PySpark and AWS: Master Big Data with PySpark and AWS - Creating Spark DFs

The video tutorial explains the use of Spark with RDBMS, focusing on the creation and use of Spark contexts and sessions. It covers the differences between reading data with Spark context and Spark session, and how to handle Spark sessions in Databricks. The tutorial also demonstrates reading data from CSV and JSON files, and performing operations on data frames, highlighting the importance of specifying headers in data frames.

What are the steps to import Spark session in PySpark?

How does Spark handle existing Spark sessions when using 'getOrCreate'?

What is the output format when reading data from Spark session?

In what scenarios would you prefer using DataFrames over RDDs?