Databricks-DE-Pro Debugging and Deploying Practice Question
A data engineer is using Databricks Asset Bundles to deploy a job that runs a Python wheel task. The bundle is deployed to a production workspace using a service principal. The job fails with the error: `Library installation failed for library due to user error: Could not find wheel file`. The engineer confirms the wheel file exists in the bundle's `dist` folder. What is the most likely cause of this failure?
⚠ Common exam trap
The trap here is assuming that placing the wheel in the local `dist` folder is sufficient, when the bundle must explicitly declare and upload artifacts.
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
✓
The wheel file is not included in the bundle's artifact definition, so it is not uploaded to the workspace.
For a Python wheel task in a Databricks Asset Bundle, the wheel must be declared as an artifact in the bundle configuration. This ensures it is built and uploaded to the workspace during deployment. Without this, the job cannot locate the wheel, leading to the error. The other options incorrectly attribute the failure to permissions, path resolution, or compatibility.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The wheel file path in the task definition is relative to the workspace root instead of the bundle root.
Why it's wrong here
In bundle task definitions, paths to artifacts are typically relative to the bundle root and are resolved during deployment. The error indicates the wheel is missing entirely, not that the path is wrong. If the path were incorrect but the file uploaded, the error would be different, such as a file not found at a specific path.
- ✗
The wheel file is not compatible with the Databricks Runtime version used by the cluster.
Why it's wrong here
Incompatibility would cause a different error, such as a Python version mismatch or dependency conflict. The error `Could not find wheel file` specifically indicates the file is not present in the workspace. Compatibility issues would arise after the file is found and installation is attempted.
- ✗
The service principal lacks permission to read from the `dist` folder in the workspace.
Why it's wrong here
The `dist` folder is local to the development environment, not in the workspace. The error occurs because the wheel is not uploaded, not due to permissions. Service principal permissions apply to workspace objects, but the wheel is not there. This option misidentifies the location of the artifact and the nature of the error.
- ✓
The wheel file is not included in the bundle's artifact definition, so it is not uploaded to the workspace.
Why this is correct
In Databricks Asset Bundles, artifacts such as Python wheels must be explicitly defined in the `artifacts` section of `databricks.yml`. If the wheel is not listed, it will not be uploaded during deployment, and the job cannot find it. The `dist` folder alone does not guarantee inclusion; the artifact must be declared and built.
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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.