Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 287 of 313

Databricks Certified Data Engineer Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Data Engineer Professional Question 287

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You are tasked with creating a Databricks multi-task job to process raw data, transform it, and load it into a data warehouse. The workflow has the following steps:

  1. Task A: Ingest raw data into Delta Lake.
  2. Task B: Perform data transformations on the ingested data.
  3. Task C: Validate the transformed data.
  4. Task D: Load the validated data into a data warehouse.

Task B depends on Task A, Task C depends on Task B, and Task D depends on Task C. How should you configure the multi-task job dependencies?

  1. A

    Set Task B to depend on Task A, Task C to depend on Task B, and Task D to depend on Task C.

  2. B

    Configure Task A, Task B, Task C, and Task D to run in parallel without dependencies.

  3. C

    Set Task D to depend on Task A, and configure Task B and Task C to run independently.

  4. D

    Set Task B to depend on Task A, Task C to depend on Task B, and Task D to depend on both Task B and Task C.

Show answer and explanation

Correct answer: A

Explanation

To correctly configure a multi-task job with dependencies in Databricks, each task must be set up to follow the correct sequence of operations. Task B depends on Task A, Task C depends on Task B, and Task D depends on Task C. This sequential dependency ensures that data is ingested, transformed, validated, and loaded in the proper order without skipping any critical steps.

  • A. Correct.

    This is the correct setup since Task B depends on the output of Task A, Task C depends on Task B, and Task D depends on Task C. This ensures the workflow runs in the correct sequence.

  • B. Incorrect.

    This is incorrect because running all tasks in parallel ignores the dependencies between the steps. For example, Task B cannot proceed without Task A being completed.

  • C. Incorrect.

    This is incorrect because Task D depends on the validated data from Task C, so Task C cannot be skipped. Additionally, Task B and Task C must follow Task A in sequence.

  • D. Incorrect.

    This is incorrect because Task D should only depend on Task C, not Task B directly. Task C ensures data validation before the load step, and skipping this would violate the workflow requirements.

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