Databricks Certified Data Engineer - Associate
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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?
Real Exam
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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 'Depends On' field in Databricks Jobs is used to define task dependencies, where a task will only start after its dependent tasks have successfully completed. This is essential for creating workflow pipelines where tasks need to run in a specific sequence. Option E correctly describes this scenario where one task must successfully complete before another can begin.
Key Points:
- Task dependencies ensure proper execution order in workflows
- A task will only run if all its dependencies have succeeded
- This is different from failure-based dependencies (which would be error handling scenarios)
- Resource optimization and library sharing are not the purpose of task dependencies
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