Apache Spark Certification Practice Test

Spark applications can be built using Java, Scala, and Python, which are the primary languages supported by Apache Spark. Java and Scala are particularly integral because Spark is written in Scala, and thus, it seamlessly integrates with Java's ecosystem. Python has become a popular choice due to its simplicity and the powerful libraries available for data manipulation and analysis.

Each of these programming languages offers distinct advantages. For example, Scala provides strong static typing and functional programming capabilities, making it very effective for complex data processing tasks. Java has widespread use in enterprise applications and provides extensive resources and libraries. Python, on the other hand, is user-friendly and has a strong community, which accelerates development time, especially for data analytics applications.

Other programming languages like C++ and Ruby are not natively supported in Spark, making the core interaction between Spark and them less efficient or, in many cases, impossible. Additionally, while Hadoop supports various languages under its ecosystem, that does not directly translate to Spark's capabilities since Spark operates independently and has its designated languages.