Package: multidplyr 0.1.4.9000

Hadley Wickham

multidplyr: A Multi-Process 'dplyr' Backend

Partition a data frame across multiple worker processes to provide simple multicore parallelism.

Authors:Hadley Wickham [aut, cre], Posit Software, PBC [cph, fnd]

multidplyr_0.1.4.9000.tar.gz
multidplyr_0.1.4.9000.zip(r-4.7)multidplyr_0.1.4.9000.zip(r-4.6)multidplyr_0.1.4.9000.zip(r-4.5)
multidplyr_0.1.4.9000.tgz(r-4.6-any)multidplyr_0.1.4.9000.tgz(r-4.5-any)
multidplyr_0.1.4.9000.tar.gz(r-4.7-any)multidplyr_0.1.4.9000.tar.gz(r-4.6-any)
multidplyr_0.1.4.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
multidplyr/json (API)
NEWS

# Install 'multidplyr' in R:
install.packages('multidplyr', repos = c('https://tidyverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tidyverse/multidplyr/issues

Pkgdown/docs site:https://multidplyr.tidyverse.org

On CRAN:

Conda:

dplyrmultiprocess

10.67 score 649 stars 5 packages 542 scripts 1.1k downloads 1 mentions 13 exports 23 dependencies

Last updated from:e960a1e83f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK142
source / vignettesOK196
linux-release-x86_64OK155
macos-release-arm64OK89
macos-oldrel-arm64OK83
windows-develOK101
windows-releaseOK106
windows-oldrelOK88
wasm-releaseOK109

Exports:%>%cluster_assigncluster_assign_eachcluster_assign_partitioncluster_callcluster_copycluster_librarycluster_rmcluster_senddefault_clusternew_clusterpartitionparty_df

Dependencies:callrclicrayondplyrgenericsgluelifecyclemagrittrpillarpkgconfigprocessxpsqs2R6RcppRcppParallelrlangstringfishtibbletidyselectutf8vctrswithr

An introduction to multidplyr

Rendered frommultidplyr.Rmdusingknitr::rmarkdownon May 24 2026.

Last update: 2021-02-03
Started: 2015-11-10

Readme and manuals

Help Manual

Help pageTopics
Call a function on each node of a clustercluster_call cluster_send
Cluster utitility functionscluster_assign cluster_assign_each cluster_assign_partition cluster_copy cluster_library cluster_rm cluster_utils
Create a new cluster with sensible defaults.new_cluster
Partition data across workers in a clusterpartition
A `party_df` partitioned data frameparty_df