What is structured data? Basically, it means that when we extend the concept of an RDD to a DataFrame object, we provide the data in the RDD with some structure.

One way to think of it is that it's fundamentally an RDD of row objects. By doing this, we can construct SQL queries. We can have distinct columns in these rows, and we can actually form SQL queries and issue commands in a SQL-like style, which we'll see shortly. Because we have an actual schema associated with the DataFrame, it means that Spark can actually do even more optimization than what it normally would. So, it can do query optimization, just like you would on a SQL database, when it tries to figure out the optimal plan for executing your Spark script. Another nice thing is that you can directly read and write to JSON files or JDBC-compiled and compliant databases. This means that if you do have your source data that's already in a structured format, for example, inside a relational database or inside...