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MapReduce: Processing Big Data

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The amount of data that we store and process has increased drastically over the past decade, and has forced us to turn from using individual machines to clusters. My talk will present a distributed programming model called MapReduce which allows batch processing of data on large clusters of commodity hardware, whilst hiding complexities such as fault tolerance and scheduling from the user. I will also briefly describe my Part II project to implement a higher level language over MapReduce.

This talk is part of the Churchill CompSci Talks series.

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