Solving large combinatorial problems in logic programming
Journal of Logic Programming - Logic programming applications
Improved CLP scheduling with task intervals
Proceedings of the eleventh international conference on Logic programming
Research problems in data warehousing
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Materialized view maintenance and integrity constraint checking: trading space for time
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Materialized view selection and maintenance using multi-query optimization
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
View relevance driven materialized view selection in data warehousing environment
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
View selection using randomized search
Data & Knowledge Engineering
A formal perspective on the view selection problem
The VLDB Journal — The International Journal on Very Large Data Bases
Physical Database Design for Data Warehouses
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Selection of Views to Materialize in a Data Warehouse
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Selection of Views to Materialize Under a Maintenance Cost Constraint
ICDT '99 Proceedings of the 7th International Conference on Database Theory
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Algorithms for Materialized View Design in Data Warehousing Environment
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Genetic Algorithm for Materialized View Selection in Data Warehouse Environments
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Multiobjective genetic algorithms for materialized view selection in OLAP data warehouses
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Simulated annealing for materialized view selection in data warehousing environment
DBA'06 Proceedings of the 24th IASTED international conference on Database and applications
Parallel Simulated Annealing for Materialized View Selection in Data Warehousing Environments
ICA3PP '08 Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing
Towards materialized view selection for distributed databases
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Selection of materialized views: a cost-based approach
CAiSE'03 Proceedings of the 15th international conference on Advanced information systems engineering
An evolutionary approach to materialized views selection in a datawarehouse environment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Materialized view selection as constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A survey of view selection methods
ACM SIGMOD Record
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Using materialized views can highly speed up the query processing time. This paper deals with the view selection issue, which consists in finding a set of views to materialize that minimizes the expected cost of evaluating the query workload, given a limited amount of resource such as total view maintenance cost and/or storage space. However, the solution space is huge since it entails a large number of possible combinations of views. For this matter, we have designed a solution involving constraint programming, which has proven to be a powerful approach for modeling and solving combinatorial problems. The efficiency of our method is evaluated using workloads consisting of queries over the schema of the TPC-H benchmark. We show experimentally that our approach provides an improvement in the solution quality (i.e., the quality of the obtained set of materialized views) in term of cost saving compared to genetic algorithm in limited time. Furthermore, our approach scales well with the query workload size.