Execute f in parallel partiation by partition_column, see partition_tables for details.

execute_parallel(tables, f, partition_column, ..., cl = NULL, debug = FALSE,
  env = parent.frame())

Arguments

tables

named map of tables to use.

f

function to apply to each tableset signature is function takes a single argument that is a named list of data.frames.

partition_column

character name of column to partition on

...

force later arguments to bind by name.

cl

parallel cluster.

debug

logical if TRUE use lapply instead of parallel::clusterApplyLB.

env

environment to look for values in.

Value

list of f evaluations.

See also

Examples

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) }
#> x g s #> 1.1 1 1 1.000000 #> 1.2 2 1 1.414214 #> 2.1 3 2 1.732051 #> 2.2 4 2 2.000000 #> 2.3 5 2 2.236068