DP-700 · Question #123
DP-700 Question #123: Real Exam Question with Answer & Explanation
The correct answer is C: Create two stages in the DAG definition. Add notebook_03 to the first stage. Add notebook_01 and notebook_02 to the second stage.. The question asks how to define dependencies in a DAG (Directed Acyclic Graph) to make two notebooks run in parallel and a third run only after both complete.
Question
You need to modify the DAG definition to meet the following requirements: - Ensure that notebook_01 and notebook_02 run in parallel. - Ensure that notebook_03 only runs after the execution of notebook_01 and notebook_02 is complete. How should you modify the DAG definition?
Options
- ACreate a second DAG definition. Move notebook_03 and notebook_02 to the new DAG definition.
- BMove the notebook_03 declaration to the top of the DAG definition. Add a concurrency to notebook_02 and notebook_01.
- CCreate two stages in the DAG definition. Add notebook_03 to the first stage. Add notebook_01 and notebook_02 to the second stage.
- DPlace the declaration of notebook_03 to the top of the DAG definition. Add a new stage that contains notebook_01 and notebook_02.
Explanation
The question asks how to define dependencies in a DAG (Directed Acyclic Graph) to make two notebooks run in parallel and a third run only after both complete.
Common mistakes.
- A. Creating a second DAG definition would result in two independent execution flows and would not ensure the required sequential dependency between all three notebooks.
- B. Merely moving a declaration to the top or adding a 'concurrency' parameter does not define the explicit parallel-then-sequential dependency required by the problem; dependencies dictate execution order, not declaration order.
- D. Placing a declaration at the top and creating a new stage without explicit dependency definitions does not ensure the required parallel and sequential execution order.
Concept tested. DAG task orchestration, parallel and sequential execution
Reference. https://learn.microsoft.com/fabric/data-factory/create-pipelines
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