Which of the following statements about Spark jobs is incorrect?

Jobs are indeed broken down into stages based on shuffle boundaries, making this statement correct.

Multiple partitions in a DataFrame do result in multiple tasks within a job, making this statement correct.

Jobs are triggered by actions and represent collections of stages and tasks, making this statement correct.

Spark includes a built-in web UI (accessible on port 4040 by default) that allows users to monitor the status of jobs, stages, tasks, storage, and executors in real time. Stating there is no way to monitor job progress is factually wrong and is therefore the incorrect statement the question is asking to identify.

This correctly identifies that job division is based on when actions are called, not on variable definitions - wait, E is also incorrect, but D is the answer because it is the most clearly and unambiguously false statement.