Parallel OLAP query processing in database clusters with data replication

Abstract : We consider the problem of improving the performance of OLAP applications in a database cluster (DBC), which is a low cost and effective parallel solution for query processing. Current DBC solutions for OLAP query processing provide for intra-query parallelism only, at the cost of full replication of the database. In this paper, we proposemore efficient distributed database design alternatives which combine physical/virtual partitioning with partial replication.We also propose a new load balancing strategy that takes advantage of an adaptive virtual partitioning to redistribute the load to the replicas. Our experimental validation is based on the implementation of our solution on the SmaQSS DBC middleware prototype. Our experimental results using the TPC-H benchmark and a 32-node cluster show very good speedup.
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Distributed and Parallel Database (Weston, Conn.)s, 2009, 25 (1-2), pp.97-123. 〈10.1007/s10619-009-7037-8〉
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https://hal.inria.fr/inria-00473537
Contributeur : Patrick Valduriez <>
Soumis le : jeudi 15 avril 2010 - 15:24:12
Dernière modification le : jeudi 15 avril 2010 - 17:14:21

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Alexandre Lima, Camille Furtado, Patrick Valduriez, Marta Mattoso. Parallel OLAP query processing in database clusters with data replication. Distributed and Parallel Database (Weston, Conn.)s, 2009, 25 (1-2), pp.97-123. 〈10.1007/s10619-009-7037-8〉. 〈inria-00473537〉

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