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Adaptive Virtual Partitioning for OLAP Query Processing in a Database Cluster

Abstract : OLAP queries are typically heavy-weight and ad-hoc thus requiring high storage capacity and processing power. In this paper, we address this problem using a database cluster which we see as a cost-effective alternative to a tightly-coupled multiprocessor. We propose a solution to efficient OLAP query processing using a simple data parallel processing technique called adaptive virtual partitioning which dynamically tunes partition sizes, without requiring any knowledge about the database and the DBMS. To validate our solution, we implemented a Java prototype on a 32 node cluster system and ran experiments with typical queries of the TPC-H benchmark. The results show that our solution yields linear, and sometimes superlinear, speedup. In many cases, it outperforms traditional virtual partitioning by factors superior to 10.
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Submitted on : Tuesday, April 3, 2012 - 3:44:29 PM
Last modification on : Wednesday, April 27, 2022 - 3:49:38 AM


  • HAL Id : hal-00684957, version 1



Alexandre A. B. Lima, Marta Mattoso, Patrick Valduriez. Adaptive Virtual Partitioning for OLAP Query Processing in a Database Cluster. SBBD 2004, Oct 2004, Brasilia, Brazil. pp.92-105. ⟨hal-00684957⟩



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