Title :
Heuristics for join processing using nonclustered indexes
Author :
Omiecinski, Edward R.
Author_Institution :
Sch. of Inf. & Comput. Sci., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
1/1/1989 12:00:00 AM
Abstract :
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
Keywords :
relational databases; access paths; bipartite graph model; buffer size; database environment; join processing; nonclustered indexes; page accesses; query optimisation; relational databases; relations; tuples; Bipartite graph; Buffer storage; Computational efficiency; Computer science; Cost function; Indexes; Indexing; Query processing; Relational databases;
Journal_Title :
Software Engineering, IEEE Transactions on