Abstract
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.
Work partially funded by CNPq, Finep, Capes, Cofecub and ACI “Massive Data” in France.
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Miranda, B., Lima, A.A.B., Valduriez, P., Mattoso, M. (2006). Apuama: Combining Intra-query and Inter-query Parallelism in a Database Cluster. In: Grust, T., et al. Current Trends in Database Technology – EDBT 2006. EDBT 2006. Lecture Notes in Computer Science, vol 4254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11896548_49
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DOI: https://doi.org/10.1007/11896548_49
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