The answer is to use `coalesce(n)` with n based on a target file size like 128 MB before writing. This is correct because `coalesce` reduces the number of partitions without triggering a full shuffle, allowing you to control output file count while avoiding the performance bottleneck of a single partition. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of how Spark’s partitioning directly impacts S3 output—many candidates mistakenly adjust `spark.sql.shuffle.partitions`, but that only controls intermediate shuffle stages, not final file count. The trap is confusing shuffle parallelism with output partitioning; lowering shuffle partitions risks out-of-memory errors, while increasing them multiplies small files. A practical way to reduce small files in AWS Glue ETL output is to apply `coalesce` right before the write operation, calculating n by dividing total data size by your desired file size. Memory tip: “Coalesce before commit, shuffle partitions just for the shuffle.”
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 company runs an AWS Glue ETL job that reads data from Amazon S3, transforms it, and writes back to S3 in a different partition structure. The job uses the 'spark.sql.shuffle.partitions' option set to 200. After the job completes, the output has many small files. The data engineer wants to minimize the number of output files while maintaining job performance. Which action should the engineer take?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use 'coalesce(n)' with n based on target file size (e.g., 128 MB) before writing.
Option D is correct because using 'coalesce' or 'repartition' with a number based on the target file size (e.g., 128 MB) reduces files without a single partition bottleneck. Option A is wrong because lowering shuffle partitions reduces parallelism and may cause OOM. Option B is wrong because increasing shuffle partitions increases files. Option C is wrong because S3 multipart upload is automatic and does not affect file count.
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 'coalesce(n)' with n based on target file size (e.g., 128 MB) before writing.
Why this is correct
Coalesce reduces partitions without a full shuffle, minimizing files.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable S3 multipart upload for the Glue job.
Why it's wrong here
Multipart upload is for large files, not file count.
✗
Increase the 'spark.sql.shuffle.partitions' to 500.
Why it's wrong here
Increases parallelism, leading to more files.
✗
Reduce the 'spark.sql.shuffle.partitions' to 50.
Why it's wrong here
Reduces parallelism, may cause OOM, but still produces many small files.
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 Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use 'coalesce(n)' with n based on target file size (e.g., 128 MB) before writing. — Option D is correct because using 'coalesce' or 'repartition' with a number based on the target file size (e.g., 128 MB) reduces files without a single partition bottleneck. Option A is wrong because lowering shuffle partitions reduces parallelism and may cause OOM. Option B is wrong because increasing shuffle partitions increases files. Option C is wrong because S3 multipart upload is automatic and does not affect file count.
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.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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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