Apache Spark Certification Practice Test

Spark can run on various cluster managers, which provides flexibility in terms of deployment options and resource management. By selecting the correct answer, you acknowledge that Spark can effectively operate in different environments, including Standalone mode and with resource managers like YARN (Yet Another Resource Negotiator).

Standalone mode is a simple way to run Spark, where the Spark cluster consists of a set of machines specifically designated to run Spark jobs without the overhead of a central resource manager. This mode is advantageous for smaller setups or for users who prefer a straightforward deployment.

On the other hand, YARN is a more sophisticated cluster manager that enables Spark to leverage the existing Hadoop infrastructure. This integration allows Spark to run alongside other processing frameworks in a more resource-efficient manner, sharing resources and improving utilization.

The combined capability to operate in both Standalone and YARN environments illustrates Spark's versatility, allowing users to choose the configuration best suited to their needs and infrastructure. Other configurations, such as Mesos or Kubernetes, are also valid in certain contexts, but the answer correctly identifies the two primary and widely-used modes that Spark operates under, emphasizing the importance of flexibility in a distributed computing framework.