New ways to Hadoop with R

February 26, 2013
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Today, there are two main ways to use Hadoop with R and big data:

1. Use the open-source rmr package to write map-reduce tasks in R (running within the Hadoop cluster - great for data distillation!)

2. Import data from Hadoop to a server running Revolution R Enterprise, via Hbase, ODBC (for high-performance Hadoop/SQL interfaces), or streaming data direct from HDFS to ScaleR's big-data predictive algorithms.

And now, there are even more Hadoop platforms supported for use with Revolution R Enterprise. You can use:

  • Cloudera CDH3 or CDH4
  • IBM BigInsights 2
  • New! Hortonworks Data Platform 1.2 
  • New! Intel's Distribution for Hadoop (announced today)

And by the end of the year, there will be a third way to use Hadoop with R:

3. Leave the data in Hadoop, and use ScaleR's "in-Hadoop predictive analytics"

We announced today that we are jointly developing in-Hadoop predictive analytics with HortonWorks, and our first demonstrations are taking place now at the Strata conference. It's in the prototype stage right now, but we expect to have it generally available by the end of the year. In the meantime, check out the video below which explains the three ways of using R and Hadoop together, and includes an early demo of our in-Hadoop Predictive Analytics.

 

For more details, check out the press release below.

Revolution Analytics press releases: Revolution Analytics Expands Support for Hadoop and Pioneers In-Hadoop Predictive Analytics with Hortonworks

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