Optimizing joins between two partitioned relations in distributed databases
Journal of Parallel and Distributed Computing
Theory of linear and integer programming
Theory of linear and integer programming
Optimizing Join Queries in Distributed Databases
IEEE Transactions on Software Engineering
Optimizing equijoin queries in distributed databases where relations are hash partitioned
ACM Transactions on Database Systems (TODS)
Using Semi-Joins to Solve Relational Queries
Journal of the ACM (JACM)
Propagating Updates in a Highly Replicated Database
Proceedings of the Sixth International Conference on Data Engineering
Update Propagation in Distributed Memory Hierarchy
Proceedings of the Sixth International Conference on Data Engineering
The complexity of processing tree queries in distributed databases
SPDP '90 Proceedings of the 1990 IEEE Second Symposium on Parallel and Distributed Processing
Incorporating processor costs in optimizing the distributed execution of join queries
Mathematical and Computer Modelling: An International Journal
Evaluating multiple join queries in a distributed database system
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
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The problem of applying update operations to relational tables under the supervision of a distributed database management system is considered. A model describing the minimal cost propagation strategy of an update request to all copies of the relevant relation is offered, and takes the form of an integer linear program. A user request is issued at a given site in the network, specifying an amendment to the information comprising some particular logical data set, or relation. Replication of data admits the possibility of relations being duplicated, with several distinct copies disseminated amongst various processor sites; synchronization of replicated information to preserve its consistency commands that the alteration be applied uniformly to all. The update request must therefore be communicated to each site possessing a copy of the relation to which it refers. This task demands the utilization of limited system resources; data transmission channels convey the update signal between sites, and processors apply the operation to stored copies of the particular relation to be changed. The ultimate goal is therefore to choose from all possible update propagation strategies one that achieves the smallest total cost. The formulation initially attained by considering the role of an isolated processor in a valid strategy contains some constraints that are nonlinear. However, by introducing new decision variables and reconsidering the offending inequalities, the model can be transformed to realize an optimization program entirely linear in structure.