If you have worked with Java and Python, you can’t have the same expectations from Apache Spark, since it is not a programming language. It is a data processing engine that is compatible with any situation and is available to use. The primary use of Spark stretches mainly to Big Data processing, keeping factors like scalability and speed in mind. Data analysts, engineers, and application developers use Spark every day to create queries and to transform data. ETL and EQL are some of the batch jobs that frequently take place in Apache Spark mainly for data processing. Spark is built on top of the Hadoop/HDFS framework that supervises and handles data supervision. This is done using Scala, which is a slightly functional alternative to Java. Spark also supports many programming languages like Python, Scala, and R.