R references for handling Big data

October 27, 2010

(This article was first published on Maximize Productivity with Industrial Engineer and Operations Research Tools, and kindly contributed to R-bloggers)

The Dallas R User Group had a meeting over the weekend.  One of the discussions is the memory limitations with R.  This is a common subject among the R community and R User Groups.  There has been a lot of strides recently in allowing R to stretch its memory limitations.  I thought I would compile and share some of the best resources I have found to remedy the big data issue.

CRAN Packages
This package allocates hard disk space to big data vectors.

This package allocates points to unused memory or points to a swap file.

Blog Articles
Taking R to the Limit:  Parallelism and Big Data

Hitting the Big DataCeiling Limit in R
While this is not a helpful article for big data it does show some of the issues R current faces.  Namely the issue of that lack of a “int64” or Long Long data type memory allocation.

Enterprise Software
Revolution R Enterprise
Revolution Analytics is creating enterprise software around R to tackle issues of big data, parallelism and threaded computing in order to speed up large data processing and analytics.

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