Saturday Mar 15, 2014

Oracle R Enterprise 1.4 Released

We’re pleased to announce that Oracle R Enterprise (ORE) 1.4 is now available for download on all supported platforms. In addition to numerous bug fixes, ORE 1.4 introduces an enhanced high performance computing infrastructure, new and enhanced parallel distributed predictive algorithms for both scalability and performance, added support for production deployment, and compatibility with the latest R versions.  These updates enable IT administrators to easily migrate the ORE database schema to speed production deployment, and statisticians and analysts have access to a larger set of analytics techniques for more powerful predictive models.

Here are the highlights for the new and upgraded features in ORE 1.4:

Upgraded R version compatibility

ORE 1.4 is certified with R-3.0.1 - both open source R and Oracle R Distribution. See the server support matrix for the complete list of supported R versions. R-3.0.1 brings improved performance and big-vector support to R, and compatibility with more than 5000 community-contributed R packages.

High Performance Computing Enhancements

Ability to specify degree of parallelism (DOP) for parallel-enabled functions (ore.groupApply, ore.rowApply, and ore.indexApply)
An additional global option, ore.parallel, to set the number of parallel threads used in embedded R execution

Data Transformations and Analytics

ore.neural now provides a highly flexible network architecture with a wide range of activation functions, supporting 1000s of formula-derived columns, in addition to being a parallel and distributed implementation capable of supporting billion row data sets
ore.glm now also prevents selection of less optimal coefficient methods with parallel distributed in-database execution
Support for weights in regression models
New ore.esm enables time series analysis, supporting both simple and double exponential smoothing for scalable in-database execution
Execute standard R functions for Principal Component Analysis (princomp), ANOVA (anova), and factor analysis (factanal) on database data

Oracle Data Mining Model Algorithm Functions

Newly exposed in-database Oracle Data Mining algorithms:

ore.odmAssocRules function for building Oracle Data Mining association models using the apriori algorithm
ore.odmNMF function for building Oracle Data Mining feature extraction models using the Non-Negative Matrix Factorization (NMF) algorithm
ore.odmOC function for building Oracle Data Mining clustering models using the Orthogonal Partitioning Cluster (O-Cluster) algorithm

Production Deployment

New migration utility eases production deployment from development environments
"Snapshotting" of production environments for debugging in test systems

For a complete list of new features, see the Oracle R Enterprise User's Guide. To learn more about Oracle R Enterprise, check out the white paper entitled, "Bringing R to the Enterprise -  A Familiar R Environment with Enterprise-Caliber Performance, Scalability, and Security.", visit Oracle R Enterprise on Oracle's Technology Network, or review the variety of use cases on the Oracle R blog.

Sunday Dec 08, 2013

Explore Oracle's R Technologies at BIWA Summit 2014

It’s getting to be that time of year again. The Oracle BIWA Summit '14 will be taking place January 14-16 at Oracle HQ Conference Center, Redwood Shores, CA. Check out the detailed agenda.

BIWA Summit provides a wide range of sessions on Business Intelligence, Warehousing, and Analytics, including: novel and interesting use cases of Oracle Big Data, Exadata, Advanced Analytics/Data Mining, OBIEE, Spatial, Endeca and more! You’ll also have opportunities to get hands on experience with products in the Hands-on Labs, great customer case studies and talks by Oracle Technical Professionals and Partners.  Meet with technical experts on the technology you want and need to use. 

Click HERE to read detailed abstracts and speaker profiles.  Use the SPECIAL DISCOUNT code ORACLE12c and registration is only $199 for the 2.5 day technically focused Oracle user group event.

On the topic of Oracle’s R technologies, don't miss:

  • Introduction to Oracle's R Technologies
  • Applying Oracle's R Technologies to Big Data Problems
  • Hands-on Lab: Learn to use Oracle R Enterprise
  • OBIEE + OAA Integration Paths : interactive OAA in SampleApp Dashboards
  • Blazing Business Analytics: Analytic Options to the Oracle Database
  • Best Practices for In-Database Analytics

We look forward to meeting you there!

