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In which of the following scenarios should a data engineer select a Task in the Depends On field of a new Databricks Job Task?
A
When another task needs to be replaced by the new task
B
When another task needs to fail before the new task begins
C
When another task has the same dependency libraries as the new task
D
When another task needs to use as little compute resources as possible
E
When another task needs to successfully complete before the new task begins
Explanation:
The correct answer is E because the 'Depends On' field in Databricks Jobs is specifically designed to define task dependencies where one task must successfully complete before another task can begin execution.
In a typical ETL pipeline, you might have:
This ensures data flows through the pipeline in the correct order without data integrity issues.