The correct answer involves using Spark's mergeSchema option when writing to S3, updating the Glue Data Catalog, and applying the recast option in Glue to handle type changes. These three steps work together to address schema evolution in an AWS Glue ETL pipeline from DynamoDB to Parquet because DynamoDB is schema-less and can introduce new attributes or change data types at any time, while Parquet requires a fixed schema for efficient columnar storage. The mergeSchema option in Spark dynamically reconciles the existing Parquet schema with incoming data, the Glue Data Catalog update ensures the schema is refreshed for downstream queries, and the recast option handles type coercion without data loss. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of how to handle schema evolution in Glue ETL without breaking pipelines—a common trap is confusing partition management with schema changes or converting to CSV, which loses the benefits of Parquet. Memory tip: think "Merge, Catalog, Recast" as the three pillars of schema evolution in Glue.
DEA-C01 Data Operations and Support Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data engineer is designing an ETL pipeline that uses AWS Glue to process data from an Amazon DynamoDB table and write results to an S3 bucket in Parquet format. The pipeline must handle schema changes in the source DynamoDB table. Which THREE steps should the engineer take to ensure the pipeline handles schema evolution? (Choose THREE.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Glue's 'recast' transformation to handle type changes.
Options A, B, and D are correct. Updating the Glue Data Catalog allows the crawler to update schema. 'mergeSchema' is a Spark option that merges schemas. 'recast' option in Glue helps handle type changes. Option C is wrong because deleting partitions is not related to schema evolution. Option E is wrong because converting to CSV is not a schema evolution strategy.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Glue's 'recast' transformation to handle type changes.
Why this is correct
recast can change data types to match the target schema.
Related concept
Read the scenario before looking for a memorised answer.
✓
Set the Glue crawler to update the table's schema in the Data Catalog.
Why this is correct
Crawler can update the schema when new columns are detected.
Related concept
Read the scenario before looking for a memorised answer.
✗
Convert the Parquet output to CSV to avoid schema constraints.
Why it's wrong here
CSV does not enforce schema but loses performance benefits of Parquet.
✗
Partition the data by date and delete old partitions.
Why it's wrong here
Partition management does not handle schema evolution.
✓
Use Spark's 'mergeSchema' option when writing to S3.
Why this is correct
mergeSchema allows Parquet files with different schemas to be written.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Glue's 'recast' transformation to handle type changes. — Options A, B, and D are correct. Updating the Glue Data Catalog allows the crawler to update schema. 'mergeSchema' is a Spark option that merges schemas. 'recast' option in Glue helps handle type changes. Option C is wrong because deleting partitions is not related to schema evolution. Option E is wrong because converting to CSV is not a schema evolution strategy.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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