You can use an R 'transform' function to transform the data and pass that function to the RevoScaleR 'rxDataStepXdf()' function. You can then use the newly created, subset .xdf file with other RevoScaleR functions. Below is a sample R script that creates a new .xdf file by randomly sampling a larger .xdf file using the hidden row selection variable available in 'transformFunc'.
# Create a transformFunc that selects 25% of the data at random
set.seed(13)
xform <- function(data) {
data$.rxRowSelection<-as.logical(rbinom(length(data[[1]]),1,.25))
return(data)
}
rxDataStepXdf(inFile=inFile, outFile="sampledData.xdf", transformFunc=xform, overwrite=TRUE)
# check that subsetting was done and the row selection variable is not kept in the data set.
rxGetInfoXdf(inFile)
rxGetInfoXdf("sampledData.xdf")
