The EXODUS optimizer generator
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Experiences building the open OODB query optimizer
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Adaptable query optimization and evaluation in temporal middleware
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Starburst Mid-Flight: As the Dust Clears
IEEE Transactions on Knowledge and Data Engineering
A Foundation for Conventional and Temporal Query Optimization Addressing Duplicates and Ordering
IEEE Transactions on Knowledge and Data Engineering
User-Defined Table Operators: Enhancing Extensibility for ORDBMS
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
EROC: A Toolkit for Building NEATO Query Optimizers
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The Volcano Optimizer Generator: Extensibility and Efficient Search
Proceedings of the Ninth International Conference on Data Engineering
OPT++ : an object-oriented implementation for extensible database query optimization
The VLDB Journal — The International Journal on Very Large Data Bases
Developing a DataBlade for a New Index
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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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.