I have a problem with appending values to a data frame using parallel processing.

I have a function that will do some calculation and return a dataframe, including these calculation is a random sampling.

so what i did is :

randomizex <- function(testdf)
{
    foreach(ind=1:1000)%dopar%
    {
      testdf$X = sample(testdf$X,nrow(testdf), replace=FALSE)
      fit = lm(X ~ Y, testdf)
      newdf <- rbind(newdf, data.frame(pc=ind, err=sum(residuals(fit)^2) ))

    }

return(newdf)
}
resdf = randomizex(mydf)

when i view the result of resdf, it's empty

if i replace %dopar% with %do% the result is calculated correctly but it's too slow ..

is there anyway to boost this a bit ??

r foreach parallel-processing
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