Bitmap-based indexes are known to be the most effective indexing method for retrieving and answering selective queries in a read-only environment. Various types of encoding bitmap indexes significantly improve query time efficiency by utilizing fast Boolean operations directly on the index before retrieving the raw data. In particular, the dual bitmap index improves the performance of equality queries in terms of the space vs. time trade-off. However, the performance of range queries is unsatisfactory. In this paper, an optimizing algorithm is proposed to improve the range query processing for the dual bitmap index. The results of the experiment conducted show that the proposed algorithm, called Dual-simRQ, reduces the number of bitmap vectors scanned and the Boolean operations performed, which impacts the overall performance for range query processing.
Compressed bitmap indexes: beyond unions and intersections