Blog Archives

Slides and replay from "R and Hadoop" webinar

September 21, 2011
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Slides and replay from "R and Hadoop" webinar

So ... there's clearly a lot of interest in integrating R and Hadoop. Today's webinar was a record-setter for Revolution Analytics, with more than 1000 people signing up to learn how to access Hadoop data from R with the packages from the open-source RHadoop project. If you didn't catch the live webinar, don't fret: the slides and replay are...

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R 2.14 to be released on October 31; R 2.13 patch on September 13

September 19, 2011
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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...

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How to extract time series from large timestamped logs with R

September 16, 2011
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Revolution Analytics' Joe Rickert has a new post on inside-R.org, demonstrating how you can use R and the RevoScaleR package to extract time series data from time-stamped logs (in this case, the "US Domestic Flights From 1990 to 2009" dataset on Infochimps): Analyzing time series data of all sorts is a fundamental business analytics task to which the R...

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How Lloyd’s of London uses R for Insurance

September 15, 2011
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How Lloyd’s of London uses R for Insurance

Lloyd's is the world's leading specialist insurance market, and is often the first to insure new, unusual or complex risks. So it's no surprise that Lloyd's is one of the many companies that use R and its advanced capabilities for data analysis to help manage its insurance risks. At the useR! conference last month, Lloyd's analysts Markus Gesmann, Viren...

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Using Google Spreadsheets with R: an update

September 15, 2011
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Prompted by a rush of visitors from Andrew Gelman's blog, I went back and updated the details of my post from 2009 on reading data from Google Spreadsheets into R. Since then, Google had switched to using a secure (https) connection for Google Docs, which required some tweaks to the code. If you haven't seen it before, it's a...

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Revolution Analytics Fall Webinar Series

September 14, 2011
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We've lined up what we think is an amazing series of R-related webinars over the next couple of months. These free 30-60 minute webinars will cover a wide range of topics: big-data analysis in R with the RevoScaleR package, Hadoop and Netezza; introductions to R for SAS users and for R users new to Revolution R; and applications of...

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How to program MapReduce jobs in Hadoop with R

September 13, 2011
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MapReduce is a powerful programming framework for efficiently processing very large amounts of data stored in the Hadoop distributed filesystem. But while several programming frameworks for Hadoop exist, few are tuned to the needs of data analysts who typically work in the R environment as opposed to general-purpose languages like Java. That's why the dev team at Revolution Analytics...

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Speed up recursion in R 600-fold with Rcpp

September 12, 2011
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Rcpp package co-author Dirk Eddelbuettel provides another case study in speeding up R code by rewriting repeatedly-called R code as inline C++ functions, using the classic Fibonacci recursion algorithm as an example. The speed gains here are impressive -- over 600x compared to native recursive R code -- but you could also improve performance by using a more efficient,...

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Why you should care about reproducible research

September 12, 2011
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This week's Economist has an in-depth article on the consequences of failures reproducible research, adding more detail to the report in the New York Times in July. Errors in data analysis by researchers at Duke University led to patients in clinical trials being assigned the wrong drug: Dr Potti and his colleagues had mislabelled the cell lines they used...

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Unlocking Big Data with R

September 9, 2011
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I have an article out this week on ReadWriteHack: Unlocking Big Data with R. My thanks to the folks at ReadWriteWeb for giving us the opportunity to showcase some of the many real-world Big Data applications of R. Here are some additional links about the applications mentioned in the article: New York Times: Destruction of the Haiti earthquake; 2010...

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