cluster {future} | R Documentation |
A cluster future is a future that uses cluster evaluation, which means that its value is computed and resolved in parallel in another process.
cluster(..., workers = availableWorkers(), envir = parent.frame())
... |
Additional named elements passed to |
workers |
A |
envir |
The environment from where global objects should be identified. |
This function is not meant to be called directly. Instead, the typical usages are:
# Evaluate futures via a single background R process on the local machine plan(cluster, workers = 1) # Evaluate futures via two background R processes on the local machine plan(cluster, workers = 2) # Evaluate futures via a single R process on another machine on on the # local area network (LAN) plan(cluster, workers = "raspberry-pi") # Evaluate futures via a single R process running on a remote machine plan(cluster, workers = "pi.example.org") # Evaluate futures via four R processes, one running on the local machine, # two running on LAN machine 'n1' and one on a remote machine plan(cluster, workers = c("localhost", "n1", "n1", "pi.example.org")
## Use cluster futures cl <- parallel::makeCluster(2, timeout = 60) plan(cluster, workers = cl) ## A global variable a <- 0 ## Create future (explicitly) f <- future({ b <- 3 c <- 2 a * b * c }) ## A cluster future is evaluated in a separate process. ## Regardless, changing the value of a global variable will ## not affect the result of the future. a <- 7 print(a) v <- value(f) print(v) stopifnot(v == 0) ## CLEANUP parallel::stopCluster(cl)