Switching to using DataFrames does not mean we need to completely abandon RDDs. Under the hood, DataFrames still use RDDs, but of Row(...) objects, as explained earlier. In this recipe, we will learn how to interact with the underlying RDD of a DataFrame.
Accessing underlying RDDs
Getting ready
To execute this recipe, you need to have a working Spark 2.3 environment. Also, you should have already gone through the previous recipe as we will reuse the data we created there.
There are no other requirements.
How to do it...
In this example, we will extract the size of the...
