Apuama: Combining intra-query and inter-query parallelism in a database cluster

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. © Springer-Verlag Berlin Heidelberg 2006.