Reputation: 67
I'm a beginner to parallel computing in R. I came across the doParallel
package and I thought it might be useful in my case.
The following code aims at evaluating in parallel several pglm
regressions:
require("foreach")
require("doParallel")
resVar <- sample(1:6,100,TRUE)
x1 <- 1:100
x2 <- rnorm(100)
x3 <- rchisq(100, 2, ncp = 0)
x4 <- rweibull(100, 1, scale = 1)
Year <- sample(2011:2014,100,replace=TRUE)
X <- data.frame(resVar,x1,x2,x3,x4,Year)
facInt = 1:4 # no factors
#find all possible combinations
cmbList <- lapply(2, function(nbFact) {
allCmbs <- t(combn(facInt, nbFact))
dupCmbs <- combn(1:4, nbFact, function(x) any(duplicated(x)))
allCmbs[!dupCmbs, , drop = FALSE] })
noSubModel <- c(0, sapply(cmbList, nrow))
noModel <- sum(noSubModel)
combinations <- cmbList[[1]]
factors <- X[,c("x1","x2","x3","x4")]
coeff_vars <- matrix(colnames(factors)[combinations[1:length(combinations[,1]),]],ncol = length(combinations[1,]))
yName <- 'resVar'
cl <- makeCluster(4)
registerDoParallel(cl)
r <- foreach(subModelInd=1:noSubModel[2], .combine=cbind) %dopar% {
require("pglm")
vars <- coeff_vars[subModelInd,]
formula <- as.formula(paste('as.numeric(', yName, ')',' ~ ', paste(vars,collapse=' + ')))
XX<-X[,c("resVar",vars,"Year")]
ans <- pglm(formula, data = XX, family = ordinal('logit'), model = "random", method = "bfgs", print.level = 3, R = 5, index = 'Year')
coefficients(ans)
}
stopCluster(cl)
cl <- c()
When I try to parallelise it in the following way, it doesn't work. I get the following error:
Error in { : task 1 failed - "object 'XX' not found"
A set of several pglm
regressions sequentially evaluated works:
require("pglm")
r <- foreach(icount(subModelInd), .combine=cbind) %do% {
vars <- coeff_vars[subModelInd,]
formula <- as.formula(paste('as.numeric(', yName, ')',' ~ ', paste(vars,collapse=' + ')))
XX<-X[,c("resVar",vars,"Year")]
ans <- pglm(formula, data = XX, family = ordinal('logit'), model = "random", method = "bfgs", print.level = 3, R = 5, index = 'Year')
coefficients(ans)
}
Can someone please advice on how to parallelise this task correctly?
Thanks!
Upvotes: 3
Views: 137
Reputation: 3253
Yes, it does look like there is an issue with pglm
and the way it accesses variables. A simple fix is to assign the XX
into global variable, i.e. change the
XX<-X[,c("resVar",vars,"Year")]
to
assign("XX", X[,c("resVar",vars,"Year")], pos = 1)
This should do the trick, as each cluster runs as a separate process (not a separate thread as far as I know), so you won't have issue with two processes/threads trying to use the XX
variable.
I added two extra lines - a set.seed(131)
and another line after coefficients(ans)
,i.e.
set.seed(131)
... rest of your code ....
coefficients(ans)
write(paste0(coefficients(ans)[1],"\n"),file="c:\\temp\\r\\out.txt",append=TRUE)
and got consistently 6 lines in the file (same numbers, but obviously in different order):
0.703727602527463
1.03799340156792
1.15220874833614
1.30381769320552
1.42656613017171
1.77287504108163
That should work for you as well.
Upvotes: 3