One of the reasons I switched to using Jupyter over R/RStudio directly was the native rendering of notebooks on GitHub, which made it pretty (example of mine: https://github.com/minimaxir/stack-overflow-survey/blob/mast...)
The addition of native R notebooks may make me switch back, although I'll have to experiment on the differences between Jupyter Notebook rendering and .Rmd rendering on GitHub. (and since the notebooks are theoretically language agnostic, it might be fun to experiment with Python code too!)
Native sparklyr is something I'll also have to research/experiment with, since according to the official Spark documentation, although R has first class support with Spark, there is not API parity with Python + Spark, for example. (although, sparklyr has most of the important transformers/models so it is definitely worth a look: http://spark.rstudio.com/mllib.html)