An Efficient Multi-Component Indexing Embedded Bitmap Compression for Data Reorganization

Abstract

In the present study, we discuss bitmap indices with compression using multi-component indexing for the efficient storage and fast retrieval of large scientific data. The bitmap compression indices embedded multi-component shows superiority over bitmap compressed indices. Gray Code ordering algorithm is used which runs in linear time in the order of the size of the database. Reduction in the number of columns is observed when multi-component indexing is applied on the binned data. An improvement in the space requirement for Bitmap Index by 25% is observed when one time component indexing is applied. Satisfactory improvement factor is observed when gray code ordering and WAH compression technique is used. Due to processing overhead, two component indexes is used. Tuple reordering problem is studied to reorganize database tuples for optimal compression rates. The experimental results on real data sets show that the compression ratio shows the improvement by a factor of 2 to 8.