DEA-C01 Data Operations and Support Practice Question
A data engineer is troubleshooting an AWS Glue job that writes data to an Amazon S3 bucket in Parquet format. The job runs successfully but the output files are smaller than the configured 'groupFiles' size. The engineer has set 'groupFiles' to 'inPartition' and 'groupSize' to 1 GB. The input data is 10 GB in a single partition. What is the most likely reason for the small files?
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
✓
The 'groupFiles' parameter only affects the input read phase, not the output write phase.
'groupFiles' only works when the input data is already small and needs to be coalesced. However, if the input is large and the job writes output, the output file size is determined by the number of Spark partitions, not grouping. The grouping feature only applies to reading input files. Option A is wrong because the setting is correct. Option C is wrong because grouping is a read-time feature, not write-time. Option D is wrong because grouping does not require repartitioning.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The 'groupFiles' parameter is deprecated in the current Glue version.
Why it's wrong here
It is still supported.
- ✓
The 'groupFiles' parameter only affects the input read phase, not the output write phase.
Why this is correct
Grouping coalesces small input files during reading but does not control output file size.
- ✗
The 'groupFiles' parameter is misspelled or set incorrectly.
Why it's wrong here
The parameter is correctly set; the issue is that grouping applies to reading, not writing.
- ✗
The engineer must also set 'repartition' to 1 to merge output files.
Why it's wrong here
Repartitioning is a separate operation; grouping does not require it.
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 |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services 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 DEA-C01 exam.