The code below shows that
(1) the way to activate the parallel backend indeed is to use 'registerDoMC'
(2) the function d_ply does NOT accept the argument parallel, while the
function ddply does. Perhaps it is interesting to add this feature to d_ply,
l_ply and a_ply too? As a workaround one can off course use the function
ddply with a dummy return value.
# df & function
myDf = data.frame(a=factor(1:10), b=factor(1:10), c=1:10)
tryFun1 = function(myDf){
Sys.sleep(1)
return(mean(myDf$c))
}
# ddply
ddply(.data=myDf, .variables=c('a', 'b'), .fun=tryFun, .progress='text')
registerDoMC()
getDoParWorkers()
ddply(.data=myDf, .variables=c('a', 'b'), .fun=tryFun, .progress='text',
.parallel=TRUE)
# d_ply
d_ply(.data=myDf, .variables=c('a', 'b'), .fun=tryFun, .progress='text')
registerDoMC()
d_ply(.data=myDf, .variables=c('a', 'b'), .fun=tryFun, .progress='text',
.parallel=TRUE)
Greetz,
Adi
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