Databricks-DE-Assoc Working with Lakeflow Jobs Practice Question
A data engineer has a Lakeflow Job with three tasks: bronze_ingest, silver_transform, and gold_aggregate. The silver_transform task must run only if bronze_ingest succeeds, and gold_aggregate must run only if silver_transform succeeds. The engineer also wants gold_aggregate to run even if silver_transform fails, so that partial results can be published. Which configuration should the engineer apply to gold_aggregate?
⚠ Common exam trap
The trap here is assuming that run_if alone controls ordering, when depends_on must also be present to define the dependency edge that run_if evaluates.
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 gold_aggregate's depends_on to include silver_transform and set run_if to ALL_DONE.
Ordering and run conditions are separate controls. depends_on places gold_aggregate after silver_transform, and run_if set to ALL_DONE allows the task to execute once upstream tasks reach a terminal state, whether they succeeded or failed. This is the standard pattern for publishing partial results or running cleanup tasks after a 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.
- ✗
Remove depends_on from gold_aggregate and set run_if to ALL_DONE.
Why it's wrong here
Removing depends_on eliminates the ordering edge, so gold_aggregate could start before silver_transform finishes. Even with ALL_DONE, the scheduler has no dependency to evaluate, so the task may run concurrently with silver_transform. This breaks the intended pipeline sequence and can read incomplete data.
- ✗
Set gold_aggregate's depends_on to include bronze_ingest and set run_if to AT_LEAST_ONE_SUCCESS.
Why it's wrong here
Depending only on bronze_ingest skips the silver_transform ordering, so gold_aggregate could run before silver_transform completes. AT_LEAST_ONE_SUCCESS would also allow execution when only bronze_ingest succeeds, which is not the intended condition. This does not reliably wait for silver_transform or handle its failure as specified.
- ✗
Set gold_aggregate's depends_on to include silver_transform and set run_if to ALL_SUCCESS.
Why it's wrong here
ALL_SUCCESS is the default behavior and runs the task only when all dependencies succeed. That would prevent gold_aggregate from running when silver_transform fails, which contradicts the requirement to publish partial results. The ordering is correct, but the condition blocks the desired failure-path execution.
- ✓
Set gold_aggregate's depends_on to include silver_transform and set run_if to ALL_DONE.
Why this is correct
depends_on establishes the ordering so gold_aggregate waits for silver_transform. Setting run_if to ALL_DONE causes gold_aggregate to run regardless of whether silver_transform succeeded or failed, as long as upstream tasks have reached a terminal state. This combination satisfies both the ordering and the run-even-on-failure 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-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.