FAQ’S on SparkSession:
What is SparkSession in PySpark?
SparkSession is the entry point to programming with Spark. It’s a unified interface for interacting with Spark functionality, allowing you to create DataFrames, perform SQL operations, and manage resources in Spark applications.
What is the difference between SparkContext and SparkSession?
SparkContext (`sc`) was the entry point to Spark before Spark 2.0, primarily used for RDD-based programming. SparkSession (`spark`) introduced in Spark 2.0 unifies various Spark APIs, including DataFrames, SQL, and Streaming. SparkSession internally encapsulates SparkContext.
Why is SparkSession used in PySpark applications?
SparkSession simplifies the interaction with Spark by providing a unified entry point for working with DataFrames, SQL queries, and other Spark functionalities. It manages the underlying SparkContext and enables better optimization and management of resources.
How do I access the default SparkSession in PySpark?
In interactive shells like PySpark, the default SparkSession is available as `spark` without needing to create it explicitly. However, in scripts or applications, you can create a new SparkSession using `SparkSession.builder` and assign it to a variable named `spark`.
