Hello Giovanni,
I don't know if my workflow would suit you but I tend to want the
opposite when I launch a parallel process. I tend to want to keep the
processes alive as long as they can. If the computation time is long I
would not want to lose everything.
lapply..8 <- function(X,FUN,...){
max..cores <- as.numeric(system("grep ^processor /proc/cpuinfo 2>/dev/null
| wc -l",TRUE))
mclapply(X,FUN,mc.cores=min(max..cores,8))
}
lapply_with_error..8 <- function(X,FUN,...) {
lapply..8(X, function(x, ...) tryCatch(FUN(x, ...),
error=function(e){
print(e)
e}
))
}
res <- lapply_with_error..8(X = 1:12, FUN = function(x) {Sys.sleep(0.1); if(x
== 4) stop()})
Then we can investigate the problem for the element that generated
errors. It is even better if we could anticipate the errors and avoid
surprises by well _testing_ the function before launching a long
process.
If you want the processes to fail fast, I fear that you want to launch the
parallel process too soon without
having tested your function enough.
HTH,
Jeremie
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