Yes, there is a difference between the sparkContext, javaSparkContext, SQLContext and SparkSession.
Let me answer your question one by one.
sparkContext is a Scala implementation entry point and JavaSparkContext is a java wrapper of sparkContext.
SQLContext is entry point of SparkSQL which can be received from sparkContext.Prior to 2.x.x, RDD ,DataFrame and Data-set were three different data abstractions.Since Spark 2.x.x, All three data abstractions are unified and SparkSession is the unified entry point of Spark.
An additional note is, RDD meant for unstructured data, strongly typed data and DataFrames are for structured and loosely typed data.
Is there any method to convert or create Context using Sparksession ?
yes. its sparkSession.sparkContext() and for SQL, sparkSession.sqlContext()
Can I completely replace all the Context using one single entry SparkSession ?
yes. you can get respective contexs from sparkSession.
Does all the functions in SQLContext, SparkContext,JavaSparkContext etc are added in SparkSession?
Not directly. you got to get respective context and make use of it.something like backward compatibility
How to use such function in SparkSession?
get respective context and make use of it.
How to create the following using SparkSession?
RDD can be created from sparkSession.sparkContext.parallelize()
JavaRDD same applies with this but in java implementation
JavaPairRDD sparkSession.sparkContext.parallelize().map(//making your data as key-value pair here is one way)
Dataset what sparkSession returns is Dataset if it is structured data.
Hope this will help you a lot.
