Apache Spark Certification Practice Test 2025 - Free Spark Exam Practice Questions and Study Guide

Executors in Apache Spark are responsible for executing the tasks assigned by the driver on the worker nodes. Once an executor is started on a worker node, it remains alive and can handle multiple tasks during its lifetime. This means that, even when a task is not currently being executed, executors continue to run and are available to take on new tasks as they become available.

This behavior is crucial for efficient resource utilization in a Spark application. Keeping executors alive allows them to quickly process tasks without the overhead of starting and stopping executors frequently. This results in better performance and reduced latency for job execution, especially in scenarios where there are many small tasks or a dynamic workload.

While the other options might suggest conditional behavior, the fundamental design of Spark's executor model ensures that once launched, executors run continuously on their respective worker nodes, ready to execute tasks as needed.