Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
Randomized algorithms for optimizing large join queries
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Exploiting inter-operation parallelism in XPRS
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Optimization of parallel query execution plans in XPRS
Distributed and Parallel Databases - Selected papers from the first international conference on parallel and distributed information systems
Outerjoin optimization in multidatabase systems
DPDS '90 Proceedings of the second international symposium on Databases in parallel and distributed systems
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Query Optimization in a Heterogeneous DBMS
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Processing Queries Over Generalization Hierarchies in a Multidatabase System
VLDB '83 Proceedings of the 9th International Conference on Very Large Data Bases
Distributed Query Processing Strategies in Mermaid, A Frontend to Data Management Systems
Proceedings of the First International Conference on Data Engineering
Dynamic query optimization on a distributed object management platform
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Multidatabase Query Optimization
Distributed and Parallel Databases
An Optimal Cache for a Federated Database System
Journal of Intelligent Information Systems
Cost-based query scrambling for initial delays
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Query Optimization in Multidatabase Systems
Distributed and Parallel Databases
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
Query Optimization in Multidatabase Systems Considering Schema Conflicts
IEEE Transactions on Knowledge and Data Engineering
Introducing QoS to Electronic Commerce Applications
ISEC '01 Proceedings of the Second International Symposium on Topics in Electronic Commerce
Cost Models DO Matter: Providing Cost Information for Diverse Data Sources in a Federated System
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Developing Evolutionary Cost Models for Query Optimization in a Dynamic Multidatabase Environment
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
Knowledge and Information Systems
Evolutionary techniques for updating query cost models in a dynamic multidatabase environment
The VLDB Journal — The International Journal on Very Large Data Bases
Distributed and Parallel Databases
Tree balance and node allocation
IDEAS'97 Proceedings of the 1997 international conference on International database engineering and applications symposium
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Execution of multidatabase queries differs from that of traditional queries in that sort merge and hash joins are more often favored, as nested loop join requires repeated accesses to external data sources. As a consequence, left deep join trees obtained by traditional (e.g., System-R style) optimizers for multidatabase queries are often suboptimal, with respect to response time, due to the long delay for a sort merge (or hash) join node to produce its last result after the subordinate join node did. In this paper, we present an optimization strategy that first produces an optimal left deep join tree and then reduces the response time using simple tree transformations. This strategy has the advantages of guaranteed minimum total resource usage, improved response time, and low optimization overhead. We describe a class of basic transformations that is the cornerstone of our approach. Then we present algorithms that effectively apply basic transformations to balance a left deep join tree, and discuss how the technique can be incorporated into existing query optimizers.