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Answer: The job run history is kept for 60 days, during which users can view completed runs in the UI or export notebook run results to HTML.
### Explanation Databricks maintains a rolling history of all job runs for **up to 60 days**. During this 60-day window, users have the ability to: - View details of completed runs in the Jobs UI. - Export notebook run results as HTML files. - Retrieve run logs via the Jobs API or by configuring cluster log delivery. **Why the other options are incorrect:** - **Option A:** Job run history is not stored indefinitely; it is purged automatically after 60 days. - **Option B:** The retention period is specifically 60 days, not 30 days. - **Option D:** Databricks does not archive older logs automatically; records expire and are permanently removed unless proactively exported by the user. **Reference:** Azure Databricks Jobs monitoring documentation states that Databricks maintains job run history for up to 60 days and recommends exporting results if long-term preservation is required.
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A data engineer needs to review the history of a specific job. What is the standard retention period for job run history in Databricks, and what capabilities are available during this timeframe?
A
The job run history is maintained indefinitely until the user manually deletes the records or exports them to an external location.
B
The job run history is retained for 30 days, during which time logs can be moved to DBFS or Amazon S3 via the workspace configuration.
C
The job run history is kept for 60 days, during which users can view completed runs in the UI or export notebook run results to HTML.
D
The job run history is retained for 60 days, after which logs are automatically moved to a managed archive within the control plane.