future (version 1.0.1)

cluster: Create a cluster future whose value will be resolved asynchroneously in a parallel process

Description

A cluster future is a future that uses cluster evaluation, which means that its value is computed and resolved in parallel in another process.

Usage

cluster(expr, envir = parent.frame(), substitute = TRUE, persistent = FALSE, workers = NULL, gc = FALSE, earlySignal = FALSE, ...)

Arguments

expr

An R expression.

envir

The environment in which the evaluation is done and from which globals are obtained.

substitute

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

persistent

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

workers

A cluster object created by makeCluster().

gc

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

earlySignal

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

...

Not used.

Value

A ClusterFuture.

Details

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 %<=%< a=""> will create cluster futures.

Examples

## Cluster futures gives an error on R CMD check on
## Windows (but not Linux or OS X) for unknown reasons.
## The same code works in package tests.


## Use cluster futures
cl <- parallel::makeCluster(2L)
plan(cluster, workers=cl)

## A global variable
a <- 0

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

## A cluster future is evaluated in a separate 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)

## CLEANUP
parallel::stopCluster(cl)