Optimization of join operations in horizontally partitioned database systems
ACM Transactions on Database Systems (TODS)
NON-VON's performance on certain database benchmarks
IEEE Transactions on Software Engineering
An execution model for exploiting AND-parallelism in logic programs
New Generation Computing
Parallel algorithms for the execution of relational database operations
ACM Transactions on Database Systems (TODS)
Logic and Databases: A Deductive Approach
ACM Computing Surveys (CSUR)
Handbook of AI
Systolic (VLSI) arrays for relational database operations
SIGMOD '80 Proceedings of the 1980 ACM SIGMOD international conference on Management of data
Concurrency Control of Bulk Access Transactions on Shared Nothing Parallel Database Machines
Proceedings of the Sixth International Conference on Data Engineering
Chained Declustering: A New Availability Strategy for Multiprocessor Database Machines
Proceedings of the Sixth International Conference on Data Engineering
Proceedings of the Seventh International Conference on Data Engineering
Implementing Relational Database Operations in a Cube-Connected Multicomputer System
Proceedings of the Third International Conference on Data Engineering
An Adaptive Data Placement Scheme for Parallel Database Computer Systems
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
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
CMD: A Multidimensional Declustering Method for Parallel Data Systems
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
DIRECT - a multiprocessor organization for supporting relational data base management systems
ISCA '78 Proceedings of the 5th annual symposium on Computer architecture
Logic, parallelism and semantic networks: the binary predicate execution model
Logic, parallelism and semantic networks: the binary predicate execution model
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Taking advantage of the structure of logical representations, we report an algorithm that evaluates conjunctive queries in a massively parallel environment under an object-based representation for deductive databases. By distributing objects in a database, we show that parallel evaluation of a query can be achieved in a cooperative way so that the conventional tuple-by-tuple, operation-by-operation evaluation strategy can be replaced by a global, parallel matching approach. With the proposed scheme, all conjuncts of a given query can be examined at the same time, which enables us to eliminate the need of any temporary relation. On the other hand, compared with the interpretive method, we show that any data dependency imposed by shared variables is no longer a major problem in achieving AND-parallelism by the proposed scheme.