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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.
multiprocess(expr, envir = parent.frame(), substitute = TRUE,
lazy = FALSE, seed = NULL, globals = TRUE,
workers = availableCores(), gc = FALSE, earlySignal = FALSE,
label = NULL, ...)
An R expression.
The environment from where global objects should be identified.
If TRUE, argument expr
is
substitute()
:ed, otherwise not.
If FALSE
(default), the future is resolved
eagerly (starting immediately), otherwise not.
(optional) A L'Ecuyer-CMRG RNG seed.
(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()
.
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.
If TRUE, the garbage collector run (in the process that evaluated the future) after the value of the future is collected. Some types of futures ignore this argument.
Specified whether conditions should be signaled as soon as possible or not.
An optional character string label attached to the future.
Additional named elements passed to Future()
.
A MultiprocessFuture implemented as either a MulticoreFuture or a MultisessionFuture.
Internally multicore()
and multisession()
are used.
# 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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