The future.mapreduce package provides utility functions for other packages implementing map-reduce APIs on top of the future framework. Specifically, it will provide general functions for “load balancing”, that is, methods for partitioning the elements to iterate over into chunks so that each chunk is processed by a single futures. Load balancing helps lower the overhead in parallel processing that comes from communicating with and orchestrating parallel workers. It will provide methods for common tasks such as globals handling and critical tasks such as parallel RNG in map-reduce contexts.

WARNING: This package is currently under development. Please stay tuned.

This will benefit existing map-reduce packages future.apply, furrr, and doFuture, but also other similar efforts. This will further simply the implementing of these existing solutions as well as other future-based map-reduce APIs that might be on the horizon.


  • Migrate core functions from future.apply and doFuture to future.mapreduce

  • Only export a minimal API and keep most functions internal for now

  • Update future.apply and doFuture to import (also internal functions) from future.mapreduce

  • Submit future.mapreduce to CRAN with a warning that the API is under development and should not be used by other packages than future.apply and doFuture until further notice

  • Submit updated versions of future.apply and doFuture

  • Work with furrr to make use of future.mapreduce

  • When the internal API has stabilized, export it and submit to CRAN


R package future.mapreduce is only available via GitHub and can be installed in R as:

remotes::install_github("HenrikBengtsson/future.mapreduce", ref="master")

Pre-release version

To install the pre-release version that is available in Git branch develop on GitHub, use:

remotes::install_github("HenrikBengtsson/future.mapreduce", ref="develop")

This will install the package from source.