Beyond a time-bounded interaction, SparkSession provides a single point of entry to interact with underlying Spark functionality and allows programming Spark with DataFrame and Dataset APIs. Most importantly, it curbs the number of concepts and constructs a developer has to juggle while interacting with Spark.
In this blog and its accompanying Databricks notebook, we will explore SparkSession functionality in Spark 2.0.
This looks to be an easier method for integrating various parts of Spark in one user session. Read the whole thing.