R and Python are like bread and butter for a data scientist. Modern frameworks tend to be interoperable and borrow from each other's strength. In this chapter, I went over the plumbing of interoperability with R and Python. Both of them have packages (R) and modules (Python) that became very popular and extend the current Scala/Spark functionality. Many consider R and Python existing libraries to be crucial for their implementations.

This chapter demonstrated a few ways to integrate these packages and provide the tradeoffs of using these integrations so that we can proceed on to the next chapter, looking at the NLP, where functional programming has been traditionally used from the start.