Like in decision tree we can see or visualize the node splits , I want to do something similar . But I am using SparkR and it does not have decision trees. So I am planning to use random forest with 1 tree as parameter and run on SparkR, then save the model and use getTree to see the node splits and further visualize using ggplot.
The short answer is no.
Models built with SparkR are not compatible with ones built with the respective R packages, in this case randomForest; hence, you will not be able to use the getTree function from the latter to visualize a tree from a random forest built with SparkR.
On a different level: I am surprised that decision trees have still not found their way into SparkR - they seem to be ready since several months now in the Github repo; but even when they are, they are not expected to offer methods for visualizing trees, and you will still not be able to use functions from other R packages for that purpose.