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DryadLINQ: distributed data-parallel computing using a high-level language

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If you have a question about this talk, please contact Eiko Yoneki.

DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments such as SQL , MapReduce, and Dryad in two ways: by adopting an expressive data model of strongly typed .NET objects; and by supporting general-purpose imperative and declarative operations on datasets within a traditional high-level programming language.

I will outline the design of DryadLINQ, including an introduction to the LINQ programming model, and discuss the tradeoffs in both programming models and implementation strategies that we made with DryadLINQ, compared with parallel SQL and MapReduce.

Bio: Michael Isard received his DPhil, in computer vision, from Oxford University in 1998. In 1999 he started work at the Compaq Systems Research Center, and since 2002 has worked for Microsoft Research at their Silicon Valley Campus. He spent much of 2003 to 2005 working closely with the MSN Search product group on the design and implementation of their V1 search engine. His current research interests include large-scale distributed systems and programming models for parallel and distributed computing.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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