Announcing Revolution R Enterprise 6.2

April 24, 2013

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

We are pleased to announce that Revolution R Enterprise Release 6.2 is available to new subscribers today. This new software release from Revolution Analytics includes a number of key new features:

  • Support for open source R 2.15.3, the latest stable release of R.  Since Release 2.14.2, the R Project has added 89 new features, 11 performance enhancements and 139 bug fixes.  Moreover, there are 137 CRAN packages whose latest version depends on R 2.15.3.
  • The new High-Speed Teradata Connector, which is based on Teradata Parallel Transporter. According to benchmark testing performed by the Teradata Center of Excellence, the High-Speed Connector is at least six times faster than the previously available ODBC connector, as shown in the chart below.


  • Stepwise Regression for Linear Models. Stepwise Regression is a method for automated selection of variables in a predictive model. For an excellent article about Stepwise Regression in action, read this post. 
  • The Parallel Random Number Generator provides an R interface to the parallel random number generators supplied with the Intel MKL libraries, enabling high quality parallel random numbers to be used in distributed computations performed by RevoScaleR’s rxExec function. This capability is a necessary foundation for randomized decision trees (trademarked by Breiman and Cutler as "Random Forests"), and is also useful for simulation and Monte Carlo analysis.
  • Revolution R Enterprise users sometimes want to "roll up" data from one level to another — for example, to summarize transaction facts at the customer level. The rxCube and rxSummary functions now provide options to write by-group counts or summary statistics directly to a high performance .xdf file for further analysis. Users also now have more control over the summary statistics that are reported.
  • Release 6.2 also includes some performance enhancements, including a fast fixed format text data source capability, as well as optimized memory utilization for sorts and merges.
  • For customers who use our RevoDeployR capability for enterprise deployment of analytics there are several enhancements, including priority scheduling for asynchronous jobs, the ability to execute external scripts, plus enhanced versioning and lifecycle management for repository-managed files and scripts.

Revolution R Enterprise is available to new customers today. If you are an existing subscriber you can expect to receive an email on Monday, April 29 with detailed instructions on how to download and install the new software. (If you don't receive your update notification, please contact the Support team.) If you'd like to learn more about the new features, you can find an overview in this press release, or you can join the webinar What's New in Revolution R Enterprise 6.2 on Wednesday, May 1. 

To leave a comment for the author, please follow the link and comment on their blog: Revolutions. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Mango solutions

plotly webpage

dominolab webpage

Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training




CRC R books series

Six Sigma Online Training

Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)