Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th 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
DB2 Advisor: An Optimizer Smart Enough to Recommend its own Indexes
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Index Selection for Databases: A Hardness Study and a Principled Heuristic Solution
IEEE Transactions on Knowledge and Data Engineering
Automatic physical database tuning: a relaxation-based approach
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Goals and benchmarks for autonomic configuration recommenders
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Recommending Materialized Views and Indexes with IBM DB2 Design Advisor
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
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
An Integer Linear Programming Approach to Database Design
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Identifying robust plans through plan diagram reduction
Proceedings of the VLDB Endowment
Automated physical designers: what you see is (not) what you get
DBTest '12 Proceedings of the Fifth International Workshop on Testing Database Systems
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There has recently been considerable research on physical design tuning algorithms. At the same time, there is only one published methodology to evaluate the quality of different, competing approaches: the TAB benchmark. In this paper we describe our experiences with TAB. We first report an experimental evaluation of TAB on our latest prototype for physical design tuning. We then identify certain weakness in the benchmark and briefly comment on alternatives to improve its usefulness.