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future (version 1.18.0)

Unified Parallel and Distributed Processing in R for Everyone

Description

The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.

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Install

install.packages('future')

Monthly Downloads

320,568

Version

1.18.0

License

LGPL (>= 2.1)

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Maintainer

Henrik Bengtsson

Last Published

July 9th, 2020

Functions in future (1.18.0)

FutureResult

Results from resolving a future
MultiprocessFuture-class

An multiprocess future is a future whose value will be resolved asynchronously in a parallel process
UniprocessFuture-class

An uniprocess future is a future whose value will be resolved synchronously in the current process
Future-class

A future represents a value that will be available at some point in the future
FutureCondition

A condition (message, warning, or error) that occurred while orchestrating a future
ClusterFuture-class

A cluster future is a future whose value will be resolved asynchronously in a parallel process
ConstantFuture-class

A future with a constant value
as.cluster

Coerce an object to a cluster object
MulticoreFuture-class

An multicore future is a future whose value will be resolved asynchronously in a parallel process
FutureGlobals

A representation of a set of globals used with futures
autoStopCluster

Automatically stop a cluster when garbage collected
future

Create a future
cluster

Create a cluster future whose value will be resolved asynchronously in a parallel process
%conditions%

Control whether standard output should be captured or not
find_references

Get first or all references of an R object
find_rshcmd

Search for SSH clients on the current system
availableCores

Get number of available cores on current machine
availableWorkers

Get set of available workers
clusterExportSticky

Export globals to the sticky-globals environment of the cluster nodes
futureOf

Get the future of a future variable
getExpression

Inject code for the next type of future to use for nested futures
getGlobalsAndPackages

Retrieves global variables of an expression and their associated packages
future.options

Options used for futures
%label%

Specify label for a future assignment
resolved

Check whether a future is resolved or not
makeClusterMPI

Create a Message Passing Interface (MPI) cluster of R workers for parallel processing
backtrace

Back trace the expressions evaluated when an error was caught
result.Future

Get the results of a resolved future
makeClusterPSOCK

Create a PSOCK cluster of R workers for parallel processing
multisession

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

Specify globals and packages for a future assignment
make_rng_seeds

Produce Reproducible Seeds for Parallel Random Number Generation
values

Get all values in a container
value.Future

The value of a future
%plan%

Use a specific plan for a future assignment
signalConditions

Signals Captured Conditions
sessionDetails

Outputs details on the current R session
nbrOfWorkers

Get the number of workers available
multicore

Create a multicore future whose value will be resolved asynchronously in a forked parallel process
%seed%

Set random seed for future assignment
multiprocess

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

Get all futures in a container
resolve

Resolve one or more futures synchronously
resetWorkers

Free up active background workers
sequential

Create a sequential future whose value will be in the current R session
pid_exists

Check whether a process PID exists or not
run.Future

Run a future
mandelbrot

Mandelbrot convergence counts
nullcon

Creates a connection to the system null device
%stdout%

Control whether standard output should be captured or not
%lazy%

Control lazy / eager evaluation for a future assignment
plan

Plan how to resolve a future
sticky_globals

Place a sticky-globals environment immediately after the global environment
%tweak%

Temporarily tweaks the arguments of the current strategy
.length

Gets the length of an object without dispatching
supportsMulticore

Check whether multicore/forked processing is supported or not
remote

Create a remote future whose value will be resolved asynchronously in a remote process
tweak

Tweak a future function by adjusting its default arguments
requestCore

Request a core for multicore processing
usedCores

Get number of cores currently used