Join processing in database systems with large main memories
ACM Transactions on Database Systems (TODS)
R* optimizer validation and performance evaluation for local queries
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
Query optimization by simulated annealing
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
Optimization of large join queries
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Dynamic query evaluation plans
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Integration of buffer management and query optimization in relational database environment
VLDB '89 Proceedings of the 15th international conference on Very large data bases
Randomized algorithms for optimizing large join queries
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Flexible buffer allocation based on marginal gains
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
Randomized algorithms for query optimization
Randomized algorithms for query optimization
Optimization of dynamic query evaluation plans
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Simulated annealing and combinatorial optimization
DAC '86 Proceedings of the 23rd ACM/IEEE Design Automation Conference
Optimization of parallel query execution plans in XPRS
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
VLDB '88 Proceedings of the 14th International Conference on Very Large Data Bases
Predictive Load Control for Flexible Buffer Allocation
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Performance Analysis of Database Systems
Performance Evaluation: Origins and Directions
Toward a progress indicator for database queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Increasing the Accuracy and Coverage of SQL Progress Indicators
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Query optimization in distributed networks of autonomous database systems
ACM Transactions on Database Systems (TODS)
Parametric query optimization for linear and piecewise linear cost functions
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Foundations and Trends in Databases
Dynamic plan generation for parameterized queries
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Variance aware optimization of parameterized queries
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Query trading in digital libraries
DELOS'04 Proceedings of the 6th Thematic conference on Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures
The QOL approach for optimizing distributed queries without complete knowledge
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Distributed Adaptive Windowed Stream Join Processing
International Journal of Distributed Systems and Technologies
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In most database systems, the values of many important run-time parameters of the system, the data, or the query are unknown at query optimization time. Parametric query optimization attempts to identify at compile time several execution plans, each one of which is optimal for a subset of all possible values of the run-time parameters. The goal is that at run time, when the actual parameter values are known, the appropriate plan should be identifiable with essentially no overhead. We present a general formulation of this problem and study it primarily for the buffer size parameter. We adopt randomized algorithms as the main approach to this style of optimization and enhance them with a sideways information passing feature that increases their effectiveness in the new task. Experimental results of these enhanced algorithms show that they optimize queries for large numbers of buffer sizes in the same time needed by their conventional versions for a single buffer size, without much sacrifice in the output quality and with essentially zero run-time overhead.