small change to attempt to stop tempfile() problems in larger documents.

[abelew]

Greetings, When knitting larger documents with many images I sometimes get tempfile errors saying it ran out of files. When I looked more closely, it seemed to me that tempfile() was just not trying very hard; so I hacked a quick md5 tempfile generator which in theory takes all the same arguments as base::tempfile(). I was thinking to make it more robust and use some actual pseudorandomly generated material, but this seems to have worked fine for all of my largest and most troublesome documents.

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[abelew]

I think I replied via email, but the following is an example more similar to what happens in my documents and shows that you only need ~ 30 plots (at least in my hands) to hit a duplicate tmpnam:

library(parallel)
library(doParallel)
library(iterators)
library(foreach)
iterators <- 10
returns <- c()
## I haven't used parallel in a while, I can't remember if it is like make -j and I can't remember if returns or res gets the result back...
cl <- parallel::makeCluster(iterators + 1)
registered <- doParallel::registerDoParallel(cl)
res <- foreach(c = 1:(iterators * 10)) %dopar% {
  filename <- tempfile()
  returns <- c(returns, filename)
}
stopped <- parallel::stopCluster(cl)
table(duplicated(unlist(res)))

[yihui]

Sorry but I don't quite understand the code since I'm not familiar with these packages. In particular, I don't understand what returns <- c(returns, filename) is trying to do. sapply(res, duplicated) is all FALSE, and I don't know what duplicated(unlist(res)) implies.

Anyway, it will be clearer if you can show a minimal reproducible example that actually uses knitr.