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In-Hadoop R-based Analytics coming to Cloudera

Revolution Analytics has teamed up with Cloudera to bring the scalable data manipulation and statistical modeling algorithms of Revolution R Enteprise to the massively-parallel computing environments of CDH3 and CDH4 Hadoop clusters. As ZDNet reports: Specifically, the upcoming version 7.0 of the Revolution R Enterpise distribution and its ScaleR algorithms will run inside CDH3 and CDH4, eliminating the need to move data out of CDH and into the conventional storage that R code would otherwise require.  Avoiding such data movement will allow predictive analytics functionality implemented in R to execute more immediately and quickly, allowing for more real-time analysis and generally better performance even in non-real-time applications. With the release of Revolution R Enterprise 7 in late 2013, users of Cloudera's Distribution for Apache Hadoop will have the ability to quickly and easily invoke R-powered predictive models, and push beyond simple summaries, queries and data visualization to produce game-changing insights from data managed by the Hadoop environment. Data scientists will use the R language to create powerful predictive models like logistic regression, decision trees, and clustering models in data in Hadoop, all without having to learn to write MapReduce in Java, Python or other languages. You can learn more about this forthcoming integration in today's live webinar, High Performance Predictive Analytics in R and Hadoop, or in the press release linked below. Revolution Analytics press releases: Revolution Analytics to Support In-Hadoop Big Data Predictive Analytics for Cloudera

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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

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