cluster_utils: Cluster utitility functions

cluster_utilsR Documentation

Cluster utitility functions


These functions provide useful helpers for performaning common operations. 'cluster_assign()' assigns the same value on each worker; 'cluster_assign_each()' assigns different values on each worker; 'cluster_assign_partition()' partitions vectors so that each worker gets (approximately) the same number of pieces.


cluster_assign(.cluster, ...)

cluster_assign_each(.cluster, ...)

cluster_assign_partition(.cluster, ...)

cluster_copy(cluster, names, env = caller_env())

cluster_rm(cluster, names)

cluster_library(cluster, packages)



Name-value pairs

cluster, .cluster

Cluster to work on


Name of variables to copy.


Environment in which to look for varibles to copy.


Character vector of packages to load


Functions that modify the worker environment invisibly return 'cluster' so calls can be piped together. The other functions return lists with one element for each worker.


cl <- default_cluster()
cluster_assign(cl, a = runif(1))
cluster_call(cl, a)

# Assign different values on each cluster
cluster_assign_each(cl, b = c(1, 10))
cluster_call(cl, b)

# Partition a vector so that each worker gets approximately the
# same amount of it
cluster_assign_partition(cl, c = 1:11)
cluster_call(cl, c)

# If you want different to compute different values on each
# worker, use `cluster_call()` directly:
cluster_call(cl, d <- runif(1))
cluster_call(cl, d)

# cluster_copy() is a useful shortcut
e <- 10
cluster_copy(cl, "e")

cluster_call(cl, ls())
cluster_rm(cl, letters[1:5])
cluster_call(cl, ls())

# Use cluster_library() to load packages
cluster_call(cl, search())
cluster_library(cl, "magrittr")
cluster_call(cl, search())

multidplyr documentation built on Sept. 27, 2022, 1:06 a.m.