future (version 1.3.0)

multiprocess: Create a multiprocess future whose value will be resolved asynchronously using multicore or a multisession evaluation

Description

A multiprocess future is a future that uses multicore evaluation if supported, otherwise it uses multisession evaluation. Regardless, its value is computed and resolved in parallel in another process.

Usage

multiprocess(expr, envir = parent.frame(), substitute = TRUE,
  lazy = FALSE, seed = NULL, globals = TRUE, 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

If FALSE (default), the future is resolved eagerly (immediately), otherwise not.

seed

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

globals

(optional) a logical, a character vector, or a named list for controlling how globals are handled. For details, see section 'Globals used by future expressions' in the help for future().

workers

The maximum number of multiprocess 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.

...

Not used.

Value

A MultiprocessFuture implemented as either a MulticoreFuture or a MultisessionFuture.

See Also

Internally multicore() and multisession() are used.

Examples

## Use multiprocess futures
plan(multiprocess)

## A global variable
a <- 0

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

## A multiprocess future is evaluated in a separate R process.
## 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)