Adaptive hybrid partitioning for OLAP query processing in a database cluster

Authors:
Camille Furtado;Alexandre A. B. Lima;Esther Pacitti;Patrick Valduriez;Marta Mattoso
Affiliations:
Computer Science Department, COPPE, Federal University of Rio de Janeiro (UFRJ), P.O. Box 68511, 21941-972 Rio de Janeiro, Brazil.;School of Sciences and Technology, Unigranrio University, R. Prof. Jose de Souza Herdy, 1160, 25071-202, Duque de Caxias, Brazil.;INRIA and LINA, University of Nantes, 2 rue de la Houssiniere, BP 92208, 44322 Nantes Cedex 3, France.;INRIA and LINA, University of Nantes, 2 rue de la Houssiniere, BP 92208, 44322 Nantes Cedex 3, France.;Computer Science Department, COPPE, Federal University of Rio de Janeiro (UFRJ), P.O. Box 68511, 21941-972 Rio de Janeiro, Brazil
Venue:
International Journal of High Performance Computing and Networking
Year:
2008

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Abstract

We consider the use of a database cluster for high-performance support of Online Analytical Processing (OLAP) applications. OLAP intra-query parallelism can be obtained by partitioning the database tables across cluster nodes. We propose to combine physical and virtual partitioning into a partitioning scheme called Adaptive Hybrid Partitioning (AHP). AHP requires less disk space while allowing for load balancing. We developed a prototype for OLAP parallel query processing in database clusters using AHP. Our experiments on a 32-node database cluster using the TPC-H benchmark demonstrate linear and super-linear speedup. Thus, AHP can reduce significantly the execution time of typical OLAP queries.