Parallel query processing for OLAP in grids

摘要

OLAP query processing is critical for enterprise grids. Capitalizing on our experience with the ParGRES database cluster, we propose a middleware solution, GParGRES, which exploits database replication and inter- and intra-query parallelism to efficiently support OLAP queries in a grid. GParGRES is designed as a wrapper that enables the use of ParGRES in PC clusters of a grid (in our case, Grid5000). Our approach has two levels of query splitting: grid-level splitting, implemented by GParGRES, and node-level splitting, implemented by ParGRES. GParGRES has been partially implemented as database grid services compatible with existing grid solutions such as the open grid service architecture and the Web services resource framework. We give preliminary experimental results obtained with two clusters of Grid5000 using queries of the TPC-H Benchmark. The results show linear or almost linear speedup in query execution, as more nodes are added in all tested configurations.