future (version 1.13.0)

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.

envir

The environment from where global objects should be identified.

substitute

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

lazy

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

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 future().

workers

A positive numeric scalar or a function specifying the maximum number of parallel futures that can be active at the same time before blocking. If a function, it is called without arguments when the future is created and its value is used to configure the workers. The function should return a numeric scalar.

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 is TRUE (more frequently) or FALSE (less frequently). Some types of futures ignore this argument.

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 Future().

Value

A MultiprocessFuture implemented as either a MulticoreFuture or a MultisessionFuture.

See Also

Internally multicore() and multisession() are used.

Examples

# NOT RUN {
## 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)

# }

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