Tricks to manage the available memory in an R session

Question

What tricks do people use to manage the available memory of an interactive R session? I use the functions below [based on postings by Petr Pikal and David Hinds to the r-he

Answer 1

As well as the more general memory management techniques given in the answers above, I always try to reduce the size of my objects as far as possible. For example, I work with very large but very sparse matrices, in other words matrices where most values are zero. Using the 'Matrix' package (capitalisation important) I was able to reduce my average object sizes from ~2GB to ~200MB as simply as:

my.matrix <- Matrix(my.matrix)

The Matrix package includes data formats that can be used exactly like a regular matrix (no need to change your other code) but are able to store sparse data much more efficiently, whether loaded into memory or saved to disk.

Additionally, the raw files I receive are in 'long' format where each data point has variables x, y, z, i. Much more efficient to transform the data into an x * y * z dimension array with only variable i.

Know your data and use a bit of common sense.