The correct answer is E. https://docs.databricks.com/api/workspace/jobs/getrun
You can visit the link and observe the response sample of the API
{
"job_id": 11223344,
"run_id": 455644833,
job_id is the unique id of the job. run_id is the unique id of the run
Then each task will have its unique run id:
"tasks": [
{
...
"run_id": 2112892,
...
Correct:
E - In the Databricks Jobs API (specifically for multi-task jobs), the execution of the entire job is identified by a unique top-level run_id (often referred to as the job_run_id or parent run ID). Within that job run, each individual task execution is also assigned its own unique run_id (task run ID). This allows you to query the status and output of specific tasks independently using their specific task run_id.
Each job execution (run) gets a unique run_id
This run_id identifies a specific instance of a job run.
It allows tracking of job execution details, logs, and results.
Each task within that job run has a unique task_id
Multi-task jobs have multiple tasks, each assigned a distinct task_id.
The task_id helps in monitoring and retrieving individual task details.
E - but between D & E is a play on the words. Still E seems a tiny bit more explicit. The bottom line the run_id attribute of each task within the job will be different.
Answer E. Job Run (run_id): Each execution of a job has a unique run_id for the entire job.
Task Run (run_id): For jobs with multiple tasks, each task also gets its own run_id, which is distinct from the job's run_id. This run_id for tasks can be used to retrieve individual task outputs.
https://docs.databricks.com/api/workspace/jobs/getrun
"tasks: The list of tasks performed by the run. Each task has its own run_id which you can use to call JobsGetOutput to retrieve the run results. "
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