Query optimization in databases has gain a lot of importance in recent years. In this paper, we have analyzed different techniques of query optimization in relational databases and compared their performance. We have covered the techniques which use different methods for query representation.
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.
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