Using Data Clustering to Optimize Scatter Bitmap Index for Membership Queries

摘要

Decision support systems that retrieve information from a data warehouse environment are usually designed to process complex and ad hoc queries. Indexing techniques based on bitmap representations can be used to improve the efficiency of information retrieval. Scatter Bitmap Index uses less space and is more CPU-efficient than other bitmap indexing techniques. It is simple to represent, and improves query processing time by utilizing low-cost Boolean operations and multiple index scans. The Scatter Bitmap Index technique performs simple predicate conditions on the index level before going to the primary data source. Furthermore, Scatter Bitmap Index can be optimized by applying K-mode Clustering, which finds relationships among attribute values in queries. In this paper, we show that Data Clustering with Scatter Bitmap Index can improve query processing time for membership queries.