MCJoin: a memory-constrained join for column-store main-memory databases

  • Authors:

  • Steven Keith Begley;Zhen He;Yi-Ping Phoebe Chen

  • Affiliations:

  • La Trobe University, Melbourne, Victoria, Australia;La Trobe University, Melbourne, Victoria, Australia;La Trobe University, Melbourne, Victoria, Australia

  • Venue:
  • SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
  • Year:
  • 2012

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Abstract

There exists a need for high performance, read-only main-memory database systems for OLAP-style application scenarios. Most of the existing works in this area are centered around the domain of column-store databases, which are particularly well suited to OLAP-style scenarios and have been shown to overcome the memory bottleneck issues that have been found to hinder the more traditional row-store database systems. One of the main database operations these systems are focused on optimizing is the JOIN operation. However, all these existing systems use join algorithms that are designed with the unrealistic assumption that there is unlimited temporary memory available to perform the join. In contrast, we propose a Memory Constrained Join algorithm (MCJoin) which is both high performing and also performs all of its operations within a tight given memory constraint. Extensive experimental results show that MCJoin outperforms a naive memory constrained version of the state-of-the-art Radix-Clustered Hash Join algorithm in all of the situations tested, with margins of up to almost 500%.