Databricks-DE-Pro Debugging and Deploying Practice Question
A data engineer is configuring a Databricks Workflow that must run a notebook task only after a previous task that writes to a Delta table has completed successfully. The engineer wants to ensure that if the first task fails, the second task does not run. Which feature should the engineer use to define this dependency?
⚠ Common exam trap
Watch out — candidates often confuse run_if conditions with task dependencies; run_if controls behavior based on overall job status, not on specific upstream tasks.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set the depends_on property of the second task to reference the first task's task_key.
Task dependencies in Databricks Workflows are defined using the depends_on property, which lists upstream task keys. This ensures the dependent task runs only after the specified upstream tasks complete successfully. It is the fundamental way to build a directed acyclic graph (DAG) of tasks within a job.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the second task with a run_if condition set to ALL_SUCCESS.
Why it's wrong here
The run_if condition controls whether a task runs based on the overall job's success or failure, not on a specific upstream task. ALL_SUCCESS is the default and means the task runs if all upstream tasks succeed, but it does not define the dependency itself. Without depends_on, there is no upstream relationship.
- ✗
Use a trigger to start the second task when the first task completes, using a file arrival trigger on the Delta table location.
Why it's wrong here
File arrival triggers are for starting a new job when new files arrive in a location, not for intra-job task dependencies. They are asynchronous and do not guarantee that the first task has finished writing or that the job will wait. This approach adds complexity and does not ensure sequential execution within the same Workflow.
- ✗
Add a condition task between the two tasks that checks the Delta table for new records and only proceeds if records exist.
Why it's wrong here
A condition task can evaluate a boolean expression and control downstream execution, but it does not establish a dependency on the first task's completion. The condition task would run in parallel unless it also has depends_on, and it checks data rather than task success. It is not the correct mechanism for simple task sequencing.
- ✓
Set the depends_on property of the second task to reference the first task's task_key.
Why this is correct
The depends_on property in a Workflow task definition specifies upstream tasks that must complete successfully before the dependent task starts. By referencing the first task's task_key, the second task will only run if the first succeeds, satisfying the requirement.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Pro exam.