Courseiva
Develop data processinghardMultiple ChoiceObjective-mapped

DP-203 Develop data processing Practice Question

Your company uses Azure Data Lake Storage Gen2 and Azure Databricks for data processing. Some Parquet files in the lake are written with a schema that includes a column 'address' of struct type. A downstream process expects 'address' to be a string. You need to transform the data in a way that minimizes read overhead and does not rewrite the entire dataset. Which approach should you use?

⚠ Common exam trap

Candidates often confuse schema evolution (which modifies metadata but still requires a rewrite for type changes) with schema-on-read (which applies transformations at query time without altering storage), leading them to choose option A incorrectly.

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

Apply a schema-on-read transformation that casts the column to string when reading.

Schema-on-read allows you to cast the 'address' column from struct to string at query time without modifying the underlying Parquet files. This approach minimizes read overhead by avoiding a full data rewrite and leverages Spark's ability to apply transformations during the read path, which is efficient for downstream processes that expect a string type.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use schema evolution in Delta Lake to change the column type.

    Why it's wrong here

    Delta Lake schema evolution does not support changing column types from struct to string.

  • Apply a schema-on-read transformation that casts the column to string when reading.

    Why this is correct

    Efficient, no rewrite needed.

  • Create a view that selects the column as a string and save it as a new table.

    Why it's wrong here

    Would create a new copy of data.

  • Rewrite the Parquet files with the correct schema using a Spark job.

    Why it's wrong here

    Unnecessary full rewrite.

About these practice questions

This DP-203 question is part of Courseiva's 760-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DP-203 practice question is part of Courseiva's free Microsoft 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 DP-203 exam.