14

PERFORMANCE ENHANCEMENT: SPEED AND MEMORY

In computer science curricula, a common

theme is the trade-off between time and

space. In order to have a fast-running pro-

gram, you may need to use more memory space.

On the other hand, in order to conserve memory space,

you might need to settle for slower code. In the R lan-

guage, this trade-off is of particular interest for the fol-

lowing reasons:

• R is an interpreted language. Many of the commands are written in C
  and thus do run in fast machine code. But other commands, and your
  own R code, are pure R and thus interpreted. So, there is a risk that
  your R application may run more slowly than you would like.


• All objects in an R session are stored in memory. More precisely, all
  objects are stored in R’s memory address space. R places a limit of
  231 −1 bytes on the size of any object, even on 64-bit machines and
  even if you have a lot of RAM. Yet some applications do encounter
  larger objects.