R Language Parallel processing mcparallelDo
Example
The mcparallelDo package allows for the evaluation of R code asynchronously on Unix-alike (e.g. Linux and MacOSX) operating systems. The underlying philosophy of the package is aligned with the needs of exploratory data analysis rather than coding. For coding asynchrony, consider the future package.
Example
Create data
data(ToothGrowth)
Trigger mcparallelDo to perform analysis on a fork
mcparallelDo({glm(len ~ supp * dose, data=ToothGrowth)},"interactionPredictorModel")
Do other things, e.g.
binaryPredictorModel <- glm(len ~ supp, data=ToothGrowth)
gaussianPredictorModel <- glm(len ~ dose, data=ToothGrowth)
The result from mcparallelDo returns in your targetEnvironment, e.g. .GlobalEnv, when it is complete with a message (by default)
summary(interactionPredictorModel)
Other Examples
# Example of not returning a value until we return to the top level
for (i in 1:10) {
if (i == 1) {
mcparallelDo({2+2}, targetValue = "output")
}
if (exists("output")) print(i)
}
# Example of getting a value without returning to the top level
for (i in 1:10) {
if (i == 1) {
mcparallelDo({2+2}, targetValue = "output")
}
mcparallelDoCheck()
if (exists("output")) print(i)
}
