Once you've finished the Apache Spark in 5 Minutes notebook, navigate back to the Zeppelin Dashboard.
Next what we'll do is look at a set of data that has information regarding air flight status.
Select the next lab notebook from Labs > Spark 2.x > Data Worker > Scala > 101 - Intro to SparkSQL
Once you load an interpreter into memory it can persist which helps with subsequent loading times.
It's a good practice to restart some of the interpreters between execution of notebooks.
It not already expanded, expand the Interpreter Binding section at the top, restart the spark2 interpreter, and click Save.
Zeppelin Notebooks are fluid and interactive. They can be modified on the fly and checked into version control.
Before we can continue, we'll need to modify one of these paragraphs.
Expand the Code Block for the Create a DataFrame for CSV file paragraph and remove the /airflightsdelays subdirectory.
Once you've modified the Create a DataFrame from CSV file code block, it should look like this.
Press the Play button on this paragraph, and continue to complete the rest of this notebook and onto the next exercise.