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One of the common discussions that I've had with several colleagues when we're making use of some of the higher order functions that can be applied on collections is whether to use the LINQ style syntax or to chain the different methods together. I tend to prefer the latter approach although when asked the question after my talk at Developer Developer Developer I didn't really have a good answer other than to suggest that it seemed to just be a personal preference thing. Damian Marshall suggested that he preferred the method chaining approach because it more clearly describes the idea of passing a collection through a pipeline where we can apply different operations to that collection.

In this demo we showcase efforts in MSR to collaborate with external researchers to explore the application of new technologies, specifically Dryad and DryadLINQ, to big data research problems in science. We also highlight our efforts to provide software and services to academics across the world, through the release of Dryad and DryadLINQ free of charge to the research community, along with associated programming guides, user documentation, and code libraries. Dryad is a general-purpose distributed computing engine, more flexible than MapReduce or Hadoop!, that was designed to simplify the task of implementing distributed applications on clusters of Windows computers. DryadLINQ is an abstraction layer which simplifies the process of implementing Dryad-based applications. Microsoft Research is acutely aware of the ubiquity of big data and the challenges this presents. We are offering researchers the tools, resources and collaboration to explore this new area.