High-Performance Query Processing of a Real-World OLAP Database with ParGRES
High Performance Computing for Computational Science - VECPAR 2008
Parallel OLAP query processing in database clusters with data replication
Distributed and Parallel Databases
Exploring graphics processing units as parallel coprocessors for online aggregation
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Quality of experience in distributed databases
Distributed and Parallel Databases
Resource allocation algorithm for a relational join operator in grid systems
Proceedings of the 16th International Database Engineering & Applications Sysmposium
A Provenance-based Adaptive Scheduling Heuristic for Parallel Scientific Workflows in Clouds
Journal of Grid Computing
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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. Copyright © 2008 John Wiley & Sons, Ltd.