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Execute f in parallel partitioned by partition_column
, see
partition_tables
for details.
execute_parallel(
tables,
f,
partition_column,
...,
cl = NULL,
debug = FALSE,
env = parent.frame()
)
list of f evaluations.
named map of tables to use.
function to apply to each tableset signature is function takes a single argument that is a named list of data.frames.
character name of column to partition on
force later arguments to bind by name.
parallel cluster.
logical if TRUE use lapply instead of parallel::clusterApplyLB.
environment to look for values in.
partition_tables
if(requireNamespace("parallel", quietly = TRUE)) {
cl <- parallel::makeCluster(2)
d <- data.frame(x = 1:5, g = c(1, 1, 2, 2 ,2))
f <- function(dl) {
d <- dl$d
d$s <- sqrt(d$x)
d
}
r <- execute_parallel(list(d = d), f,
partition_column = "g",
cl = cl) %.>%
do.call(rbind, .) %.>%
print(.)
parallel::stopCluster(cl)
}
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