Consider the following function definitions
library(doParallel)
f_print <- function(x)
{
print(x)
}
f_foreach <- function(l)
{
foreach (i=l) %do%
{
f_print(i)
}
}
f_foreach_parallel <- function(l)
{
doParallel::registerDoParallel(1)
foreach (i=l) %dopar%
{
f_print(i)
}
}
Function use :
> f_foreach(c(1,2))
[1] 1
[1] 2
[[1]]
[1] 1
[[2]]
[1] 2
> f_foreach_parallel(c(1,2))
Show Traceback
Rerun with Debug
Error in { :
task 1 failed - "impossible de trouver la fonction "f_print""
[Error: could not find function f_print]
>
Can you help explain why the f_print()
is not visible when parallelism is involved in foreach
? How can we use f_print()
in this paralleled foreach
?Any documentations related to this point ?
In addition to what has already been said in the comments of the top post, especially the one on specifying .export
, when using the doFuture package your code will indeed work regardless of parallel backend, operating system, and .export
. Here's an adapted version of your setup:
f_print <- function(x) {
print(x)
}
f_foreach <- function(l) {
foreach(i=l) %do% {
f_print(i)
}
}
f_foreach_dopar <- function(l) {
foreach(i=l) %dopar% {
f_print(i)
}
}
Instead of doing:
library("doParallel")
## Setup PSOCK workers (just as on Windows)
workers <- parallel::makeCluster(1L, outfile = "")
registerDoParallel(workers)
f_foreach_dopar(c(1,2))
## Error in { : task 1 failed - "could not find function "f_print""
you can do:
library("doFuture")
registerDoFuture()
## As above
workers <- parallel::makeCluster(1L, outfile = "")
plan(cluster, workers = workers)
f_foreach_dopar(c(1,2))
## [1] 1
## [1] 2
## [[1]]
## [1] 1
##
## [[2]]
## [1] 2
The reason why this works is that doFuture does a more thorough search to identify global variables (here f_print()
).
PS. The reason for outfile = ""
is so that stdout/stderr output (e.g. as from print()
) is actually displayed. Redirecting stdout/stderr in parallel processing, which I don't recommend, is a whole different discussion, but I'll assume you used print()
just for your example.