An Efficient Bitmap Indexing Strategy Based on Word-Aligned Hybrid for Data Warehouses

This paper presents an efficient bitmap indexing technique that improves the performance of the word-aligned hybrid (WAH) for high-cardinality attributes in data warehousing applications. WAH compression is based on the run-length encoding, and its performance depends on the presence of long runs of identical bits. To ensure the existence of such long runs and thus achieve higher compression rate, our strategy is, before building the bitmap index, to reorganize the base data by reordering (sorting) and clustering the attribute to be indexed. The experiments showed that our strategy significantly reduces the size of WAH bitmap indices. Moreover, the response time measured for both equality and range queries was showed to decrease substantially.