Relational database applications' optimization and performance study

The objective of the thesis is to develop efficient query processing techniques for large relational database applications since, when such applications have to process more than a million records, performance becomes a key issue. Some techniques rely upon massive hardware architectures and new database software to improve efficiency of large database systems. One of the objectives of the thesis, however, is to develop optimization techniques using existing hardware and software.

Performance improvement may be achieved by the use of parallel application processes that can process different fragments of a database at the same time. Further performance improvement is achieved by using dynamic SQL and simulating an SQL outer join in the 'C programming language. Simulating the SQL function MAX and proper locking mechanism resulted in marginal performance improvement.

Database design to support the use of parallel application processes and the other techniques is presented. Applications are built to test the techniques and the performance results are presented and discussed. Multiple test cases are run for each technique to ensure that the results are similar in time. For each technique, the scenarios of maximum performance improvement, the underlying mechanism, and possible limitations are discussed.