AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
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
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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
Database tuning advisor for microsoft SQL server 2005: demo
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
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
Physical design refinement: the "merge-reduce" approach
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Physical design refinement: The ‘merge-reduce’ approach
ACM Transactions on Database Systems (TODS)
Towards workload shift detection and prediction for autonomic databases
Proceedings of the ACM first Ph.D. workshop in CIKM
Self-tuning database systems: a decade of progress
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Efficient use of the query optimizer for automated physical design
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Robustness in automatic physical database design
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
A critical look at the TAB benchmark for physical design tools
ACM SIGMOD Record
Configuration-parametric query optimization for physical design tuning
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Constrained physical design tuning
Proceedings of the VLDB Endowment
QueryScope: visualizing queries for repeatable database tuning
Proceedings of the VLDB Endowment
When is it time to rethink the aggregate configuration of your OLAP server?
Proceedings of the VLDB Endowment
Self-organizing tuple reconstruction in column-stores
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Constrained physical design tuning
The VLDB Journal — The International Journal on Very Large Data Bases
Injecting domain knowledge into a granular database engine: a position paper
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Benchmarking adaptive indexing
TPCTC'10 Proceedings of the Second TPC technology conference on Performance evaluation, measurement and characterization of complex systems
Stochastic database cracking: towards robust adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
NoDB: efficient query execution on raw data files
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Adaptive indexing in modern database kernels
Proceedings of the 15th International Conference on Extending Database Technology
Database system performance evaluation models: A survey
Performance Evaluation
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In recent years there has been considerable research on automating the physical design in database systems. Current techniques provide good recommendations, but are resource intensive. This makes DBAs somewhat conservative when deciding to launch a resource-intensive tuning session. In this paper, we introduce an alerter that helps determining when a physical design tool should be invoked. The alerter is a lightweight mechanism that provides guaranteed lower (and upper bounds) on the improvement that a DBA could expect by invoking a comprehensive physical design tool. Moreover, it produces an accompanying recommendation that serves as a "proof" for the lower bound. We show experimentally that the alerter handles large workloads with little overhead, and help judiciously decide on launching subsequent tuning sessions.