| By David Smith |
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| December 4, 2012 04:45 AM EST |
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Last month's release of Revolution R Enterprise 6.1 added the capability to fit decision and regression trees on large data sets (using a new parallel external memory algorithm included in the RevoScaleR package).
It also introduced the possibility of applying this and the other big-data statistical methods of RevoScaleR to data files distributed in in Hadoop's HDFS file system*, using the Hadoop nodes themselves as the compute engine (with Revolution R Enterprise installed).
Revolution Analytics' VP of Development Sue Ranney explained how this works in a recent webinar.
I've embedded the slides below, and you can also watch the webinar recording on YouTube.
[*] Or to use the department of redundancy department-approved acronym, HHFDSFS
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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