Automatic Database Clustering Using Data Mining

Abstract

Because of data proliferation, efficient access methods and data storage techniques have become increasingly critical to maintain an acceptable query response time. One way to improve query response time is to reduce the number of disk I/Os by partitioning the database vertically (attribute clustering) and/or horizontally (record clustering). A clustering is optimized for a given set of queries. However in dynamic systems the queries change with time, the clustering in place becomes obsolete, and the database needs to be re-clustered dynamically. In this paper we discuss an efficient algorithm for attribute clustering that dynamically and automatically generate attribute clusters based on closed item sets mined from the attributes sets found in the queries running against the database