Error: C stack usage is too close to the limit

Question

I'm attempting to run some fairly deep recursive code in R and it keeps giving me this error:

Error: C stack usage is too close to the limit

My output from CStack_info() is:

Cstack_info()
    size    current  direction eval_depth 
67108864       8120          1          2 

I have plenty of memory on my machine, I'm just trying to figure out how I can increase the CStack for R.

EDIT: Someone asked for a reproducible example. Here's some basic sample code that causes the problem. Running f(1,1) a few times you'll get the error. Note that I've already set --max-ppsize = 500000 and options(expressions=500000) so if you don't set those you might get an error about one of those two things instead. As you can see, the recursion can go pretty deep here and I've got no idea how to get it to work consistently. Thanks.

f <- function(root=1,lambda=1) {
    x <- c(0,1);
    prob <- c(1/(lambda+1),lambda/(lambda+1));
        repeat {
      if(root == 0) {
        break;
      }
      else {
        child <- sample(x,2,replace=TRUE,prob);
        if(child[1] == 0 && child[2] == 0) {
          break;
        }
        if(child[1] == 1) {
          child[1] <- f(root=child[1],lambda);
        }
        if(child[2] == 1 && child[1] == 0) {
          child[2] <- f(root=child[2],lambda);
        }
      }
      if(child[1] == 0 && child[2] == 0) {
        break;
      }
      if(child[1] == 1 || child[2] == 1) {
        root <- sample(x,1,replace=TRUE,prob);
      }
        }
    return(root)
}

Answer 1

I encountered the same problem of receiving the "C stack usage is too close to the limit" error (albeit for another application than the one stated by user2045093 above). I tried zwol's proposal but it didn't work out.

To my own surprise, I could solve the problem by installing the newest version of R for OS X (currently: version 3.2.3) as well as the newest version of R Studio for OS X (currently: 0.99.840), since I am working with R Studio.

Hopefully, this may be of some help to you as well.

Answer 2

One issue here can be that you're calling f inside itself

plop <- function(a = 2){
  pouet <- sample(a)
  plop(pouet)
}
plop()
Erreur : évaluations trop profondément imbriquées : récursion infinie / options(expressions=) ?
Erreur pendant l'emballage (wrapup) : évaluations trop profondément imbriquées : récursion infinie / options(expressions=) ?

Answer 3

As Martin Morgan wrote... The problem is that you get too deep inside of recursion. If the recursion does not converge at all, you need to break it by your own. I hope this code is going to work, because It is not tested. However at least point should be clear here.

f <- function(root=1,lambda=1,depth=1) {
 if(depth > 256){
  return(NA)
 }
 x <- c(0,1);
 prob <- c(1/(lambda+1),lambda/(lambda+1));
 repeat {
  if(root == 0) {
    break;
  } else {
   child <- sample(x,2,replace=TRUE,prob);
   if(child[1] == 0 && child[2] == 0) {
     break;
   }
   if(child[1] == 1) {
     child[1] <- f(root=child[1],lambda,depth+1);
   }
   if(child[2] == 1 && child[1] == 0) {
     child[2] <- f(root=child[2],lambda,depth+1);
   }
  }
  if(child[1] == NA | child[2] == NA){
   return NA;
  }
  if(child[1] == 0 && child[2] == 0) {
    break;
  }
  if(child[1] == 1 || child[2] == 1) {
    root <- sample(x,1,replace=TRUE,prob);
  }
 }
 return(root)
}

Answer 4

The stack size is an operating system parameter, adjustable per-process (see setrlimit(2)). You can't adjust it from within R as far as I can tell, but you can adjust it from the shell before starting R, with the ulimit command. It works like this:

$ ulimit -s # print default
8192
$ R --slave -e 'Cstack_info()["size"]'
   size 
8388608

8388608 = 1024 * 8192; R is printing the same value as ulimit -s, but in bytes instead of kilobytes.

$ ulimit -s 16384 # enlarge stack limit to 16 megs
$ R --slave -e 'Cstack_info()["size"]'
    size 
16777216 

Answer 5

This happened to me for a completely different reason. I accidentally created a superlong string while combining two columns:

output_table_subset = mutate(big_data_frame,
     combined_table = paste0(first_part, second_part, col = "_"))

instead of

output_table_subset = mutate(big_data_frame,
     combined_table = paste0(first_part, second_part, sep = "_"))

Took me for ever to figure it out as I never expected the paste to have caused the problem.

Answer 6

This error is not due to memory it is due to recursion. A function is calling itself. To illustrate the point, here is a minimal example of 2 functions that call each other:

change_to_factor <- function(x){
  x <- change_to_character(x)
  as.factor(x)
} 

change_to_character <- function(x){
  x <- change_to_factor(x)
  as.character(x)
}

change_to_character("1")

Error: C stack usage 7971600 is too close to the limit

The functions will continue to call each other recursively and will theoretically never complete. It is only checks within your system that prevent this from occurring definitely and consuming all of the compute resources of your machine. You need to alter the functions to ensure that they don't call itself (or each other) recursively.