Apache Spark Certification Practice Test

The reason C++ is not considered a primary language used for coding in Apache Spark revolves around the framework's design and its ecosystem. Apache Spark is fundamentally built on Scala, which is a language that runs on the Java Virtual Machine (JVM). Scala is often the most common language used in the Spark community due to its functional programming features that seamlessly integrate with Spark's architecture.

Java is also heavily utilized for Spark programming because of its inherent compatibility with Scala, as they both run on the JVM. Many Spark APIs are available in Java, making it a popular choice for developers already familiar with Java. Python has gained immense popularity as well, especially with the advent of PySpark, which provides an interface for Apache Spark in Python. This has made Spark accessible for data scientists and analysts who prefer Python's simplicity and widespread use in data analysis and machine learning.

In contrast, while C++ is a powerful programming language used widely in systems programming and applications requiring high performance, it does not have support within the Spark framework. Apache Spark does not provide bindings or APIs for C++, making it unsuitable for direct use with Spark compared to the other mentioned languages. Thus, it's clear why C++ stands out as not being a language used to code in Spark.