DEA-C01 Data Ingestion and Transformation Practice Question
A data pipeline uses AWS Glue ETL to process data from an S3 bucket and write results to a Redshift cluster. The job fails with a 'DiskFull' error on the Glue worker nodes. What is the best way to resolve this issue?
⚠ Common exam trap
Watch out — candidates often confuse storage on the worker nodes with storage in the output target, leading them to choose file format optimization (Option C) instead of addressing the worker-level resource constraint.
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
✓
Increase the number of Glue DPUs or use G.1X worker type.
The 'DiskFull' error on Glue worker nodes indicates that the local storage allocated per worker is insufficient for the data being processed. Increasing the number of DPUs or switching to a G.1X worker type (which provides more disk space per worker) directly addresses this by either distributing the workload across more workers or upgrading to a worker type with higher storage capacity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of Glue DPUs or use G.1X worker type.
Why this is correct
More DPUs or larger workers provide additional disk and memory.
- ✗
Decrease the number of partitions in the output.
Why it's wrong here
Fewer partitions may reduce parallelism but could cause other issues.
- ✗
Use a different file format like Parquet to reduce storage.
Why it's wrong here
Compression may help but the error is on worker disk, not S3.
- ✗
Increase the job timeout setting.
Why it's wrong here
Timeout does not affect disk space.
Visual reference
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 |
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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.