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(expr, envir = parent.frame(), substitute = TRUE, lazy = FALSE, seed = NULL, globals = TRUE, persistent = FALSE, workers = availableWorkers(), user = NULL, revtunnel = TRUE, homogeneous = TRUE, gc = FALSE, earlySignal = FALSE, label = NULL, ...)
expr |
An R expression. |
envir |
The environment from where global objects should be identified. |
substitute |
If TRUE, argument |
lazy |
If |
seed |
(optional) A L'Ecuyer-CMRG RNG seed. |
globals |
(optional) a logical, a character vector, or a named list
to control how globals are handled.
For details, see section 'Globals used by future expressions'
in the help for |
persistent |
If FALSE, the evaluation environment is cleared from objects prior to the evaluation of the future. |
workers |
A |
user |
(optional) The user name to be used when communicating with another host. |
revtunnel |
If TRUE, reverse SSH tunneling is used for the PSOCK cluster nodes to connect back to the master R process. This avoids the hassle of firewalls, port forwarding and having to know the internal / public IP address of the master R session. |
homogeneous |
If TRUE, all cluster nodes is assumed to use the same path to ‘Rscript’ as the main R session. If FALSE, the it is assumed to be on the PATH for each node. |
gc |
If TRUE, the garbage collector run (in the process that
evaluated the future) only after the value of the future is collected.
Exactly when the values are collected may depend on various factors such
as number of free workers and whether |
earlySignal |
Specified whether conditions should be signaled as soon as possible or not. |
label |
An optional character string label attached to the future. |
... |
Additional named elements passed to |
This function will block if all available R cluster nodes are occupied and will be unblocked as soon as one of the already running cluster futures is resolved.
The preferred way to create an cluster future is not to call
this function directly, but to register it via
plan(cluster)
such that it becomes the default
mechanism for all futures. After this future()
and %<-%
will create cluster futures.
## Use cluster futures cl <- parallel::makeCluster(2L, 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)