Computer Science Department University of Maryland College Park
In this paper, we describe the design and implementation of the ADMS query optimizer. This optimizer integrates query matching into optimization and generates more efficient query plans using cached results. It features data caching and pointer caching, alternative cache replacement strategies, and different cache update methods. A comprehensive set of experiments were conducted using a benchmark database and synthetic queries. The results showed that pointer caching and dynamic cache update strategies substantially saved query execution time and, thus, increased query throughput under situations with fair query correlation and update load. The requirement of the disk cache space is relatively small, and the extra optimization overhead introduced is more than offset by the time saved in query evaluation.
Last updated November 7, 1995