Discovering representative skyline points over distributed data
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Daisy: the center for data-intensive systems at Aalborg University
ACM SIGMOD Record
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Given a set of multidimensional points, a skyline query returns the interesting points that are not dominated by other points. It has been observed that the actual cardinality (s) of a skyline query result may differ substantially from the desired result cardinality (k), which has prompted studies on how to reduce s for the case where ks. Based on these observations, the paper proposes a new approach, called skyline ordering, that forms a skyline-based partitioning of a given data set such that an order exists among the partitions. Then, set-wide maximization techniques may be applied within each partition. Efficient algorithms are developed for skyline ordering and for resolving size constraints using the skyline order. The results of extensive experiments show that skyline ordering yields a flexible framework for the efficient and scalable resolution of arbitrary size constraints on skyline queries.