performance - Possible shortcomings for using JIT with R?

Question

I recently discovered that one can use JIT (just in time) compilation with R using the compiler package (I summarizes my findings on this topic in a recent blog post).

One of the questions I was asked is:

Is there any pitfall? it sounds too good to be true, just put one line of code and that's it.

After looking around I could find one possible issue having to do with the "start up" time for the JIT. But is there any other issue to be careful about when using JIT?

I guess that there will be some limitation having to do with R's environments architecture, but I can not think of a simple illustration of the problem off the top of my head, any suggestions or red flags will be of great help?

Answer 1

the output of a simple test with rpart could be an advice not to use enableJIT in ALL cases:

library(rpart)
fo <- function() for(i in 1:500){rpart(Kyphosis ~ Age + Number + Start, data=kyphosis)}
system.time(fo())
#User      System verstrichen 
#2.11        0.00        2.11 

require(compiler)
enableJIT(3)
system.time(fo())
#User      System verstrichen 
#35.46        0.00       35.60

Any explanantion?