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future.apply

Apply Function to Elements in Parallel using Futures

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.

Functions (8)

fold

Efficient Fold, Reduce, Accumulate, Combine of a Vector

future.apply

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

future_apply

Apply Functions Over Array Margins via Futures

future_by

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

future_lapply

Apply a Function over a List or Vector via Futures

future_mapply

Apply a Function to Multiple List or Vector Arguments

makeChunks

Create Chunks of Index Vectors

make_rng_seeds

Produce Reproducible Seeds for Parallel Random Number Generation

future.apply

Apply Function to Elements in Parallel using Futures

v1.7.0
GPL (>= 2)
Authors
Henrik Bengtsson [aut, cre, cph], R Core Team [cph, ctb]
Initial release

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