ACM Transactions on Database Systems (TODS)
An incremental access method for ViewCache: concept, algorithms, and cost analysis
ACM Transactions on Database Systems (TODS)
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
The Art of Computer Programming, 2nd Ed. (Addison-Wesley Series in Computer Science and Information
Logic and Data Bases
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Common expression analysis in database applications
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
Using Common Subexpressions to Optimize Multiple Queries
Proceedings of the Fourth International Conference on Data Engineering
Optimization of Nonrecursive Queries
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Anatomy of a Mudular Multiple Query Optimizer
VLDB '88 Proceedings of the 14th 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
Solving Dial-a-Ride Problems with a Low-Level Hybridization of Ants and Constraint Programming
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
Decomposition approach to solve dial-a-ride problems using ant computing and constraint programming
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
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In this research, we address the query clustering problem which involves determining globally optimal execution strategies for a set of queries. The need to process a set of queries together often arises in deductive database systems, scientific database systems, large bibliographic retrieval systems and several other database applications. We address the optimization problem from the perspective of overlaps in data requirements, and model the batched operations using a set-partitioning approach In this model, we first consider the case of m queries each involving a two-way join operation. We develop a recursive methodology to determine all the processing strategies in this case. Next, we establish certain dominance properties among the strategies, and develop exact as well as heuristic algorithms for selecting an appropriate strategy. We extend this analysis to a clustering approach, and outline a framework for optimizing multiway joins. The results show that the proposed approach is viable and efficient, and can easily be incorporated into the query processing component of most database systems.