A parallel general-purpose synthetic data generator

  • Authors:
  • Joseph E. Hoag;Craig W. Thompson

  • Affiliations:
  • University of Arkansas;University of Arkansas

  • Venue:
  • ACM SIGMOD Record
  • Year:
  • 2007

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Abstract

PSDG is a parallel synthetic data generator designed to generate "industrial sized" data sets quickly using cluster computing. PSDG depends on SDDL, a synthetic data description language that provides flexibility in the types of data we can generate.