Learn R Programming

⚠️There's a newer version (1.11.2) of this package.Take me there.

future.apply (version 1.9.0)

Apply Function to Elements in Parallel using Futures

Description

Implementations of apply(), by(), eapply(), lapply(), Map(), .mapply(), mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster. These future_*apply() functions come with the same pros and cons as the corresponding base-R *apply() functions but with the additional feature of being able to be processed via the future framework.

Copy Link

Version

Install

install.packages('future.apply')

Monthly Downloads

205,321

Version

1.9.0

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Henrik Bengtsson

Last Published

April 25th, 2022

Functions in future.apply (1.9.0)

future_apply

Apply Functions Over Array Margins via Futures
future.apply

future.apply: Apply Function to Elements in Parallel using Futures
future_by

Apply a Function to a Data Frame Split by Factors via Futures
fold

Efficient Fold, Reduce, Accumulate, Combine of a Vector
makeChunks

Create Chunks of Index Vectors
future_Map

Apply a Function to Multiple List or Vector Arguments
future_eapply

Apply a Function over a List or Vector via Futures
future.apply.options

Options used for future.apply
make_rng_seeds

Produce Reproducible Seeds for Parallel Random Number Generation