Databricks-DE-Assoc Working with Lakeflow Jobs Practice Question
A data engineer has a Lakeflow Job with two tasks: Task1 and Task2. Task2 must run only if Task1 succeeds. The engineer also wants Task2 to be skipped if Task1 fails, but the overall job status should be marked as failed. Which configuration should the engineer use for the dependency between Task1 and Task2?
⚠ Common exam trap
Many exam-takers confuse 'All succeeded' with 'None failed' or 'All done', which have different semantics for skip and failure propagation.
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 Task2 to depend on Task1 with the 'All succeeded' condition.
The 'All succeeded' condition ensures Task2 runs only when Task1 succeeds. If Task1 fails, Task2 is skipped, and the job is marked as failed because a task failed. This precisely meets the requirement of conditional execution and overall job failure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set Task2 to depend on Task1 with the 'All done' condition.
Why it's wrong here
The 'All done' condition means Task2 runs after Task1 completes, regardless of success or failure. This does not meet the requirement that Task2 should run only if Task1 succeeds. If Task1 fails, Task2 would still run, which is not desired.
- ✗
Set Task2 to depend on Task1 with the 'At least one succeeded' condition.
Why it's wrong here
The 'At least one succeeded' condition is used when Task2 depends on multiple tasks and should run if any of them succeed. With a single dependency, if Task1 fails, Task2 will not run because no task succeeded. However, the job status might not be marked as failed if Task2 is skipped, depending on job settings. This does not guarantee the job fails.
- ✗
Set Task2 to depend on Task1 with the 'None failed' condition.
Why it's wrong here
The 'None failed' condition means Task2 runs if none of the dependencies failed. With a single dependency, if Task1 fails, Task2 will not run. However, this condition is typically used with multiple dependencies and does not explicitly require that all succeeded; it only requires that none failed. It might allow Task2 to run if Task1 is skipped, which is not the case here, but the job status behavior may differ.
- ✓
Set Task2 to depend on Task1 with the 'All succeeded' condition.
Why this is correct
The 'All succeeded' condition means Task2 runs only if Task1 completes successfully. If Task1 fails, Task2 is skipped, and the job is marked as failed because a task failed. This matches the requirement: Task2 runs only on success, and the job fails if Task1 fails.
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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-Assoc 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-Assoc exam.