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Open Source Authors: David Smith, Liz McMillan, Elizabeth White, Denise Dubie, Jeremy Geelan

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Big Data Analytics with R and Hadoop

The open-source RHadoop project makes it easier to extract data from Hadoop for analysis with R, and to run R within the nodes of the Hadoop cluster -- essentially, to transform Hadoop into a massively-parallel statistical computing cluster based on R. In yesterday's webinar (the replay of which is embedded below), Data scientist and RHadoop project lead Antonio Piccolboni introduced Hadoop and explained how to write map-reduce statements in the R language to drive the Hadoop cluster.   You can download Antonio's slides and and the replay from the webinar at the link below. Revolution Analytics webinars: R + Hadoop = Big Data Analytics

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More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid