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Answer: When another task needs to successfully complete before the new task begins
Specifying a task in the 'Depends On' field ensures that certain tasks are completed successfully before others begin. This is crucial for managing task dependencies within Databricks Jobs, maintaining a logical workflow sequence. It optimizes workflow efficiency and effectiveness by ensuring that the outcome of preceding tasks influences the initiation and execution of subsequent tasks.
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Why would a data engineer specify a Task in the 'Depends On' field when configuring a new Task in a Databricks Job?
A
When another task needs to use as little compute resources as possible
B
When another task needs to successfully complete before the new task begins
C
When another task needs to be replaced by the new task
D
When another task has the same dependency libraries as the new task
E
When another task needs to fail before the new task begins
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