce. • Finally, we check whether each skyline candidate point is actually a skyline point in every partition using MapReduce.
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