Cost effective genetic optimal database index set for decision support systems with attributes accessing probabilities

Abstract

Index mechanism speeds up the data retrieval with the values given for the search attribute. In decision support systems, creating useful indexes is one of the most important tasks to achieve good performance. In order to create useful indexes, thorough knowledge and understanding about the uses of the data, the types and frequencies of queries to be performed etc is necessary and important. In this paper, we describe the creation of cost effective genetic optimal database index set for the decision support systems based on the attributes accessing probabilities thru genetic algorithm. It is implemented with C# in .NET by considering microsoft SQL server 2000 as back end database and performed extensive experiments and the results indicate the significant performance improvement with minimizing the cost involved in the query process with the generated optimal database index set which is based on the access requirements.