Databricks Certified Data Engineer - Associate
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Question 39
A data engineer has set up a notebook to automatically process using a Job. The data engineer's manager wants to version control the schedule due to its complexity.
Which of the following approaches can the data engineer use to obtain a version-controllable configuration of the Job's schedule?
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A
They can link the Job to notebooks that are a part of a Databricks Repo.
B
They can submit the Job once on a Job cluster.
C
They can download the JSON description of the Job from the Job's page.
D
They can submit the Job once on an all-purpose cluster.
E
They can download the XML description of the Job from the Job's page.
Explanation:
Explanation
The correct answer is C because:
- Option C: Downloading the JSON description of the Job from the Job's page provides a complete, machine-readable configuration file that includes the schedule settings. This JSON file can be stored in a version control system (like Git) and tracked over time, allowing for proper version control of the Job's schedule configuration.
Why other options are incorrect:
-
Option A: Linking the Job to notebooks in a Databricks Repo only version controls the notebook code, not the Job's schedule configuration itself.
-
Option B: Submitting the Job once on a Job cluster doesn't provide a version-controllable configuration file for the schedule.
-
Option D: Submitting the Job once on an all-purpose cluster similarly doesn't provide a configuration file for version control.
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Option E: Databricks Jobs use JSON format for configuration, not XML. Downloading XML description is not a valid option.
Best Practice:
The JSON description contains all Job settings including the schedule, which can be committed to version control, enabling tracking of changes, rollback capabilities, and collaborative development of Job configurations.
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