Update 2/6/16

As of 2015-10-20, the bigmemory on CRAN has been updated! This update restores windows functionality without the use of a development version.

To install the most up to date version use:

# Install Bigmemory packages from CRAN page
install.packages("bigmemory")

Furthermore, the bigmemory package now has an active website at http://www.bigmemory.org/ and the development versions are now being kept on GitHub instead of R-Forge at https://github.com/kaneplusplus/bigmemory

Happy Big Data Wrangling!

Intro

This post is now out of date

The objective of this post is to be able to install the bigmemory package and the following bigmemory family packages: biganalytics, biglm, and bigalgebra.

Installing bigmemory on Windows

The main reason this post is being written is due to the issues many students are having installing bigmemory on Windows. Looking at the last posting on their website by the bigmemory developers, the authors of the package note that bigmemory support on Windows is lacking and they were working on ways to update it.

What this means is that the CRAN version of bigmemory only works for OS X and Linux at the time of this writing.

To get around this, we download and install the source files located on the project’s r-forge page

# Install Bigmemory packages from r-forge page
install.packages("bigmemory", repos="http://R-Forge.R-project.org")
install.packages("bigmemory.sri", repos="http://R-Forge.R-project.org")
install.packages("biganalytics", repos="http://R-Forge.R-project.org")
install.packages("bigalgebra", repos="http://R-Forge.R-project.org")
# Install Boost Header and biglm package from CRAN
install.packages(c("BH","biglm"))

Installing bigmemory on OS X or Linux

To install bigmemory on OS X or Linux all you need to do is issue the following install command:

# Install Bigmemory packages from r-forge page
install.packages(c("bigmemory","bigmemory.sri", "biganalytics", "bigalgebra","BH","biglm"))