Implementing Semantic Query Optimization in Relational Databases

Abstract

Semantic query optimization is applied to relational databases using the inductive learning approach. This approach generates an alternate query using the learning framework and the algorithm. The alternate query should be semantically equivalent to original query. The semantically equivalent query generated should be less expensive than the original query. These can be implemented in SQL using the SQL hints. These hints allow user to implement the desired plan for the query.