Issue No. 01 - January (1989 vol. 15)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/32.21722
<p>The author examines join processing when the access paths available are nonclustered indexes on the joining attribute(s) for both relations involved in the join. He uses a bipartite graph model to represent the pages from the two relations that contain tuples to be joined. The minimization of the number of page accesses needed to compute a join in the author's database environment is explored from two perspectives. The first is to reduce the maximum buffer size so that no page is accessed more than once, and the second is to reduce the number of page accesses for a fixed buffer size. The author has developed heuristics for these problems. He gives performance comparisons of these heuristics and another method that recently appeared in the literature. Results show that one particular heuristic performs very well for addressing the problem from either perspective.</p>
relational databases; query optimisation; join processing; nonclustered indexes; access paths; bipartite graph model; relations; tuples; page accesses; database environment; buffer size; relational databases.
E. Omiecinski, "Heuristics for Join Processing Using Nonclustered Indexes," in IEEE Transactions on Software Engineering, vol. 15, no. , pp. 18-25, 1989.