Partition Strategy for Distributed Query Processing in Fast Local Networks
IEEE Transactions on Software Engineering
An adaptive data placement scheme for parallel database computer systems
Proceedings of the sixteenth international conference on Very large databases
Optimizing equijoin queries in distributed databases where relations are hash partitioned
ACM Transactions on Database Systems (TODS)
Parallel database systems: the future of high performance database systems
Communications of the ACM
Query processing in a system for distributed databases (SDD-1)
ACM Transactions on Database Systems (TODS)
Automating physical database design in a parallel database
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
A Hash Partition Strategy for Distributed Query Processing
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Efficient OLAP Query Processing in Distributed Data Warehouses
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
A Distributed Query Processing Strategy Using Placement Dependency
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
An Efficient Algorithm for Processing Distributed Queries Using Partition Dependency
ICPADS '00 Proceedings of the Seventh International Conference on Parallel and Distributed Systems
Hash-based Placement and Processing for Efficient Node Partitioned Query-Intensive Databases
ICPADS '04 Proceedings of the Parallel and Distributed Systems, Tenth International Conference
Multiprocessor hash-based join algorithms
VLDB '85 Proceedings of the 11th international conference on Very Large Data Bases - Volume 11
Model and procedure for performance and availability-wise parallel warehouses
Distributed and Parallel Databases
Load-balancing for WAN warehouses
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
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Commercial database systems must typically rely on fast hardware platforms and interconnects to deal efficiently with data in parallel. However, cheap computing power can be applied for flexibility and scalability in managing large data volumes if the right choices are made concerning data placement and processing. Our work concentrates on the use of cheap computing power in possibly slow, non-dedicated local networks to achieve a computing power over demanding query-intensive databases that would be unachievable without expensive specialized hardware and massively parallel systems. The Node Partitioned Data Management System (NPDM) works on computing nodes on non-dedicated local networks. In this paper we concentrate on query transformations required for efficient processing over a specialized query-intensive schema. The decision support benchmark TPC-H is used as a study case for the transformations and for experimental analysis.