For performing interactive data cleaning, processing, munging, and analysis, many data scientists use R or Python as their favorite tool. However, there are many data scientists who tend to get very attached to their favorite tool--that is, Python or R and try to solve all data analytics problems or jobs using that tool. Thus, introducing them to a new tool can be very challenging in most circumstances as the new tool has more syntax and a new set of patterns to learn before using the new tool to solve their purpose.
There are other APIs in Spark written in Python and R such as PySpark and SparkR respectively that allow you to use them from Python or R. However, most Spark books and online examples are written in Scala. Arguably, we think that learning how to work with Spark using the same language on which the Spark code has been written...
