- A
Enable 'groupFiles' in the Glue job's S3 target configuration.
Glue's groupFiles option merges small files during write.
- B
Use 'coalesce(1)' at the end of the ETL script.
Why wrong: May cause OOM and single executor bottleneck.
- C
Use 'repartition(100)' to increase parallelism.
Why wrong: Increases number of files, worsening the issue.
- D
Configure an S3 lifecycle policy to delete small files.
Why wrong: Lifecycle policies do not merge files.
Question 1,616 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 notices that an AWS Glue job writing to Amazon S3 in Parquet format creates many small files (less than 1 MB each). This leads to poor query performance in Amazon Athena. What is the BEST way to reduce the number of output files?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
✓
Enable 'groupFiles' in the Glue job's S3 target configuration.
Option A is correct because enabling 'groupFiles' in the AWS Glue job's S3 target configuration instructs Glue to coalesce small files into larger ones (default target size ~128 MB) during the write phase. This directly reduces the number of small Parquet files written to S3, improving Athena query performance by minimizing S3 LIST and GET overhead.
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.
- ✓
Enable 'groupFiles' in the Glue job's S3 target configuration.
Why this is correct
Glue's groupFiles option merges small files during write.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use 'coalesce(1)' at the end of the ETL script.
Why it's wrong here
May cause OOM and single executor bottleneck.
- ✗
Use 'repartition(100)' to increase parallelism.
Why it's wrong here
Increases number of files, worsening the issue.
- ✗
Configure an S3 lifecycle policy to delete small files.
Why it's wrong here
Lifecycle policies do not merge files.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'coalesce(1)' or 'repartition()' as file-size solutions, but these operations control the number of Spark partitions, not the final file size, and can actually worsen the problem or cause job failures.
Detailed technical explanation
How to think about this question
Under the hood, 'groupFiles' works by buffering output from multiple Spark tasks and writing consolidated files using a configurable group size (default 128 MB). This is particularly useful when the source data is highly partitioned or when dynamic frame transformations produce many small records. In real-world scenarios, such as streaming or incremental loads, small files accumulate rapidly, and 'groupFiles' is the only built-in Glue mechanism to automatically coalesce them during the write without manual repartitioning.
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.
TExam Day Tips
- 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.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
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: Enable 'groupFiles' in the Glue job's S3 target configuration. — Option A is correct because enabling 'groupFiles' in the AWS Glue job's S3 target configuration instructs Glue to coalesce small files into larger ones (default target size ~128 MB) during the write phase. This directly reduces the number of small Parquet files written to S3, improving Athena query performance by minimizing S3 LIST and GET overhead.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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