Friday Dec 06, 2013

Oracle R Distribution 3.0.1 now available for Windows 64-bit

We are excited to introduce support for Oracle R Distribution 3.0.1 on Windows 64-bit versions. Previous releases are available on Solaris x86, Solaris SPARC, AIX and Linux 64-bit platforms. Oracle R Distribution (ORD) continues to support these platforms and now expands support to Windows 64-bit platforms.

ORD is Oracle's free distribution of the open source R environment that adds support for dynamically loading the Intel Math Kernel Library (MKL) installed on your system. MKL provides faster performance by taking advantage of hardware-specific math library implementations. The net effect is optimized processing speed, especially on multi-core systems.

To enable MKL support on your ORD Windows client:

1. Add the location of libOrdBlasLoader.dll and mkl_rt.dll to the PATH system environment variable on the client.

In a typical ORD 3.0.1 installation, libOrdBlasLoader.dll is located in the R HOME directory:

C:\Program Files\R\R-3.0.1\bin\x64

In a full MKL 11.1 installation, mkl_rt.dll is located in the Intel MKL Composer XE directory:

C:\Program Files (x86)\Intel\Composer XE 2013 SP

2. Start R and execute the function Sys.BlasLapack:

    R> Sys.BlasLapack()
     [1] "Intel Math Kernel Library (Intel MKL)"

     [1] -1

The vendor value returned indicates the presence of MKL instead of R's internal BLAS. The value for the number of threads to utilize, nthreads = -1, indicates all available cores are used by default. To modify the number of threads used, set the system environment variable MKL_NUM_THREADS = n, where n is the number of physical cores in the system you wish to use.

To install MKL on your Windows client, you must have an MKL license.

Oracle R Distribution will be certified with a future release of Oracle R Enterprise, and is available now from Oracle's free and Open Source Software portal. Questions and comments are welcome on the Oracle R Forum.

Monday Jul 29, 2013

Oracle R Distribution for R-3.0.1 released

We're pleased to announce that the Oracle R Distribution 3.0.1 Linux RPMs are now available on Oracle's public yum. R-3.0.1, code-named "Good Sport", is the second release in the R-3.0.x series. This new series in R doesn't announce new features, but indicates that the code base has developed to a new level of maturity.

However, there are some significant improvements in the 3.0 series worth mentioning.  R-3.0.0 introduces the use of large vectors in R, and eliminates some restrictions in the core R engine by allowing R to use the memory available on 64-bit systems more efficiently. Prior to this release, objects had a hard-coded limit of 2^31-1 elements, or roughly 2.1 billion elements.  Objects exceeding this limit were treated as missing (NA) and R sometimes returned a warning, regardless of available memory on the system. Starting in R-3.0.0, objects can exceed this limit, which is a significant improvement. Here's the relevant statement from the R-devel NEWS file:

 There is a subtle change in behaviour for numeric index 
 values 2^31 and larger. These never used to be legitimate 
 and so were treated as NA, sometimes with a warning. They 
 are now legal for long vectors so there is no longer a 
 warning, and x[2^31] <- y will now extend the vector on a 
 64-bit platform and give an error on a 32-bit one. 

R-3.0.1 adds to these updates by improving serialization for big objects and fixing a variety of bugs.

Older open source R packages will need to be re-installed after upgrading from ORD 2.15.x to ORD 3.0.1, which is accomplished by running:

R> update.packages(checkBuilt = TRUE) 

This command upgrades open source packages if a more recent version exists on CRAN or if the installed package was build with an older version of R.

Oracle R Distribution 3.0.1 will be compatible with future versions of Oracle R Enterprise.  As of this posting, we recommend using ORD 2.15.3 with Oracle R Enterprise 1.3.1.  When installing ORD for use with ORE 1.3.1, be sure to use the command yum install R- 2.15.3, otherwise R-3.0.1 will be installed by default.

ORD 3.0.1 binaries for AIX, Solaris x86, and Solaris SPARC platforms will be available from Oracle's free and Open Source portal soon. Please check back for updates.


The place for best practices, tips, and tricks for applying Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Advanced Analytics for Hadoop in both traditional and Big Data environments.


« May 2015