A physical storage model for efficient statistical query processing

A common approach to improving the performance of statistical query processing is to use precomputed results. Another lower-level approach would be to redesign the storage structure for statistical databases. This avenue is relatively unexplored. The objective of this paper is to present a physical storage structure for statistical databases, whose design is motivated by the characteristics of statistical queries. We show that our proposal enhances multi-attribute clustering efficiency, and improves the performance of statistical and aggregational queries. This customized structure reduces the amount of I/O incurred statistical query processing, thus decreasing the response time.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>