future (version 1.3.0)

multisession: Create a multisession future whose value will be resolved asynchronously in a parallel R session

Description

A multisession future is a future that uses multisession evaluation, which means that its value is computed and resolved in parallel in another R session.

Usage

multisession(expr, envir = parent.frame(), substitute = TRUE,
  lazy = FALSE, seed = NULL, globals = TRUE, persistent = FALSE,
  workers = availableCores(), gc = FALSE, earlySignal = FALSE,
  label = NULL, ...)

Arguments

expr

An R expression to be evaluated.

envir

The environment from where global objects should be identified. Depending on the future strategy (the evaluator), it may also be the environment in which the expression is evaluated.

substitute

If TRUE, argument expr is substitute():ed, otherwise not.

lazy

Specifies whether a future should be resolved lazily or eagerly. The default is eager evaluation (except when the deprecated plan(lazy) is used).

seed

(optional) A L'Ecuyer-CMRG RNG seed.

globals

A logical, a character vector, or a named list for controlling how globals are handled. For details, see below section.

persistent

If FALSE, the evaluation environment is cleared from objects prior to the evaluation of the future.

workers

The maximum number of multisession futures that can be active at the same time before blocking.

gc

If TRUE, the garbage collector run (in the process that evaluated the future) after the value of the future is collected.

earlySignal

Specified whether conditions should be signaled as soon as possible or not.

label

An optional character string label attached to the future.

...

Additional arguments passed to the "evaluator".

Value

A MultisessionFuture. If workers == 1, then all processing using done in the current/main R session and we therefore fall back to using a lazy future.

Known issues

In the current implementation, all background R sessions are allocated and launched in the background as soon as the first multisession future is created. This means that more R sessions may be running than what will ever be used. The reason for this is that background sessions are currently created using makeCluster(), which requires that all R sessions are created at once.

Details

This function will block if all available R session are occupied and will be unblocked as soon as one of the already running multisession futures is resolved. For the total number of R sessions available including the current/main R process, see availableCores(). A multisession future is a special type of cluster future. The preferred way to create an multisession future is not to call this function directly, but to register it via plan(multisession) such that it becomes the default mechanism for all futures. After this future() and %<-% will create multisession futures.

See Also

For processing in multiple forked R sessions, see multicore futures. For multicore processing with fallback to multisession where the former is not supported, see multiprocess futures. Use availableCores() to see the total number of cores that are available for the current R session.

Examples

## Use multisession futures
plan(multisession)

## A global variable
a <- 0

## Create multicore future (explicitly)
f <- future({
  b <- 3
  c <- 2
  a * b * c
})

## A multisession future is evaluated in a separate R session.
## 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)