Dynamic query evaluation plans
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Optimization of dynamic query evaluation plans
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Least expected cost query optimization: an exercise in utility
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Design and Analysis of Parametric Query Optimization Algorithms
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Parametric query optimization for linear and piecewise linear cost functions
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Plan selection based on query clustering
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Optimizing nested queries with parameter sort orders
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Analyzing plan diagrams of database query optimizers
VLDB '05 Proceedings of the 31st international conference on Very large data bases
On the production of anorexic plan diagrams
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
Foundations and Trends in Databases
Identifying robust plans through plan diagram reduction
Proceedings of the VLDB Endowment
Efficiently approximating query optimizer plan diagrams
Proceedings of the VLDB Endowment
On the stability of plan costs and the costs of plan stability
Proceedings of the VLDB Endowment
The Picasso database query optimizer visualizer
Proceedings of the VLDB Endowment
The QOL approach for optimizing distributed queries without complete knowledge
Proceedings of the 16th International Database Engineering & Applications Sysmposium
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The cost of a query plan depends on many parameters, such as predicate selectivities and available memory, whose values may not be known at optimization time. Parametric query optimization (PQO) optimizes a query into a number of candidate plans, each optimal for some region of the parameter space. We propose a heuristic solution for the PQO problem for the case when the cost functions may be nonlinear in the given parameters. This solution is minimally intrusive in the sense that an existing query optimizer can be used with minor modifications. We have implemented the heuristic and the results of the tests on the TPCD benchmark indicate that the heuristic is very effective. The minimal intrusiveness, generality in terms of cost functions and number of parameters and good performance (up to 4 parameters) indicate that our solution is of significant practical importance.