The multi-criteria decision making, which is possible with the advent ofskyline queries, has been applied in many areas. Though most of the existingresearch is concerned with only a single relation, several real worldapplications require finding the skyline set of records over multiplerelations. Consequently, the join operation over skylines where the preferencesare local to each relation, has been proposed. In many of those cases, however,the join often involves performing aggregate operations among some of theattributes from the different relations. In this paper, we introduce suchqueries as "aggregate skyline join queries". Since the naive algorithm isimpractical, we propose three algorithms to efficiently process such queries.The algorithms utilize certain properties of skyline sets, and processes theskylines as much as possible locally before computing the join. Experimentswith real and synthetic datasets exhibit the practicality and scalability ofthe algorithms with respect to the cardinality and dimensionality of therelations.
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