A performance analysis of the gamma database machine
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Database Operations in a Cube-Connected Multicomputer System
IEEE Transactions on Computers
Hash-based join algorithms for multiprocessor computers with shared memory
Proceedings of the sixteenth international conference on Very large databases
Parallel database systems: the future of high performance database systems
Communications of the ACM
Using shared virtual memory for parallel join processing
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Interconnecting shared-everything systems for efficient parallel query processing
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
The Gamma Database Machine Project
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the Eighth International Conference on Data Engineering
Parallel Database Systems: the case for shared-something
Proceedings of the Ninth International Conference on Data Engineering
Parallel Database Systems: the case for shared-something
Proceedings of the Ninth International Conference on Data Engineering
A Taxonomy and Performance Model of Data Skew Effects in Parallel Joins
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Practical Skew Handling in Parallel Joins
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Benchmarking Database Systems A Systematic Approach
VLDB '83 Proceedings of the 9th International Conference on Very Large Data Bases
Four Types of Data Skew and Their Effect on Parallel Join Performance
Four Types of Data Skew and Their Effect on Parallel Join Performance
An Adaptive Parallel Distributive Join Algorithm on a Cluster of Workstations
The Journal of Supercomputing
Survey of Architectures of Parallel Database Systems
Programming and Computing Software
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Recently, a number of hybrid systems have been proposed to combine the advantages of shared nothing and shared everything concepts for computing relational join operations. Most of these proposed systems, however, presented a few analytical results and have produced limited or no implementations on actual multiprocessors. In this paper, we present a parallel join algorithm with load-balancing for a hybrid system that combines both shared-nothing and shared-everything architectures. We derive an analytical model for the join algorithm on this architecture and validate it using both hardware/software simulations and actual experimentations. We study the performance of the join on the hybrid system for a wide range of system parameter values. We conclude that the hybrid system outperforms both shared-nothing and shared-everything architectures.