Databricks-DE-Assoc Databricks Intelligence Platform Practice Question
A data engineer is setting up a Databricks job that runs a notebook on a schedule. The job must process data from a source that is updated daily and write results to a Delta table. The engineer wants to ensure that if the job fails, it automatically retries up to three times. Which feature should the engineer configure in the job settings to achieve this?
⚠ Common exam trap
Many candidates confuse cluster auto-restart with job retries. Cluster auto-restart recovers the cluster, not the job, and job retries are configured separately in the job settings.
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
✓
In the job's task settings, set the maximum number of retries to 3 and configure the retry interval.
Databricks jobs provide a retry configuration at the task level. By setting the maximum number of retries to 3, the task will be automatically retried if it fails, up to three times. This can be configured in the job's task settings, along with a retry interval if needed. This feature is designed to handle transient failures without manual intervention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable the 'Retry on failure' option in the notebook itself and set the retry count to 3.
Why it's wrong here
Notebooks do not have a built-in 'Retry on failure' option. Retry logic must be implemented in code or configured at the job level. This option suggests a feature that does not exist in the notebook interface, so it is incorrect. Job-level configuration is the correct place to set retries.
- ✓
In the job's task settings, set the maximum number of retries to 3 and configure the retry interval.
Why this is correct
Databricks jobs allow configuring retries at the task level. Setting the maximum number of retries to 3 ensures the task will be retried up to three times if it fails. The retry interval can also be set to control the delay between retries. This directly meets the requirement for automatic retries.
- ✗
Set the maximum concurrent runs to 1 and enable retries with a maximum of 3 retries.
Why it's wrong here
Maximum concurrent runs controls how many instances of the job can run simultaneously. Setting it to 1 prevents overlapping runs but does not configure retries. The retry setting is separate. This option combines an unrelated setting with the retry configuration, but the retry part is correct only if retries are enabled separately. It does not fully address the requirement.
- ✗
Configure the job to use a job cluster with auto-restart enabled and set the number of retries to 3.
Why it's wrong here
Auto-restart is a cluster feature that restarts the cluster if it fails, not the job. Job retries are configured at the job level, not the cluster level. Setting retries to 3 is correct, but enabling auto-restart on the cluster does not control job retries. This option misplaces the retry configuration.
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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.