Question 22
Domain 5: Monitoring and AlertingWhen using CLI or REST API to get results from jobs with multiple tasks, which statement correctly describes the response structure?
Correct answer: E
Explanation
Jobs can be created and monitored through the “Databricks CLI, REST API,” and the Jobs API returns information per run. For multi-task jobs, each task run is tracked separately, so “each run of a job will have a unique run_id; all tasks within this job will also have a unique run_id.”
Why each option is right or wrong
A. Each run of a job will have a unique job_id; all tasks within this job will have a unique job_id
Jobs use run_id for executions, not job_id for each run or task.
B. Each run of a job will have a unique job_id; all tasks within this job will have a unique task_id
Tasks are identified by run_id in this response structure, not task_id.
C. Each run of a job will have a unique orchestration_id; all tasks within this job will have a unique run_id
The documented Jobs API uses run_id, not orchestration_id or task run_id wording.
D. Each run of a job will have a unique run_id; all tasks within this job will have a unique task_id
Tasks in multi-task job results are also represented with run_id, not task_id.
E. Each run of a job will have a unique run_id; all tasks within this job will also have a unique run_id
The Jobs API models execution at the run level: the top-level job execution is identified by a unique `run_id`, and in a multi-task workflow each task execution is also returned as its own run record with its own unique `run_id` in the response payload. This is why the CLI/REST response does not collapse all tasks into one shared identifier; instead, it exposes separate run objects for the parent job run and for each task run, consistent with the Jobs API’s run-tracking structure used for monitoring and troubleshooting.