Efficiently Processing Query-Intensive Databases over a Non-Dedicated Local Network

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.