Efficient mid-query re-optimization of sub-optimal query execution plans
SIGMOD '98 Proceedings of the 1998 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
Least expected cost query optimization: what can we expect?
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Dynamic Query Optimization in Rdb/VMS
Proceedings of the Ninth International Conference on Data Engineering
LEO - DB2's LEarning Optimizer
Proceedings of the 27th 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
Parametric query optimization for linear and piecewise linear cost functions
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
AniPQO: almost non-intrusive parametric query optimization for nonlinear cost functions
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
On the production of anorexic plan diagrams
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Foundations and Trends in Databases
On the stability of plan costs and the costs of plan stability
Proceedings of the VLDB Endowment
Query optimization in microsoft SQL server PDW
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Testing the accuracy of query optimizers
DBTest '12 Proceedings of the Fifth International Workshop on Testing Database Systems
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Modern database systems employ a query optimizer module to automatically identify the most efficient strategies for executing the declarative SQL queries submitted by users. The efficiency of these strategies, called "plans", is measured in terms of "costs" that are indicative of query response times. Optimization is a mandatory exercise since the difference between the costs of the best execution plan, and a random choice, could be in orders of magnitude. The role of query optimizers has become especially critical during this decade due to the high degree of processing complexity characterizing current data warehousing and mining applications, as exemplified by the TPC-H and TPC-DS decision support benchmarks [20, 21].