Efficient k-dominant Skyline Query Based on Dominate Hierarchical Tree in MapReduce

Skyline query is a key technology for information processing. With the increasing of big data, skyline query cannot achieve effectively recommendation because it cannot control the retrieval conditions so that returns too many results. As an extended form of skyline query, k-dominant skyline solves the problem above by reducing the control of certain attribute so as to filtering large amount of data. However, the k-dominant query algorithm sometimes depends on user definition and the results cannot be shared. To solve above issues, we propose an efficient k-dominant skyline query based on dominate hierarchical tree in MapReduce environment. First, we present an index structure called dominate-based hierarchical tree (DBH-tree) and its construction algorithm. We can divide data into subspace according to the k-dominant using the index structure. Then, we propose the k-dominant skyline query algorithm with Map and Reduce function. The algorithm can quickly and efficiently draw all the dominating results and provide global results sharing. Finally, extensively experiments shown that our algorithm with synthetic and real datasets have great efficiency and gradual output.