Apuama: Combining Intra-query and Inter-query Parallelism in a Database Cluster

  • Bernardo Miranda
  • Alexandre A. B. Lima
  • Patrick Valduriez
  • Marta Mattoso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4254)


Database clusters provide a cost-effective solutionn for high performance query processing. By using either inter- or intra-query parallelism on replicated data, they can accelerate individual queries and increase throughput. However, there is no database cluster that combines inter- and intra-query parallelism while supporting intensive update transactions. C-JDBC is a successful database cluster that offers inter-query parallelism and controls database replica consistency but cannot accelerate individual heavy-weight queries, typical of OLAP. In this paper, we propose the Apuama Engine, which adds intra-query parallelism to C-JDBC. The result is an open-source package that supports both OLTP and OLAP applications. We validated Apuama on a 32-node cluster running OLAP queries of the TPC-H benchmark on top of PostgreSQL. Our tests show that the Apuama Engine yields super-linear speedup and scale-up in read-only environments. Furthermore, it yields excellent performance under data update operations.


Query Processing Query Execution Query Execution Time Database Cluster Node Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bernardo Miranda
    • 1
  • Alexandre A. B. Lima
    • 1
    • 3
  • Patrick Valduriez
    • 2
  • Marta Mattoso
    • 1
  1. 1.Computer Science Department, COPPEFederal University of Rio de Janeiro 
  2. 2.Atlas Group, INRIA and LINAUniversity of NantesFrance
  3. 3.School of Engineering and Computer ScienceUniversity of Grande RioBrazil

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