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Revolution R: 100% R and more
1. Revolution R: 100% R and More Presented by: David Smith VP Marketing, Revolution Analytics
2. August 24, 2011: Welcome! Thanks for coming. Slides and replay available (soon) at: http://bit.ly/railcj David SmithVP Marketing, Revolution AnalyticsEditor, Revolutions blog http://blog.revolutionanalytics.com Twitter: @revodavid 2
3. In today’s webcast: About Revolution Analytics and R What Revolution R adds to R Resources for getting more from R Q&A 3 Introducing Revolution R
4. What is R? Data analysis software A programming language Development platform designed by and for statisticians An environment Huge library of algorithms for data access, data manipulation, analysis and graphics An open-source software project Free, open, and active A community Thousands of contributors, 2 million users Resources and help in every domain 4 Download the White Paper R is Hot
5. 7 Source: http://r4stats.com/popularity 5 R is exploding in popularity and functionality Scholarly Activity Google Scholar hits (’05-’09 CAGR) “I’ve been astonished by the rate at which R has been adopted. Four years ago, everyone in my economics department [at the University of Chicago] was using Stata; now, as far as I can tell, R is the standard tool, and students learn it first.” R 46% SAS -11% SPSS -27% S-Plus 0% Stata 10% Deputy Editor for New Products at Forbes Package Growth Number of R packages listed on CRAN “A key benefit of R is that it provides near-instant availability of new and experimental methods created by its user base — without waiting for the development/release cycle of commercial software. SAS recognizes the value of R to our customer base…” Product Marketing Manager SAS Institute, Inc. 2010 2008 2006 2004 2002
6. 3000+ R Packages from the Open Source community 6 Time Series analysis Portfolio Optimization Econometrics Genomics Clinical Trials Bayesian Inference Survival analysis Social Networks Data Visualization Data APIs (Twitter) .. and more
9. R Productivity Environment (Windows) 9 Script with type ahead and code snippets Solutions window for organizing code and data Sophisticated debugging with breakpoints , variable values etc. Objects loaded in the R Environment Packages installed and loaded Object details http://www.revolutionanalytics.com/demos/revolution-productivity-environment/demo.htm
10. Interactive Debugging One-click to set a breakpoint in an R script Step in/out/over, inspect variables Eliminate the edit -> browser -> repair cycle 10
12. Performance: Multi-threaded Math 12 Open Source R Revolution R Enterprise 1. http://www.revolutionanalytics.com/why-revolution-r/benchmarks.php 2. http://r.research.att.com/benchmarks/
13. Three Paradigms for Big Data Standard R engine is constrained by capacity and performance Revolution R Enterprise offers three methods for big data with R: Off-line: parallel out-of-memory analytics Off-line, distributed analytics On-line, in-database analytics Hadoop Netezza 13
14. Revolution R Enterprise with RevoScaleRBig Data Statistics in R 14 www.revolutionanalytics.com/bigdata Every US airline departure and arrival, 1987-2008 File: AirlineData87to08.xdf Rows: 123.5 million Variables: 29 Size on disk: 13.2Gb arrDelayLm2 <- rxLinMod(ArrDelay ~ DayOfWeek:F(CRSDepTime),cube=TRUE)
15. Example: Old Wives Census Analysis 15 http://info.revolutionanalytics.com/CensusOldWivesWhitePaper.html
18. Each compute node independently processes its data, and returns its intermediate results back to the master node
19. master node aggregates all of the intermediate results from each compute node and produces the final resultCompute Node (RevoScaleR) Data Partition Master Node (RevoScaleR) Compute Node (RevoScaleR) Data Partition Compute Node (RevoScaleR) Data Partition 16 *Available for Microsoft HPC Server, November 2011 Video demo: http://bit.ly/riUBgs
22. Hadoop Streaming package for executing MapReduce jobs from R.R Map or Reduce Task Tracker Task Node R Client Job Tracker 18
23. Enterprise Readiness: Revolution R Enterprise Server Multi-User Support Production Applications Integrate R analytics into Web based applications Data Analysis and Visualization Reporting Dashboards Interactive applications Revolution R Enterprise Server with RevoDeployR 19
24. 20 Deployment with Revolution R Enterprise Desktop Applications (i.e. Excel) Business Intelligence (i.e. Jaspersoft) Interactive Web Applications End User Client libraries (JavaScript, Java, .NET) Application Developer HTTP/HTTPS – JSON/XML RevoDeployR Web Services R Programmer Session Management Authentication Data/Script Management Administration R
25. The Advanced Analytics Stack Deployment / Consumption Advanced Analytics ETL Data / Infrastructure “Open Analytics Stack” White Paper: bit.ly/lC43Kw 21
26. On-Call Technical Support Consulting Migration | Analytics | Applications | Validation Training R | Revolution R | Statistical Topics Systems Integration BI | ERP | Databases | Cloud 22
28. Why R? 24 Every data analysis technique at your fingertips Create beautiful and unique data visualizations Get better results faster Draw on the talents of data scientists worldwide R is hot, and growing fast
39. Revolution R Enterprise: Free to Academia Personal use Research Teaching Package development 27 Free Academic Download www.revolutionanalytics.com/downloads/free-academic.php Discounted Technical Support Subscriptions Available
40. Thank You! Download slides, replay (from Aug 24) http://bit.ly/railcj Learn more about Revolution R revolutionanalytics.com/products Keep up to date with R and Revolution news revolutionanalytics.com/newsletter Contact Revolution Analytics http://bit.ly/hey-revo 28
41. 29 The leading commercial provider of software and support for the popular open source R statistics language. www.revolutionanalytics.com +1 (650) 330 0553Twitter: @RevolutionR
Editor's Notes
Type ahead: the IDE recognizes an R function as you type in the first few characters and shows the completed formula and parametersCode snippets: Templates for common R functions e.g. for loop, xy plot. These are written in XML and users can add their ownSolution Window: The RPE organizes R scripts and data files in folders by Solution. This facilitates but does not implement versioningThe lists of packages of installed and the list of loaded packages are available for inspection. Clicking on these packages shows their components in the object windowThe top right Object Browser window shows all of the objects available in the R environmentThe bottom right object window shows the details of particular objectsDebugging Tools: when running in debugging mode the RPE supports breakpoints, stepping in and out of code and shows the contents of variables upon “mouse over”.Users may step through all code available in the Solution that is active.
