Large relations in node-partitioned data warehouses

Abstract

A cheap shared-nothing context can be used to provide significant speedup on large data warehouses, but partitioning and placement decisions are important in such systems as repartitioning requirements can result in much less-than-linear speedup. This problem can be minimized if query workload and schemas are inputs to placement decisions. In this paper we analyze the problem of handling large relations in a node partitioned data warehouse (NPDW) with a basic placement strategy that partitions facts horizontally and replicates dimensions, with the help of a cost model. Then we propose a strategy to improve performance and show both analytical and TPC-H results. © Springer-Verlag Berlin Heidelberg 2005.