Databricks Certified Data Engineer - Associate

Explanation

In Databricks Jobs, the Depends On field is used to define task dependencies and control the execution order of tasks within a job.

Key Points:

1. Task Dependencies: When you specify a task in the Depends On field, it means the new task will only start executing after the specified dependent task has completed successfully.

2. Execution Flow Control: This is essential for creating sequential workflows where certain tasks must complete before others can begin (e.g., data extraction must complete before data transformation can start).

3. Why Other Options Are Incorrect:

   • Option A: Incorrect - The Depends On field doesn't replace tasks; it defines dependencies.
   • Option B: Incorrect - Tasks don't need to fail for dependencies to work; successful completion is the typical requirement.
   • Option C: Incorrect - Dependency libraries are configured separately, not through task dependencies.
   • Option D: Incorrect - Resource allocation is managed through cluster configuration, not task dependencies.

4. Practical Example:

   Task 1: Extract data from source → Task 2: Transform data → Task 3: Load to destination
   

   Task 1: Extract data from source → Task 2: Transform data → Task 3: Load to destination
   

   Here, Task 2 would have Task 1 in its Depends On field, and Task 3 would have Task 2 in its Depends On field.

Correct Answer: E - The Depends On field is used when another task needs to successfully complete before the new task begins.