Bringing order to query optimization
ACM SIGMOD Record
SilkRoute: A framework for publishing relational data in XML
ACM Transactions on Database Systems (TODS)
Toward autonomic computing with DB2 universal database
ACM SIGMOD Record
Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Dynamic Constraints Derivation and Maintenance in the Teradata RDBMS
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Query sampling in DB2 Universal Database
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Join minimization in XML-to-SQL translation: an algebraic approach
ACM SIGMOD Record
Exploiting Interactions among Query Rewrite Rules in the Teradata DBMS
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
Journal of Intelligent Information Systems
Merging views containing outer joins in the Teradata DBMS
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Efficient auditing for complex SQL queries
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
ARGUS: rete + DBMS = efficient persistent profile matching on large-volume data streams
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Hybrid query execution engine for large attributed graphs
Information Systems
| Hi-index | 0.01 |
The complexity of queries in relational DBMSs is increasing, particularly in the decision support area and interactive client sewer environments. This calls for a more powerful and flexible optimization of complex queries. H. Pirahesh et al. (1992) introduced query rewrite as a distinct query optimization phase mainly targeted to responding to this requirement. This approach has enabled us to extensively enrich the optimization rules in our system. Further, it has made it easier to incrementally enrich and adapt the system as need arises. Examples of such query optimizations are predicate pushdown, subquery and magic sets transformations, and decorrelating subquery. We describe the design and implementation of a rule engine for query rewrite optimization. Each transformation is implemented as a rule which consists of a pair of rule condition and action. Rules can be grouped into rule classes for higher efficiency, better understandability and more extensibility. The rule engine has a number of novelties in that it supports a full spectrum of control-from totally data driven to totally procedural. Furthermore, it incorporates a budget control scheme for controlling the resources taken for query optimization as well as guaranteeing the termination of rule execution. The rule engine and a suite of query rewrite rules have been implemented in Starburst relational DBMS prototype and a significant portion of this technology has been integrated into IBM DB2 Common Server relational DBMS.