Exploring the movies data details for the recommendation system in Spark 2.0

In this recipe, we will begin to explore the movie data file by parsing data into a Scala case class and generating a simple metric. The key here is to acquire an understanding of our data, so in the later stages, if nebulous results arise, we will have some insight to make an informed conclusion about the correctness of our results.

This is the first of the two recipes which explore the movie dataset. Data exploration is an important first step in statistical analysis and machine learning.

One of the best ways to understand the data quickly is to generate a data visualization of it, and we will use JFreeChart to do that. It is very important to make sure you feel comfortable with the data and understand firsthand what is in each file, and the story it tries to tell.

We must always explore, understand, and visualize the data before we do anything else. Most performances and misses with ML and others systems can be...