DEA-C01 Data Ingestion and Transformation Practice Question
A company is using AWS Glue to process data from Amazon S3. The Glue job reads CSV files and writes Parquet files to a different S3 bucket. The job occasionally fails with 'java.lang.OutOfMemoryError: Java heap space'. The data size varies. Which change should the engineer make to avoid this error?
⚠ Common exam trap
Watch out — candidates often confuse 'increasing DPUs' with 'increasing parallelism' and assume it only speeds up jobs, but in reality it also increases total memory, which directly mitigates heap space errors.
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 Glue job.
The 'java.lang.OutOfMemoryError: Java heap space' error in AWS Glue indicates that the Spark executors ran out of memory while processing the data. Increasing the number of DPUs (Data Processing Units) allocated to the Glue job increases the total memory available across the cluster, allowing larger datasets to be processed without hitting the heap limit. Each DPU provides 4 vCPUs and 16 GB of memory, so adding more DPUs scales memory linearly.
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 DPUs allocated to the Glue job.
Why this is correct
More DPUs provide more memory and compute resources.
- ✗
Convert the CSV files to JSON format before processing.
Why it's wrong here
JSON is less memory-efficient than CSV.
- ✗
Decrease the Spark shuffle partitions in the job script.
Why it's wrong here
This might reduce memory but is less direct and could impact performance.
- ✗
Increase the job timeout setting.
Why it's wrong here
Timeout only affects job duration, not memory.
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.