R evolution R E nterpris e R eleas e 6.2 New F eatures

David M. S mith T homas W. Dins more

May 1, 2013 1

P oll Ques tion

Which stats package do you use most?

In today’s webcas t:

About Revolution R Enterprise New Features in Revolution R Enterprise 6.2 Resources for getting more from R Q&A

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Revolution Analytics is the leading commercial provider of software and support for the

open-source R statistical computing language

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R evolution R E nterpris e is Enterprise-ready Multi-platform Scalable from desktop to big data Delivers high performance analytics Easier to build and deploy analytic applications

What is R ? Data analysis software A powerful programming language

Development platform designed by and for statisticians A complete environment

Huge library of algorithms for data access, data manipulation, analysis and graphics

An open-source software project Free, open, and active

A vibrant community Thousands of contributors, 2 million users Resources and help in every domain

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Download the White Paper

R is Hot bit.ly/r-is-hot

R evolution A nalytic s S c ales R to the E nterpris e

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Power Distributed high performance

analytics Productivity Build & deploy analytics

applications easily Enterprise Readiness Enterprise landscape Full-service customer

support, consulting and training

Power

Productivity

Enterprise Readiness

Revolution R Enterprise

R evolution R E nterpris e High P erformanc e, Multi-P latform A nalytic s P latform

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Revolution R Enterprise

ScaleR High Performance Big Data Analytics

RevoR Performance Enhanced Open Source R

Open Source R packages

ConnectR High Speed Connectors

HDFS, Hbase, ODBC, SAS

PlatformR Parallel Distributed Computing

IBM/Netezza, IBM/Platform LSF, MS HPC Server, MS Azure Burst

DevelopR Integrated Development Environment

DeployR Web Services

S c aleR brings the power of B ig Data to R

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Parallel External Memory Algorithms exploit available compute resources (cores & computers) independent of platform

Abstracted communications layer provides portability of

code between platforms: server, cluster, or in-

database

Use the high-speed local data mart (XDF), or stream data from SAS, ODBC, HDFS or other remote data sources.

Familiar, high-productivity

programming environment for R users

Distributed Statistical Algorithms

Communications Framework

Data Source API

R Language Interface

S c aleR A ddres s es P erformanc e and C apac ity L imitations of Open S ourc e R

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DeployR integrates R with applic ations

Seamless Bring the power of R to any web enabled application

Simple Leverage common APIs including JS, Java, .NET

Scalable Robustly scale user and compute workloads

Secure Manage enterprise security with LDAP & SSO

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R / Statistical Modeling Expert

DeployR

Business Intelligence

Mobile Web Apps

Cloud / SaaS

Deployment Expert

R evolution R E nterpris e A rchitecture Use a connected MPP server or cluster for:

Data exploration On-demand R applications Big-data predictive models Offline (batch) operations Code generation for real-time deployment

R R E 6.2 New F eatures Open Source R 2.15.3 High Speed Teradata Connector New Analytics Improved Performance Enhanced DeployR API

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S upport for Open S ourc e R 2.15.3

89 new features 11 performance enhancements 139 bug fixes 137 package dependencies

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High-S peed Teradata C onnector

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50,000

100,000

150,000

200,000

250,000

300,000

1MM 10MM 100MM

Row

s P

er S

econ

d Data Transfer Speed

ODBC TPT

Source: Teradata Center of Excellence

Six times faster

New A nalytics : (1) S tepwis e R egres s ion

Automates the model fitting process Uses statistical criteria to select features Multiple options:

Methods: Forwards, backwards, bidirectional Criteria: AIC, BIC, Mallows’ Cp

Linear models (working on Logistic, GLM)

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New A nalytics (2): P R NG

Parallel Random Number Generator R interface to MKL PRNGs Needed for “Forests” Useful in simulation, Monte Carlo analysis

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Other A nalytic E nhancements

Improved control over model-fitting Interaction terms Linear models, GLM, logit

Output to XDF: “By-Group” summary stats Cube results

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P erformance E nhancements

Fixed format text input: Previously used Stat/Transfer With RRE 6.2:

~2x faster on Windows ~1.3x faster on Linux

Sort and merge

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P erformance E nhancements : S ort

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2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

Test A Test B

Row

s P

er S

econ

d Sort Speed

RRE 6.1 RRE 6.2

Ten times faster Nine times faster

15MM rows 100 columns

7.5MM rows 200 columns

Sort on five keys

DeployR E nhancements

Priority scheduling for asynchronous jobs Execute external scripts

GIT SVN

Repository-managed files and scripts Lifecycle management Enhanced versioning

Updated java, javascript, .net client libraries

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R evolution R E nterpris e 6.2

Updated R distribution Enhanced Teradata integration More analytic capabilities Faster import, sort and merge Improved enterprise deployability 11

P oll Ques tion

What interests you most about Revolution R Enterprise?

T hank You! Download slides, replay

http://bit.ly/RRE62-webinar Resources for getting started with R

http://bit.ly/ZnZGt2

Get Revolution R Enterprise Contact Sales: http://bit.ly/hey-revo Free to Academics: www.revolutionanalytics.com/academic

We’re Hiring!

www.revolutionanalytics.com/careers

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www.revolutionanalytics.com +1 650 646 9545 Twitter: @RevolutionR

The leading commercial provider of software and support for the popular open source R statistics language.

T hank you

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