Apache Spark Certification Practice Test

The correct answer is based on how Spark operates in a distributed environment. When code is sent to the executors, what is passed to the SparkContext generally includes the actual code that needs to be executed. This encompasses both JAR files containing compiled Java or Scala code, and Python code scripts, which can be executed in a PySpark environment.

SparkContext is responsible for coordinating the execution of a Spark job. When you submit a job, it packages the relevant code and sends it to the executors, which are the worker nodes that perform the computations. By combining both JAR files (for Java or Scala applications) and Python code (for PySpark applications), the SparkContext ensures that the executors have everything they need to perform the specified tasks.

Other options focus on specific components that are not comprehensive for the code execution process. For example, while Python script files and executable JAR files are specific formats, they are not as inclusive as the broader category of JAR or Python code. Configuration files, although essential for setting parameters and environment variables, do not contain the actual code that executors will run. Thus, option C accurately captures the full spectrum of code types that SparkContext can send to executors for executing operations in a Spark job