A SQL query on a large fact table is running slowly. The query profile shows a large number of shuffle bytes and a high number of tasks in a single stage. Which bottleneck does this indicate?

Insufficient executor memory causing excessive disk spills.

Network latency between the cluster and the storage layer.

A bottleneck in the driver due to too many concurrent queries.

Data skew causing an uneven distribution of work across tasks.

A job failed, and the engineer needs to determine if the failure was due to a code change or a data issue. The engineer queries `system.jobs.runs` and sees that the previous run succeeded with the same code version, but the data in the source table has changed. Which is the most likely cause of the failure?

The job's cluster configuration was changed between runs.

The job's parameters were overridden in the failed run.

The job's code was recompiled with a different version of a library.

The data change introduced a value that the code does not handle, causing an exception.

Which Databricks system table would you query to retrieve the history of job runs, including run IDs, start times, and end times?

system.compute.cluster_policies

A Spark job fails with an `OutOfMemoryError` on the executor. Which remediation is most directly appropriate for this error?

Decrease the number of partitions

Increase the number of partitions

DatabricksCertified Data Engineer Professional

Domain 9Objective 1

Debugging and Troubleshooting DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 1)

Part of the Debugging and Deploying domain, which accounts for 10% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~5–8 in this domain), expect 3–4 from this objective — we provide 34 practice questions to prepare you well beyond it. (estimate)

34questions here

7free pages

9concepts

10%of the exam

Questions 1–5

1application · medium
A SQL query on a large fact table is running slowly. The query profile shows a large number of shuffle bytes and a high number of tasks in a single stage. Which bottleneck does this indicate?
Select an answer first
2foundation · easy
When debugging a Spark pipeline, which Spark UI tab would you use to see the DAG of stages for a specific action?
Select an answer first
3expert · hard
A job failed, and the engineer needs to determine if the failure was due to a code change or a data issue. The engineer queries `system.jobs.runs` and sees that the previous run succeeded with the same code version, but the data in the source table has changed. Which is the most likely cause of the failure?
Select an answer first
4foundation · easy
Which Databricks system table would you query to retrieve the history of job runs, including run IDs, start times, and end times?
Select an answer first
5foundation · easy
A Spark job fails with an `OutOfMemoryError` on the executor. Which remediation is most directly appropriate for this error?
Select an answer first

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Debugging and Troubleshooting DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 1)

Questions 1–5

A SQL query on a large fact table is running slowly. The query profile shows a large number of shuffle bytes and a high number of tasks in a single stage. Which bottleneck does this indicate?

When debugging a Spark pipeline, which Spark UI tab would you use to see the DAG of stages for a specific action?

Which Databricks system table would you query to retrieve the history of job runs, including run IDs, start times, and end times?

A Spark job fails with an `OutOfMemoryError` on the executor. Which remediation is most directly appropriate for this error?

Keep studying — Debugging and Deploying