Optimizing query execution for variable-aligned length compression of bitmap indices

摘要: Indexing is a fundamental mechanism for efficient data access. Recently, we proposed the Variable-Aligned Length (VAL) bitmap index encoding framework, which generalizes commonly used word-aligned compression techniques. VAL presented variable-aligned allows columns of to be compressed using different lengths. This flexibility creates tunable that balances trade-off between space and query processing time. The variable format presents several unique opportunities optimization. In this paper explore multiple algorithms optimize both point queries range in VAL. particular, propose dynamic encoding-length translation heuristic process queries. For queries, column orderings based on bitmap's metadata: largest segment length first (lsf), size (size), weighted (ws). our empirical study over real synthetic sets, show selection scheme produces execution times only 3.5% below optimal. We also found ordering significantly consistently out-performs other Finally, scale sets are row-ordered.