Enhancing an Extensible Query Optimizer with Support for Multiple Equivalence Types

Database management systems are continuously being extended with support for new types of data and advanced querying capabilities. In large part because of this, query optimization has remained a very active area of research throughout the past two decades. At the same time, current commercial optimizers are hard to modify, to incorporate desired changes in, e.g., query algebras or transformation rules. This has led to a number of research contributions aiming to create extensible query optimizers, such as Starburst, Volcano, and OPT++. This paper reports on a study that has enhanced Volcano to support a relational algebra with added temporal operators, such as temporal join and aggregation. These enhancements include the introduction of algorithms and cost formulas for the new operators, six types of query equivalences, and accompanying query transformation rules. The paper describes extensions to Volcano's structure and algorithms and summarizes implementation experiences.