Skyline Evaluation Within Join Operation, Block Nested Loop Join Implementation

Skyline Join approach in its Naïve age work as it computes join first and then apply skyline computation to find corresponding skyline objects. Considering increase in cardinality and dimensionality of join table the cost of computing skyline in a non-reductive join relation is costlier than that of on single table. Most of the existing work on skyline queries for databases mainly discusses the computation efficiency in single relational table. In proposed work we investigate the evaluation of skylines over disparate sources via joins in efficient manner. The basic idea of our approach is that without computing skyline in the entire joined table, we can process the joined skyline only based on the property of being skyline to quickly identify the skyline object for the joined tuple. We propose an algorithm to build on top of the traditional relational Block Nested-Loop join algorithms, which fuses the computation of the join and the skyline in order to outputs the correct skyline without computing the full join. Our Experimental results demonstrate the applicability of interweaving join and skyline together.