Run a for Loop in Parallel in R
I Have a for Loop That Is Something Like This: for (I=1:150000) { tempMatrix = {} tempMatrix = functionThatDoesSomething() #Calling a Function finalMatrix =...
I have a for loop that is something like this:
for (i=1:150000) {
tempMatrix = {}
tempMatrix = functionThatDoesSomething() #calling a function
finalMatrix = cbind(finalMatrix, tempMatrix)
}
Could you tell me how to make this parallel ?
I tried this based on an example online, but am not sure if the syntax is correct. It also didn't increase the speed much.
finalMatrix = foreach(i=1:150000, .combine=cbind) %dopar% {
tempMatrix = {}
tempMatrix = functionThatDoesSomething() #calling a function
cbind(finalMatrix, tempMatrix)
}
1 Answer
Thanks for your feedback. I did look up parallel after I posted this question.
Finally after a few tries, I got it running. I have added the code below in case it is useful to others
library(foreach)
library(doParallel)
#setup parallel backend to use many processors
cores=detectCores()
cl <- makeCluster(cores[1]-1) #not to overload your computer
registerDoParallel(cl)
finalMatrix <- foreach(i=1:150000, .combine=cbind) %dopar% {
tempMatrix = functionThatDoesSomething() #calling a function
#do other things if you want
tempMatrix #Equivalent to finalMatrix = cbind(finalMatrix, tempMatrix)
}
#stop cluster
stopCluster(cl)
Note - I must add a note that if the user allocates too many processes, then user may get this error: Error in serialize(data, node$con) : error writing to connection
Note - If .combine in the foreach statement is rbind , then the final object returned would have been created by appending output of each loop row-wise.
Hope this is useful for folks trying out parallel processing in R for the first time like me.
References:
Maya is a hardware enthusiast who tests and reviews smart home devices, smartphones, wearables, and audio gear. She focuses on practical consumer value and build quality.
