A System for Query Processing and Optimization in SQL for Set Predicates using Compressed Bitmap Index

In data warehousing and OLAP application, within the database relation comparison between group of tuples with their attribute and values requires syntax and semantics that currently available Database Management System do not provide. Currently, complex SQL queries consist of scalar-level operations are often formed to obtain even very simple set-level semantics. Such queries are not only difficult to write but also challenging for a database engine to optimize, which results in costly evaluation. We studied aggregate function-based technique and Compressed bitmap index-based technique to processing set predicates. Bitmap index, which creates one bitmap vector for individual attribute value. It occupy less space than raw data and gives more opportunities for efficient query processing. We exploited the property of bitmap index and developed a very effective bitmap pruning strategy by using Word-Aligned Hybrid (WAH) compression for processing queries, which eliminates the necessity of scanning and processing the entire data set (table),which results in speeds up the query processing significantly. Experiments verified our technique is much more efficient than existing algorithms in optimizing queries for set Predicates.