Automated data partitioning for independent distributed transactions

  • Authors:
  • Alexandru Turcu;Roberto Palmieri;Binoy Ravindran

  • Affiliations:
  • Virginia Tech;Virginia Tech;Virginia Tech

  • Venue:
  • Proceedings Demo & Poster Track of ACM/IFIP/USENIX International Middleware Conference
  • Year:
  • 2013

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Abstract

Granola is a recently proposed transactional execution protocol that employs a novel timestamp-based synchronization for executing certain classes of distributed transactions. However, Granola has two critical drawbacks. A) It requires users to manually define a data partitioning scheme and choose the appropriate transaction primitive. We seek to automate this process. We employ an existing graph-based algorithm (Schism) for partitioning transactional data, and extend it to be compatible with the additional insights and requirements of the Granola protocol. B) Granola requires a-priori knowledge of data location for routing transactions to repositories. We develop a routing mechanism based on machine learning to overcome this issue.