DEA-C01 Data Operations and Support Practice Question
A company runs a nightly Amazon EMR job that processes data from S3 and writes results back to S3. The job fails with 'OutOfMemoryError' in the reduce phase. The cluster currently uses 5 m5.xlarge instances. Which cost-effective change should the data engineer make?
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 reducers (mapreduce.reduce.tasks) and keep the same instance type.
Increasing the number of reducers (mapreduce.reduce.tasks) distributes the memory load across the existing 5 m5.xlarge instances, reducing the per-reducer memory pressure and preventing OutOfMemoryError without adding cost. Option A (adding more core nodes) increases cost without directly addressing reducer memory. Option C (reducing input data) may affect completeness and is not a proper fix. Option D (switching to r5.xlarge) is more expensive per instance, making it less cost-effective.
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 core nodes to 10.
Why it's wrong here
More nodes do not directly reduce reducer memory pressure.
- ✓
Increase the number of reducers (mapreduce.reduce.tasks) and keep the same instance type.
Why this is correct
More reducers reduce memory per reducer, preventing OOM.
- ✗
Reduce the input data size by filtering early in the job.
Why it's wrong here
Filtering may skip important data; not a reliable fix.
- ✗
Switch to r5.xlarge instances for more memory per instance.
Why it's wrong here
r5 instances are costlier; increasing reducers is cheaper.
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.