AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The Microsoft Relational Engine
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
The Query Optimizer in Tandem's new ServerWare SQL Product
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Exploiting Upper and Lower Bounds In Top-Down Query Optimization
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
DB2 Advisor: An Optimizer Smart Enough to Recommend its own Indexes
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Automatic physical database tuning: a relaxation-based approach
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
To tune or not to tune?: a lightweight physical design alerter
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Automatic SQL tuning in oracle 10g
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Constrained physical design tuning
Proceedings of the VLDB Endowment
Adaptive Physical Design for Curated Archives
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Index interactions in physical design tuning: modeling, analysis, and applications
Proceedings of the VLDB Endowment
Intelligent Data Granulation on Load: Improving Infobright's Knowledge Grid
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
Constrained physical design tuning
The VLDB Journal — The International Journal on Very Large Data Bases
Minimizing database repros using language grammars
Proceedings of the 13th International Conference on Extending Database Technology
Listen to the customer: model-driven database design
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
CoPhy: a scalable, portable, and interactive index advisor for large workloads
Proceedings of the VLDB Endowment
Predicting cost amortization for query services
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Automated partitioning design in parallel database systems
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Semi-automatic index tuning: keeping DBAs in the loop
Proceedings of the VLDB Endowment
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Automated physical design tuning for database systems has recently become an active area of research and development. Existing tuning tools explore the space of feasible solutions by repeatedly optimizing queries in the input workload for several candidate configurations. This general approach, while scalable, often results in tuning sessions waiting for results from the query optimizer over 90% of the time. In this paper we introduce a novel approach, called Configuration-Parametric Query Optimization, that drastically improves the performance of current tuning tools. By issuing a single optimization call per query, we are able to generate a compact representation of the optimization space that can then produce very efficiently execution plans for the input query under arbitrary configurations. Our experiments show that our technique speeds-up query optimization by 30x to over 450x with virtually no loss in quality, and effectively eliminates the optimization bottleneck in existing tuning tools. Our techniques open the door for new, more sophisticated optimization strategies by eliminating the main bottleneck of current tuning tools.