DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer uses AWS Glue to process data from S3. The Glue job frequently fails with 'Out of Memory' errors. The job reads several large compressed files. What is the MOST effective way to resolve this issue without changing the code?
⚠ Common exam trap
Test-takers frequently confuse 'Out of Memory' errors with performance issues and choose to reduce parallelism (Option C) or increase timeout (Option D), not realizing that memory exhaustion requires more memory per executor, not fewer tasks or longer runtime.
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 G.1X workers or use G.2X workers
Increasing the number of G.1X workers or switching to G.2X workers directly addresses the 'Out of Memory' errors by allocating more memory per Spark executor. G.1X provides 16 GB of memory per worker, while G.2X provides 32 GB, which is critical when processing large compressed files because decompression and transformation require additional heap space. This approach resolves the issue without modifying the job code, as it only changes the resource configuration.
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 G.1X workers or use G.2X workers
Why this is correct
More workers or higher memory workers provide more heap space for processing.
- ✗
Convert the compressed files to uncompressed format before processing
Why it's wrong here
Uncompressed files may reduce memory overhead but increase storage and cost.
- ✗
Repartition the data to fewer partitions
Why it's wrong here
Fewer partitions may reduce parallelism but could worsen memory pressure.
- ✗
Increase the job timeout setting
Why it's wrong here
Timeout does not affect memory allocation.
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.