doFuture: Foreach Parallel Adapter using Futures

The doFuture package provides mechanisms for using the foreach package together with the future package such that foreach() parallelizes via any future backend.

Usage

There are two alternative ways to use this package:

1. y <- foreach(...) %dofuture% { ... }

2. y <- foreach(...) %dopar% { ... } with registerDoFuture()

The first alternative (recommended), which uses %dofuture%, avoids having to use registerDoFuture(). The %dofuture% operator provides a more consistent behavior than %dopar%, e.g. there is a unique set of foreach arguments instead of one per possible adapter. Identification of globals, random number generation (RNG), and error handling is handled by the future ecosystem, just like with other map-reduce solutions such as future.apply and furrr. An example is:

library(doFuture)
plan(multisession)

y <- foreach(x = 1:4, y = 1:10) %dofuture% {
  z <- x + y
  slow_sqrt(z)
}

This alternative is the recommended way to let foreach() parallelize via the future framework if you start out from scratch.

See %dofuture% for more details and examples on this approach.

The second alternative is based on the traditional foreach approach where one registers a foreach adapter to be used by %dopar%. A popular adapter is doParallel::registerDoParallel(), which parallelizes on the local machine using the parallel package. This package provides registerDoFuture(), which parallelizes using the future package, meaning any future-compliant parallel backend can be used. An example is:

library(doFuture)
registerDoFuture()
plan(multisession)

y <- foreach(x = 1:4, y = 1:10) %dopar% {
  z <- x + y
  slow_sqrt(z)
}

This alternative is useful if you already have a lot of R code that uses %dopar% and you just want to switch to using the future framework for parallelization. Using registerDoFuture() is also useful when you wish to use the future framework with packages and functions that uses foreach() and %dopar% internally, e.g. caret, plyr, NMF, and glmnet. It can also be used to configure the Bioconductor BiocParallel package, and any package that rely on it, to parallelize via the future framework.

See registerDoFuture() for more details and examples on this approach.