Abstract
Bitmaps are commonly used for indexing read-mostly data sets. The range of an attribute is split into bins, where its values are placed: bij = 1 denotes the value of the ith tuple is in the jth bin, and bij = 0 otherwise. A number of query types can be decomposed into the systematic application of boolean operators over sets of bins. However, when bitmaps are high-dimensional, the overall query-processing performance can deteriorate due to the increased number of bins that participate per query.
We propose a caching framework that organizes, manages, and integrates cached partial results to accelerate query processing on high-dimensional bitmaps. We begin by showing that, to resolve general complex disjunctive and conjunctive queries, the selection of an optimal set of partial bitmap results is NP-complete. A restriction on this problem to only consider consecutive bin sequences (characteristic of common range and point queries) allows us to solve it efficiently. The evaluation our caching system over several workloads carried out on the TPC-H benchmark and a real network-intrusion data set is presented.