An Innovative Query Tuning Scheme for Large Databases

In today's competitive world businesses place more emphasis on information considering them as the more valuable asset of the organization. Hence data is given more attention than that is given to hardware or software and even sometimes to the human resources. The utility of data relies on the fact that how soon it can be turned into useful information and to strategic knowledge. Data is generally stored in a database that powers the company's information system. Relational databases store data in a series of related tables as rows and columns. When a query is issued seeking data from the database, it extracts data from multiple tables depending on the criteria set in the query and presents it as a single set of rows and columns. Hence, the response time of SQL queries becomes a visible factor for the performance of the entire information system. Therefore, query optimization becomes a vital function for preventing performance degradation. In this paper, the authors present two SQL tuning techniques that improve the performance of data retrieval from relational databases over non tuned SQL queries.