ACM Transactions on Database Systems (TODS)
Practical selectivity estimation through adaptive sampling
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
On the propagation of errors in the size of join results
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Adaptive selectivity estimation using query feedback
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Efficient mid-query re-optimization of sub-optimal query execution plans
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Approximation algorithms
Exploiting statistics on query expressions for optimization
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Automating Statistics Management for Query Optimizers
IEEE Transactions on Knowledge and Data Engineering
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
LEO - DB2's LEarning Optimizer
Proceedings of the 27th International Conference on Very Large Data Bases
Pipelining in multi-query optimization
Journal of Computer and System Sciences - Special issu on PODS 2001
Robust query processing through progressive optimization
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
The history of histograms (abridged)
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Automated statistics collection in DB2 UDB
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Foundations and Trends in Databases
A development environment for query optimizers
Proceedings of the Third International Workshop on Testing Database Systems
Optimizing queries with expensive video predicates in cloud environment
Concurrency and Computation: Practice & Experience
Rapid experimentation for testing and tuning a production database deployment
Proceedings of the 16th International Conference on Extending Database Technology
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The accuracy of cardinality estimates is crucial for obtaining a good query execution plan. Today's optimizers make several simplifying assumptions during cardinality estimation that can lead to large errors and hence poor plans. In a scenario such as query optimizer testing it is very desirable to obtain the "best" plan, i.e., the plan produced when the cardinality of each relevant expression is exact. Such a plan serves as a baseline against which plans produced by using the existing cardinality estimation module in the query optimizer can be compared. However, obtaining all exact cardinalities by executing appropriate subexpressions can be prohibitively expensive. In this paper, we present a set of techniques that makes exact cardinality query optimization a viable option for a significantly larger set of queries than previously possible. We have implemented this functionality in Microsoft SQL Server and we present results using the TPC-H benchmark queries that demonstrate their effectiveness.