Logic-based approach to semantic query optimization
ACM Transactions on Database Systems (TODS)
A method for automatic rule derivation to support semantic query optimization
ACM Transactions on Database Systems (TODS)
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Logic and Databases: A Deductive Approach
ACM Computing Surveys (CSUR)
Index selection in a self-adaptive data base management system
SIGMOD '76 Proceedings of the 1976 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Efficient Evaluation of Queries with Mining Predicates
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Query optimization by semantic reasoning
Query optimization by semantic reasoning
Index Selection for Databases: A Hardness Study and a Principled Heuristic Solution
IEEE Transactions on Knowledge and Data Engineering
ACM Computing Surveys (CSUR)
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
Data mining-based materialized view and index selection in data warehouses
Journal of Intelligent Information Systems
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This paper presents a framework to mine query predicates from query patterns in order to produce candidate attributes from query predicates for index generation and access path selection. Query predicates are query conditions or constraints involving tables to be accessed and values of attributes or columns to be retrieved in the format of the tuples or objects. Access path and its auxiliary data structures determine how data tuples and objects to be retrieved efficiently, in turn, the performance of data query processing. This framework mines set of query patterns, analyzes the association of attributes, and provides heuristics for access path generation and selection.