Predicting replicated database scalability from standalone database profiling

  • Authors:
  • Sameh Elnikety;Steven Dropsho;Emmanuel Cecchet;Willy Zwaenepoel

  • Affiliations:
  • Microsoft Research, Cambridge, United Kingdom;Google Inc., Zurich, Switzerland;University of Massachusetts, Amherst, USA;EPFL, Lausanne, Switzerland

  • Venue:
  • Proceedings of the 4th ACM European conference on Computer systems
  • Year:
  • 2009

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Abstract

This paper develops analytical models to predict through-put and response time of a replicated database using meas-urements of the workload on a standalone database. These models allow workload scalability to be estimated before the replicated system is deployed, making the technique useful for capacity planning and dynamic service provi-sioning. The models capture the scalability limits stemming from update propagation and aborts for both multi-master and single-master replicated databases that support snap-shot isolation. We validate the models by comparing their throughput and response time predictions against experimental meas-urements on two existing prototype replicated database systems running the TPC-W and RUBiS workloads. We show that the model predictions match the experimental results for both the multi-master and single-master designs and for the various workload mixes of TPC-W and RUBiS.