DEA-C01 Data Ingestion and Transformation Practice Question
A company uses AWS Glue to transform data from Amazon S3 into Parquet format. The job fails with an out-of-memory error for large files. Which TWO actions can resolve this issue? (Choose TWO.)
⚠ Common exam trap
Watch out — candidates often think enabling logging (CloudWatch) or changing file formats will fix memory issues, but only resource scaling (DPUs) or data partitioning (smaller files) address the root cause of insufficient memory for large in-memory transformations.
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 DPUs allocated to the job.
Increasing the number of DPUs (Data Processing Units) allocated to the Glue job provides more memory and compute capacity, which directly addresses out-of-memory errors when processing large files. AWS Glue uses Apache Spark under the hood, and each DPU provides 4 vCPU and 16 GB of memory, so adding DPUs scales the available resources for in-memory transformations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the input format from CSV to JSON.
Why it's wrong here
File format does not directly cause OOM; memory allocation is the issue.
- ✓
Increase the number of DPUs allocated to the job.
Why this is correct
More DPUs provide more memory and processing power.
- ✗
Use the Glue streaming ETL feature.
Why it's wrong here
Streaming ETL is for real-time data, not for batch processing large files.
- ✗
Enable CloudWatch logs for detailed error analysis.
Why it's wrong here
Logs help diagnose but do not resolve the OOM.
- ✓
Split the input data into smaller files.
Why this is correct
Smaller files allow better parallelism and reduce per-executor memory pressure.
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.