Order-preserving key transformations
ACM Transactions on Database Systems (TODS)
Database machines and database management
Database machines and database management
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Distributive join: a new algorithm for joining relations
ACM Transactions on Database Systems (TODS)
A database machine based on concatenated code words for very large databases
Computers for artificial intelligence processing
Parallel main memory database system
SAC '92 Proceedings of the 1992 ACM/SIGAPP Symposium on Applied computing: technological challenges of the 1990's
Join and Semijoin Algorithms for a Multiprocessor Database Machine
ACM Transactions on Database Systems (TODS)
Hash-Based and Index-Based Join Algorithms for Cube and Ring Connected Multicomputers
IEEE Transactions on Knowledge and Data Engineering
Future Trends in Data Base Systems
Proceedings of the Fourth International Conference on Data Engineering
Hashing Methods and Relational Algebra Operations
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
Parallel Control Techniques for Dedicated Relational Database Engines
Proceedings of the Third International Conference on Data Engineering
Parallel Distributive Join Algorithm on the Intel Paragon
The Journal of Supercomputing
An Adaptive Parallel Distributive Join Algorithm on a Cluster of Workstations
The Journal of Supercomputing
Distributed Mining of Maximal Frequent Itemsets on a Data Grid System
The Journal of Supercomputing
Parallel mining of association rules from text databases
The Journal of Supercomputing
Efficient mining of maximal frequent itemsets from databases on a cluster of workstations
Knowledge and Information Systems
Parallel mining of maximal sequential patterns using multiple samples
The Journal of Supercomputing
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This paper presents a parallel distributive join algorithm for cube-connected multiprocessors. The performance analysis shows that the proposed algorithm has an almost linear speedup over the sequential distributive join algorithm [12] as the number of processors increases, and its performance is comparable to that of the parallel hybrid-hash join algorithm [13]. A big advantage of the proposed algorithm over hash-based join algorithms is that it does not have the bucket overflow problem caused by nonuniform hashing of the smaller operand relation. Moreover, the proposed algorithm can easily support the nonequijoin operation, which is very hard to implement by using hash-based join algorithms.