Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
The EXODUS optimizer generator
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
A rule-based view of query optimization
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Testing for the Church-Rosser Property
Journal of the ACM (JACM)
Optimizing the performance of a relational algebra database interface
Communications of the ACM
Accurate estimation of the number of tuples satisfying a condition
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Optimal Plan Search in a Rule-Based Query Optimizer
EDBT '88 Proceedings of the International Conference on Extending Database Technology: Advances in Database Technology
An Observation on Database Buffering Performance Metrics
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Rule-based optimization and query processing in an extensible geometric database system
ACM Transactions on Database Systems (TODS)
ACM SIGMOD Record
The Iris Architecture and Implementation
IEEE Transactions on Knowledge and Data Engineering
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In this paper we present the design and initial performance results of a rule-based query optimizer used in Iris, an object-oriented database system [3]. Query optimization methods are expressed as rules and the entire query process is carried out in a way analogous to the operation of production systems in AI. Two kinds of rules are used: the first kind transform a query, represented as a relational algebra expression, into an equivalent, but simpler, query; the second kind add information to the relational algebra representation to specify join order and data access methods. Preliminary results show that the speed of the query optimizer and the performance of the execution plans generated are comparable to those in a traditional relational database system.