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Abstract : |
The aim of query optimization is to produce an equivalent query which is less expensive to process than the original query. Semantic query optimization involves the use of semantic knowledge during the optimization process. The success strongly depends on the availability of this knowledge. We present a rule--based approach of semantic query optimization which overcomes the limitation of predefined knowledge by discovering constraints. We show that unnecessary distinct--keywords and group by--parts of an SQL query can be detected and removed with the use of discovered constraints. 1, |
