future.apply v1.3.0

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by Henrik Bengtsson View Source

Apply Function to Elements in Parallel using Futures

Implementations of apply(), by(), eapply(), lapply(), Map(), 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.

Functions in future.apply

Name	Description
future_Map	Apply a Function to Multiple List or Vector Arguments
future_eapply	Apply a Function over a List or Vector via Futures
fold	Efficient Fold, Reduce, Accumulate, Combine of a Vector
future.apply	future.apply: Apply Function to Elements in Parallel using Futures
makeChunks	Create Chunks of Index Vectors
future_apply	Apply Functions Over Array Margins via Futures
make_rng_seeds	Produce Reproducible Seeds for Parallel Random Number Generation
future_by	Apply a Function to a Data Frame Split by Factors via Futures
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Vignettes of future.apply

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future.apply-1-overview.md.rsp
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Details

VignetteBuilder	R.rsp
License	GPL (>= 2)
LazyLoad	TRUE
URL	https://github.com/HenrikBengtsson/future.apply
BugReports	https://github.com/HenrikBengtsson/future.apply/issues
RoxygenNote	6.1.1
NeedsCompilation	no
Packaged	2019-06-18 03:07:59 UTC; hb
Repository	CRAN
Date/Publication	2019-06-18 05:10:07 UTC

suggests	datasets , listenv (>= 0.7.0) , markdown , R.rsp , stats , tools
depends	future (>= 1.13.0) , R (>= 3.2.0)
imports	globals (>= 0.12.4)
Contributors	R Core team