parallel computations on Reference Classes

Question

I have a list of fairly large objects that I want to apply a complicated function to in parallel, but my current method uses too much memory. I thought Reference Classes mi

Answer 1

I think the forked processes, while they have access to all the variables in the workspace, must not be able to change them. This works, but I don't know yet if it improves the memory issues or not.

foo <- mclapply(foo, function(x) {x$reset(); x})
foo[[4]]$balance
## 0