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Abstract & key component of any relational database system is the query •essing sub-system. The high level query language allows us • write queries that take a great deal of time to be executed. ’is execution time can be greatly reduced, if the optimizer i—phrases the query before executing it. This thesis reports ff an attempt for providing evaluation for different optimization algorithms, in addition to providing a unified optimization new optimization methodologies and algorithms that cover a subset of SQL queries. Very little work has been directed towards evaluating the existing algorithms to come up with a unified optimization methodology that covers nested and canonical form queries. Our objective is to minimize the response time of SQL queries. To compare between different optimization algorithms that are slightly modified to give better results, simulation of the optimization process is used. This leads to the integrated optimization methodology. SQL queries have been classified to different Query-types. A sample for each query-type is provided. The simulated algorithms are applied against the samples to obtain the results that are used along with Algorithms complexities to evaluate the optimization algorithms. The evaluation process has included cost-performance analysis. The results are aggregated to reach the conclusions of this work. |