Network-Aware Join Processing in Global-Scale Database Federations

  • Authors:

  • Xiaodan Wang;Randal Burns;Andreas Terzis;Amol Deshpande

  • Affiliations:

  • Johns Hopkins University, USA. xwang@cs.jhu.edu;Johns Hopkins University, USA. randal@cs.jhu.edu;Johns Hopkins University, USA. terzis@cs.jhu.edu;University of Maryland, USA. amol@cs.umd.edu

  • Venue:
  • ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
  • Year:
  • 2008

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Abstract

We introduce join scheduling algorithms that employ a balanced network utilization metric to optimize the use of all network paths in a global-scale database federation. This metric allows algorithms to exploit excess capacity in the network, while avoiding narrow, long-haul paths. We give a two-approximate, polynomial-time algorithm for serial (left-deep) join schedules. We also present extensions to this algorithm that explore parallel schedules, reduce resource usage, and define trade-offs between computation and network utilization. We evaluate these techniques within the SkyQuery federation of Astronomy databases using spatial-join queries submitted by SkyQuery's users. Experiments show that our algorithms realize near-optimal network utilization with minor computational overhead.