Statistical profile estimation in database systems
ACM Computing Surveys (CSUR)
Logic-based approach to semantic query optimization
ACM Transactions on Database Systems (TODS)
Practical selectivity estimation through adaptive sampling
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Deriving production rules for constraint maintenance
Proceedings of the sixteenth international conference on Very large databases
Optimal histograms for limiting worst-case error propagation in the size of join results
ACM Transactions on Database Systems (TODS)
Automatic generation of production rules for integrity maintenance
ACM Transactions on Database Systems (TODS)
Algorithms for inferring functional dependencies from relations
Data & Knowledge Engineering
Fundamental techniques for order optimization
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Improved histograms for selectivity estimation of range predicates
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Using inductive learning to generate rules for semantic query optimization
Advances in knowledge discovery and data mining
Integrity constraints: semantics and applications
Logics for databases and information systems
Automatic Knowledge Acquisition and Maintenance for Semantic Query Optimization
IEEE Transactions on Knowledge and Data Engineering
Learning Transformation Rules for Semantic Query Optimization: A Data-Driven Approach
IEEE Transactions on Knowledge and Data Engineering
A Feasibility and Performance Study of Dependency Inference
Proceedings of the Fifth International Conference on Data Engineering
Using Type Inference and Induced Rules to Provide Intensional Answers
Proceedings of the Seventh International Conference on Data Engineering
Exploiting Uniqueness in Query Optimization
Proceedings of the Tenth International Conference on Data Engineering
Efficient Discovery of Functional and Approximate Dependencies Using Partitions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Discovery and Application of Check Constraints in DB2
Proceedings of the 17th International Conference on Data Engineering
Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Universality of Serial Histograms
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Sampling-Based Estimation of the Number of Distinct Values of an Attribute
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An Approach to Deriving Object Hierarchies from Database Schema and Contents
ISMIS '91 Proceedings of the 6th International Symposium on Methodologies for Intelligent Systems
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Query Optimization via Empty Joins
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Translating advanced integrity checking technology to SQL
Database integrity
Using Constraints to Describe Source Contents in Data Integration Systems
IEEE Intelligent Systems
Journal of Intelligent Information Systems
On Simplification of Database Integrity Constraints
Fundamenta Informaticae
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Correlation maps: a compressed access method for exploiting soft functional dependencies
Proceedings of the VLDB Endowment
Toward a verified relational database management system
Proceedings of the 37th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Query optimization in large databases using association rule mining
Proceedings of the 48th Annual Southeast Regional Conference
On Simplification of Database Integrity Constraints
Fundamenta Informaticae
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Query optimizers nowadays draw upon many sources of information about the database to optimize queries. They employ runtime statistics in cost-based estimation of query plans. They employ integrity constraints in the query rewrite process. Primary and foreign key constraints have long played a role in the optimizer, both for rewrite opportunities and for providing more accurate cost predictions. More recently, other types of integrity constraints are being exploited by optimizers in commercial systems, for which certain semantic query optimization techniques have now been implemented.These new optimization strategies that exploit constraints hold the promise for good improvement. Their weakness, however, is that often the “constraints” that would be useful for optimization for a given database and workload are not explicitly available for the optimizer. Data mining tools can find such “constraints” that are true of the database, but then there is the question of how this information can be kept by the database system, and how to make this information available to, and effectively usable by, the optimizer.We present our work on soft constraints in DB2. A soft constraint is a syntactic statement equivalent to an integrity constraint declaration. A soft constraint is not really a constraint, per se, since future updates may undermine it. While a soft constraint is valid, however, it can be used by the optimizer in the same way integrity constraints are. We present two forms of soft constraint: absolute and statistical. An absolute soft constraint is consistent with respect to the current state of the database, just in the same way an integrity constraint must be. They can be used in rewrite, as well as in cost estimation. A statistical soft constraint differs in that it may have some degree of violation with respect to the state of the database. Thus, statistical soft constraints cannot be used in rewrite, but they can still be used in cost estimation.We are working long-term on absolute soft constraints. We discuss the issues involved in implementing a facility for absolute soft constraints in a database system (and in DB2), and the strategies that we are researching. The current DB2 optimizer is more amenable to adding facilities for statistical soft constraints. In the short-term, we have been implementing pathways in the optimizer for statistical soft constraints. We discuss this implementation.