A data engineer is writing a Python UDF to classify customer feedback into sentiment categories. The UDF takes a string column and returns a string. The engineer notices that the UDF returns `null` for rows where the input is `null`. The business requirement is that `null` input should be classified as 'neutral'. What is the correct way to handle this?

Use `when(col('feedback').isNull(), 'neutral').otherwise(udf(col('feedback')))` in the DataFrame API.

Use `coalesce` on the column before applying the UDF to replace nulls with a default string.

Modify the UDF to check for `None` and return 'neutral' in that case.

Set the UDF's return type to `StringType()` and rely on Spark to convert null to 'neutral'.

DatabricksCertified Data Engineer Professional

Domain 1Objective 1

Using Python and Tools for Development DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 5)

Part of the Developing Code for Data Processing using Python and SQL domain, which accounts for 22% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~11–18 in this domain), expect 6–9 from this objective — we provide 23 practice questions to prepare you well beyond it. (estimate)

23questions here

5free pages

7concepts

22%of the exam

Questions 21–23

21application · medium
A data engineer is writing a Python UDF to classify customer feedback into sentiment categories. The UDF takes a string column and returns a string. The engineer notices that the UDF returns `null` for rows where the input is `null`. The business requirement is that `null` input should be classified as 'neutral'. What is the correct way to handle this?
Select an answer first
22foundation · easy
Which decorator is used to define a Python UDF in PySpark?
Select an answer first
23foundation · easy
In a Databricks Asset Bundle project, which file is the central configuration that defines deployment targets and resource definitions?
Select an answer first

Finished these 3 questions?

Review the revealed explanations, or continue through the curriculum.

No more pagesBack to DATA-ENGINEER-PROFESSIONAL

Free Basic Practice is a study aid with revealable answers — not a scored exam. Examers.io is independent and not affiliated with or endorsed by Databricks. “DATA-ENGINEER-PROFESSIONAL” is a trademark of its owner, used for identification only.

Using Python and Tools for Development DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 5)

Questions 21–23

Which decorator is used to define a Python UDF in PySpark?

In a Databricks Asset Bundle project, which file is the central configuration that defines deployment targets and resource definitions?

Keep studying — Developing Code for Data Processing using Python and SQL