Revolutions

R 2.15.0 "Easter Beagle" is released

The R core group today announced the availability of R 2.15.0, codenamed "Easter Beagle". If you build R yourself, the new source distribution (including packages for Debian Linux) is available now, and binaries for Windows, MacOS and Linux will be available from your local CRAN mirror over the next couple of days. (As of this writing, Windows binaries are already propagating.)

This release includes many new features, but highlights include:

• Parallelized versions of the mapply and Map functions
• Load-balancing support for parallel programming on clusters 
• Improved performance when serializing R objects to/from disk (which will in turn improve performance of R integrated with systems like Hadoop)
• High-performance functions for calculating row/column statistics on matrix and data frame objects
• Support for simulating random matrixes using the Wishart distribution

R 2.15.0 represents the first release in the R Project's new annual release cycle. R 2.16 is expected about the same time next year, with patch updates in the interim as required. Many thanks go to the R core team for their hard work and dedication continuing to improve and advance the state of the R engine, core packages, and build infrastructure.

R-announce mailing list: R 2.15.0 is released

R turns 12; R 2.14.2 is out

As promised by the R Core Group, R 2.14.2 is out. This is the final patchlevel of the R 2.14.x series (R 2.15.0 is due on March 30), and so R 2.14.2 will be the R engine for the next release of Revolution R Enterprise in a couple of months. 

Today also marks the 12th anniversary since R 1.0.0 was released on February 29, 2000. If course, R had been in development for several years before then, as you can see in this abbreviated history of R: 

• 1993: Research project in Auckland, NZ by Ross Ihaka and Robert Gentleman
• 1995: Released as open-source software (Generally compatible with the 'S' language)
• 1997: R core group formed
• 2000: (February 29) R 1.0.0 released
• 2004: First international user conference in Vienna
• 2012: (February 29) R 2.14.2 released

But if you count 1.0.0 as "Day 0", then today marks R's twelfth birthday (and the third February 29 since Day 0). You can download the latest version of R from the CRAN network as the mirrors propagate.

R-announce mailing list: R 2.14.2 is released + R anniversary

R 2.14.2 and R 2.15.0 coming soon

The R core group has announced release dates for the next two versions of R (with their code names):

2.14.2 "Gift-Getting Season" on Feb 29 (3rd anniversary of R-1.0.0!)
2.15.0 "Easter Beagle" on Mar 30

R 1.0.0 was released twelve years ago on February 29, 2000; this will be the third February 29 since then. (Hence Peter Dalgaard's little joke above.)

R-announce mailing list: Release plans for 2.14.2 and 2.15.0

Revolution R update adds Red Hat 6 support

The Dev Team at Revolution Analytics recently released an update to the Revolution R 5 family. Version 5.0.1 adds compatibility with Red Hat Enterprise Linux 6 for all editions (Community, Academic and Enterprise). This expands the platform support to Red Hat 5, Red Hat 6 and Microsoft Windows. 

For Revolution R Enterprise customers and users of the free Academic edition, this update also addresses some minor issues with big-data statistics and distributed computing:

• The Revolution R Enterprise shortcut can now be pinned to your Start menu.
• K-means clustering (rxKmeans) with missing values was sometimes incorrectly reporting the number of valid and missing observations
• rxMerge was erroneously returning FALSE if the outfile argument had no .xdf extension, even though the merge was successful. Also, the use of the newVarNames argument sometimes led to the renaming of additional variables.
• rxSetVarInfo now returns an RxXdfData object if the inputdata is an .xdf file. If the input data is a data frame, a data frame is returned.
• rxFactors now returns an RxXdfData object if an output file is specified. Otherwise, a data frame is returned.
• The doRSR package now provides correct results when registered with a distributed compute context with wait=FALSE.
• RxHpcServer now behaves correctly if the names of all the compute nodes in a cluster are alphabetically after “Local Client.”
• The RevoDeployR web services framework has been updated (Academic and Server editions)

If you've previously downloaded Revolution R Community or the free Academic edition, you can download the latest version via our download page. If you're a current Revolution R Enterprise subscriber, you should already have an email with update instructions (if not, please contact Revolution Analytics support).

New to Revolution R? You can find information about our commercial-grade distribution of R at the link below.

Revolution Analytics: Revolution R Enterprise

Introducing Dave Rich, Revolution Analytics' new CEO

It's with great pleasure that we welcome Dave Rich as Revolution Analytics' new CEO today. Dave comes to us from Accenture Analytics, where he was Global Managing Director. Dave's extensive experience integrating analytics platforms with day-to-day operations at Fortune 500 enterprises will be invaluable as we apply analytics based on Revolution R Enterprise to mission-critical business processes.

Former CEO Norman Nie, who over the past two years has been instrumental in setting the product vision for Revolution's product suite, is now our Senior Advisor for Products and Strategy to the CEO. It's great to have Norman's expertise in statistics and big data analytics to continue to guide our product strategy for bringing R to the enterprise.

Thanks, Norman, for your leadership, and welcome, Dave, to the Revolution team! 

Revolution Analytics News Room: Revolution Analytics names David Rich new CEO

R 2.14.1 is released

Source distributions of the latest maintenance release of R, R 2.14.1, are now available. Binary distributions will begin appearing on local CRAN mirrors in the next few days.

