Databricks Certified-Data-Engineer-Professional : Databricks Certified Data Engineer Professional

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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer has created a new cluster using shared access mode with default configurations.
The data engineer needs to allow the development team access to view the driver logs if needed.
What are the minimal cluster permissions that allow the development team to accomplish this?

A) CAN VIEW
B) CAN RESTART
C) CAN ATTACH TO
D) CAN MANAGE

2. A data engineer is developing a Lakeflow Declarative Pipeline (LDP) using a Databricks notebook directly connected to their pipeline. After adding new table definitions and transformation logic in their notebook, they want to check for any syntax errors in the pipeline code without actually processing data or running the pipeline. How should the data engineer perform this syntax check?

A) Disconnect the notebook from the pipeline and reconnect it to a compute cluster to access code validation features.
B) Open the web terminal from the notebook and run a shell command to validate the pipeline code.
C) Use the "Validate" option in the notebook to check for syntax errors.
D) Switch to a workspace file instead of a notebook to access validation and diagnostics tools.

3. A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook. Task A does not depend on other tasks. Tasks B and C run in parallel, with each having a serial dependency on task A.
If tasks A and B complete successfully but task C fails during a scheduled run, which statement describes the resulting state?

A) All logic expressed in the notebook associated with task A will have been successfully completed; tasks B and C will not commit any changes because of stage failure.
B) Because all tasks are managed as a dependency graph, no changes will be committed to the Lakehouse until ail tasks have successfully been completed.
C) All logic expressed in the notebook associated with tasks A and B will have been successfully completed; some operations in task C may have completed successfully.
D) Unless all tasks complete successfully, no changes will be committed to the Lakehouse; because task C failed, all commits will be rolled back automatically.
E) All logic expressed in the notebook associated with tasks A and B will have been successfully completed; any changes made in task C will be rolled back due to task failure.

4. A view is registered with the following code:

Both users and orders are Delta Lake tables.
Which statement describes the results of querying recent_orders?

A) All logic will execute when the view is defined and store the result of joining tables to the DBFS; this stored data will be returned when the view is queried.
B) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
C) All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D) Results will be computed and cached when the view is defined; these cached results will incrementally update as new records are inserted into source tables.

5. A data engineer deploys a multi-task Databricks job that orchestrates three notebooks. One task intermittently fails with Exit Code 1 but succeeds on retry. The engineer needs to collect detailed logs for the failing attempts, including stdout/stderr and cluster lifecycle context, and share them with the platform team. What steps the data engineer needs to follow using built-in tools?

A) Export the notebook run results to HTML; this bundle includes complete stdout, stderr, and cluster event history across all tasks.
B) Download worker logs directly from the Spark UI and ignore driver logs, as worker logs contain stdout/stderr for all tasks and cluster events.
C) Use the notebook interactive debugger to re-run the entire multi-task job, and capture step- through traces for the failing task.
D) From the job run details page, export the job's logs or configure log delivery; then retrieve the compute driver logs and event logs from the compute details page to correlate stdout/stderr with cluster events.

Solutions: