| Version: | 0.10.1 |
| Depends: | future (≥ 1.49.0) |
| Imports: | mirai (≥ 2.2.0), parallelly, utils |
| Suggests: | future.tests, future.apply, listenv |
| Title: | A 'Future' API for Parallel Processing using 'mirai' |
| Description: | Implementation of the 'Future' API <doi:10.32614/RJ-2021-048> on top of the 'mirai' package <doi:10.5281/zenodo.7912722>. By using this package, you get to take advantage of the benefits of 'mirai' plus everything else that 'future' and the 'Futureverse' adds on top of it. It allows you to process futures, as defined by the 'future' package, in parallel out of the box, on your local machine or across remote machines. Contrary to back-ends relying on the 'parallel' package (e.g. 'multisession') and socket connections, 'mirai_cluster' and 'mirai_multisession', provided here, can run more than 125 parallel R processes. As a reminder, regardless which future backend is used by the user, the code does not have to change, it gives identical results, and behaves exactly the same. |
| License: | GPL (≥ 3) |
| Language: | en-US |
| Encoding: | UTF-8 |
| URL: | https://future.mirai.futureverse.org, https://github.com/futureverse/future.mirai |
| BugReports: | https://github.com/futureverse/future.mirai/issues |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-07-10 10:08:55 UTC; henrik |
| Author: | Henrik Bengtsson 
[aut, cre, cph],
Charlie Gao [ctb]
(note: For 'mirai'-related patches and implementing feature
requests in 'mirai') |
| Maintainer: | Henrik Bengtsson <henrikb@braju.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-07-10 10:30:01 UTC |
future.mirai: A Future API for Parallel Processing using 'mirai'
Description
The future.mirai package implements the Future API using the mirai package.
Author(s)
Maintainer: Henrik Bengtsson henrikb@braju.com (ORCID) [copyright holder]
Other contributors:
Charlie Gao charlie.gao@shikokuchuo.net (ORCID) (For 'mirai'-related patches and implementing feature requests in 'mirai') [contributor]
See Also
Useful links:
Report bugs at https://github.com/futureverse/future.mirai/issues
Examples
plan(mirai_multisession)
# A function that returns a future
# (note that N is a global variable)
f <- function() future({
4 * sum((runif(N) ^ 2 + runif(N) ^ 2) < 1) / N
}, seed = TRUE)
# Run a simple sampling approximation of pi in parallel using M * N points:
N <- 1e6 # samples per worker
M <- 10 # iterations
pi_est <- Reduce(sum, Map(value, replicate(M, f()))) / M
print(pi_est)
## Switch back to sequential processing, which also
## shuts down the automatically launched mirai workers
plan(sequential)
A future backend based based on the 'mirai' framework
Description
Set up the future parameters.
Usage
MiraiFutureBackend(...)
Arguments
... |
Additional arguments passed to |
Value
An object of class MiraiFutureBackend.
Mirai-based cluster futures
Description
WARNING: This function must never be called.
It may only be used with future::plan()
Usage
mirai_cluster(..., envir = parent.frame())
Arguments
envir |
The environment from where global objects should be identified. |
... |
Not used. |
Value
Nothing.
Examples
# Manually launch mirai workers
mirai::daemons(parallelly::availableCores())
plan(mirai_cluster)
# A function that returns a future
# (note that N is a global variable)
f <- function() future({
4 * sum((runif(N) ^ 2 + runif(N) ^ 2) < 1) / N
}, seed = TRUE)
# Run a simple sampling approximation of pi in parallel using M * N points:
N <- 1e6 # samples per worker
M <- 10 # iterations
pi_est <- Reduce(sum, Map(value, replicate(M, f()))) / M
print(pi_est)
## Switch back to sequential processing
plan(sequential)
## Shut down manually launched mirai workers
invisible(mirai::daemons(0))
Mirai-based localhost multisession futures
Description
WARNING: This function must never be called.
It may only be used with future::plan()
Usage
mirai_multisession(..., workers = availableCores(), envir = parent.frame())
Arguments
workers |
The number of parallel processes to use.
If a function, it is called without arguments when the future
is created and its value is used to configure the workers.
If |
envir |
The environment from where global objects should be identified. |
... |
Not used. |
Value
Nothing.
Examples
plan(mirai_multisession)
# A function that returns a future
# (note that N is a global variable)
f <- function() future({
4 * sum((runif(N) ^ 2 + runif(N) ^ 2) < 1) / N
}, seed = TRUE)
# Run a simple sampling approximation of pi in parallel using M * N points:
N <- 1e6 # samples per worker
M <- 10 # iterations
pi_est <- Reduce(sum, Map(value, replicate(M, f()))) / M
print(pi_est)
## Switch back to sequential processing, which also
## shuts down the automatically launched mirai workers
plan(sequential)
Check on the status of a future task.
Description
Check on the status of a future task.
Usage
## S3 method for class 'MiraiFuture'
resolved(x, ...)
Value
boolean indicating the task is finished (TRUE) or not (FALSE)