On the optimal nesting order for computing N-relational joins
ACM Transactions on Database Systems (TODS)
Query optimization by simulated annealing
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Optimization of large join queries
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Efficient optimization of large join queries using Tabu Search
Information Sciences—Informatics and Computer Science: An International Journal
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Query Optimization in Database Systems
ACM Computing Surveys (CSUR)
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
A Polynomial Time Algorithm for Optimizing Join Queries
Proceedings of the Ninth International Conference on Data Engineering
Optimizing large star-schema queries with snowflakes via heuristic-based query rewriting
CASCON '03 Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research
Computing closest common subexpressions for view selection problems
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
Cooperating SQL Dataflow Processes for In-DB Analytics
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
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As database technology is applied to more and more application areas, user queries on a database become more and more complex. Existing query optimization techniques were not developed for dealing with complex queries and may suffer from some serious problem such as intolerably long optimization time and poor optimizing results. To tackle this challenge, we introduce a new technique to improve the quality of complex query optimization in this paper. The key idea is to exploit the common subqueries that often appear in a complex query and reuse the optimization work done for each common subquery. An algorithm to identify common subqueries efficiently and generate a high-quality execution plan for a given complex query is proposed. The complexity of the algorithm is analyzed. Experiments demonstrate that this proposed polynomial-time technique is quite promising in optimizing complex queries for a database management system.