future.apply v1.3.0

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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

Name
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

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