This update makes a few small improvements (such as the ability to accurately count the number of available cores for parallel processing on Solaris and Windows, and improved support of grayscale Postscript and PDF graphics export) and fixes a few minor bugs (such as a correction to BIC calculations in the presence of zero-weight observations). The complete list of changes can be found in the NEWS file.

r-announce mailing list: R 2.14.1 is released

Announcing Revolution R Enterprise 5.0

We're proud to announce the latest update to the enhanced, commercial-grade distribution of R, Revolution R Enterprise 5.0. With each new release, Revolution R Enterprise adds more capabilities to open-source R, to make R users more productive, to improve performance of R programs, to support Big Data analytics, and to provide servers and APIs for enterprise deployment. 

New features in Revolution R Enterprise 5.0 include::

• Distributed/Parallel Computing: Automatically distribute statistical analyses from a desktop across nodes of a cluster through Windows HPC server and distribute R function calls across nodes. 
• Scalable Data Management: Increase flexibility in data analysis with new data import and cleaning/manipulation tools.
• Integration with Hadoop: Support MapReduce programming in R and integration with HDFS and HBASE with Cloudera Certified Technology.
• Expanded Scalable Analytics Functionality: Apply new big data statistics algorithms including principal components analysis, factor analysis, contingency table analysis and more.
• Enhanced R Productivity Environment: Create and build R packages with expanded support features.
• Enhanced RevoDeployR server: Add multiple compute nodes to support more users, batch execution of large analysis jobs, and LDAP enterprise security support.
• Upgraded Open Source R: Revolution R 5.0 includes the fully-patched R 2.13.2, which features a new byte-compiler to improve performance of user-written functions and packages.

We're particularly excited about the new capabilities to do parallel programming and statistical analysis on a HPC Server cluster. Here's a quick overview and an example of using a 5-node cluster to do a billion-row regression in less than a minute:

 

The detailed list of new features is below (after the jump), and you can find more about Revolution R Enterprise 5.0 at the link below. Existing subscribers will be notified with download instructions for the update in the next couple of days, and Revolution R Enterprise 5.0 is (as always) available free of charge to academic users.

Revolution Analytics: Revolution R Enterprise 5.0 overview 

R 2.14.0 is released

As scheduled, the first release of the new R 2.14 series is now available for download in source code form. As of this writing, pre-compiled binaries for Windows, Linux and MacOS aren't yet available, but will appear on your local CRAN mirror in the next couple of days.

One of the biggest changes in 2.14 is the introduction of the new "parallel" package as a standard part of R. As the NEWS file explains:

[The parallel package] incorporates (slightly revised) copies of packages multicore and snow (excluding MPI, PVM and NWS clusters).  Code written to use the higher-level API functions in those packages should work unchanged (apart from changing any references to their namespaces to a reference to parallel, and links explicitly to multicore or snow on help pages).

In addition, all of the standard (base and recommended) R packages are now byte-compiled on installation, which improves R's performance in several situations. 

Other improvements include better alignment of math and text in graphics, Rao's efficient score test for GLM's, the ability to draw curves from functions with plot.function, a new L'Ecuyer random number generator, improved access to documentation (especially vignettes), and several minor bug-fixes.

With R now on an annual (rather than six-monthly) update cycle, R 2.15 is not expected until October 2012 (with point releases for the 2.14.x series likely in the interim).

R-announce mailing list: R 2.14.0 is released

 

R 2.13.2 released

The R core team announced today that R 2.13.2 is now available:

The byte pixies have rolled up R-2.13.2.tar.gz at 9:00 this morning. This is intended to be the final release of the 2.13 series, for the benefit of those apprehensive of putting 2.14.x into production use. 

This update fixes a number of minor bugs (for example, pch="." will guarantee at least a 1-pixel dot, to support very high-resolution charting), improves performance (date object print much faster now, for example), and adds a few minor features (such as being able to accurately limit memory usage for systems with very large amounts of RAM). The full change log appears after the jump. 

You can download the R 2.13.2 source code now for home builds; binaries for Windows, Mac and Linux will appear on your local CRAN mirror in the next few days. The next release of R, R 2.14.0, is scheduled for October 31.

R-announce mailing list: R 2.13.2 is released

R 2.14 to be released on October 31; R 2.13 patch on September 30

The next major release of R has been announced: R 2.14.0 is scheduled for October 31. Details are still coming in about the new features planned for this release, but R core member Luke Tierney has revealed some of the performance improvements expected, and R core member Brian Ripley has spoken of forthcoming low-level support for multi-threaded computing and a standard parallel computing library (incorporating the existing multicore and snow packages). R 2.14.0 will mark the first release in the new annual (rather than six-monthly) cycle for major releases.

Also as new policy, this update will be preceded by a patch to the current R 2.13 series, with R 2.13.2 scheduled for September 30. This update will patch a number of minor bugs (for example, pch="." will guarantee at least a 1-pixel dot, to support very high-resolution charting) and a few minor features (such as being able to accurately limit memory usage for systems with very large amounts of RAM).

As the final pachlevel of the current release of R, R 2.13.2 will also serve as the foundation for the forthcoming Revolution R Enterprise 5.0.

r-announce mailing list: R 2.14.0 scheduled for October 31, 2.13.2 for September 30