Exam Associate-Developer-Apache-Spark-3.5 Topic 1 Question 22 Discussion
Actual exam question for Databricks's Associate-Developer-Apache-Spark-3.5 exam
Question #: 22
Topic #: 1
Question #: 22
Topic #: 1
A Data Analyst is working on the DataFrame sensor_df, which contains two columns:
Which code fragment returns a DataFrame that splits the record column into separate columns and has one array item per row?
A)
B)
C)
D)
Which code fragment returns a DataFrame that splits the record column into separate columns and has one array item per row?
A)
B)
C)
D)
Suggested Answer: C Vote an answer
To flatten an array of structs into individual rows and access fields within each struct, you must:
Use explode() to expand the array so each struct becomes its own row.
Access the struct fields via dot notation (e.g., record_exploded.sensor_id).
Option C does exactly that:
First, explode the record array column into a new column record_exploded.
Then, access fields of the struct using the dot syntax in select.
This is standard practice in PySpark for nested data transformation.
Final answer: C
Use explode() to expand the array so each struct becomes its own row.
Access the struct fields via dot notation (e.g., record_exploded.sensor_id).
Option C does exactly that:
First, explode the record array column into a new column record_exploded.
Then, access fields of the struct using the dot syntax in select.
This is standard practice in PySpark for nested data transformation.
Final answer: C
by pankaj.k.shukla at Sep 28, 2026, 11:41 AM
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pankaj.k.shukla
2026-09-28 11:41:37Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.
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