Answer: The **Stage's detail screen** and the **Executor's log files**.

The correct answer is **C: The Stage's detail screen and the Executor's log files.** * **Stage's Detail Screen:** On the specific Stage ID page in the Spark UI, you can find the **Shuffle metrics** section. This area includes two specific columns: *Shuffle spill (memory)* and *Shuffle spill (disk)*. If the 'disk' column contains non-zero values, it confirms that data was serialized and written to disk during that stage. * **Executor's Log Files:** By navigating to the **Executors** tab and viewing the stdout/stderr logs for a specific executor, you can search for entries from the `UnsafeExternalSorter`. Messages such as "Spilling data because number of spilledRecords crossed the threshold" provide definitive proof of spilling at the task level. **Why other options are incorrect:** * **Query (SQL) detail screen:** This view shows high-level physical and logical plan metrics but does not expose the granular task-level shuffle spill counters found in the Stage view. * **Driver's log files:** Spilling is an executor-side event. The driver does not manage the local shuffle memory of the executors, so these events are not captured in the driver logs. * **Executor's detail screen:** While the Executors tab provides aggregate metrics, the primary per-task spill counters are most effectively analyzed on the Stage detail page.

Author: LeetQuiz Editorial Team