- A
Enable S3 request rate increase to speed up data reading.
Why wrong: Does not affect executor memory.
- B
Increase the number of DPUs allocated to the Glue job.
More DPUs increase total memory available.
- C
Repartition the data to a larger number of partitions.
Why wrong: May help parallelism but not memory per executor if DPUs unchanged.
- D
Change the input format from Parquet to Snappy-compressed CSV.
Why wrong: Format change does not fix memory; Snappy may be similar.
Question 352 of 1,786
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses AWS Glue to transform data stored in Amazon S3. During a run, the job fails with a 'OutOfMemoryError' in the Spark executor. The job processes 2 TB of parquet files using 10 DPUs. The data is evenly distributed across partitions. Which action would MOST likely resolve the issue without impacting the job logic?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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 OutOfMemoryError in the Spark executor indicates that the available memory per executor is insufficient for the data being processed. Increasing the number of DPUs allocated to the Glue job increases the total memory and compute resources available, allowing Spark to handle the 2 TB dataset without changing the job logic.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable S3 request rate increase to speed up data reading.
Why it's wrong here
Does not affect executor memory.
- ✓
Increase the number of DPUs allocated to the Glue job.
Why this is correct
More DPUs increase total memory available.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Repartition the data to a larger number of partitions.
Why it's wrong here
May help parallelism but not memory per executor if DPUs unchanged.
- ✗
Change the input format from Parquet to Snappy-compressed CSV.
Why it's wrong here
Format change does not fix memory; Snappy may be similar.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse memory issues with I/O bottlenecks or data skew, leading them to choose repartitioning or format changes, but the direct fix for insufficient executor memory is to increase DPUs.
Trap categories for this question
Similar concept trap
Format change does not fix memory; Snappy may be similar.
Detailed technical explanation
How to think about this question
AWS Glue allocates memory proportionally to DPUs, where each DPU provides 4 vCPU and 16 GB of memory (with 1 DPU reserved for the Spark driver in standard jobs). With 10 DPUs, only 9 DPUs (144 GB) are available for executors; processing 2 TB of Parquet data requires sufficient executor memory to hold working sets, shuffle data, and perform transformations. The OutOfMemoryError often occurs when the data size exceeds the aggregate executor memory, especially during wide transformations like joins or aggregations.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the number of DPUs allocated to the Glue job. — The OutOfMemoryError in the Spark executor indicates that the available memory per executor is insufficient for the data being processed. Increasing the number of DPUs allocated to the Glue job increases the total memory and compute resources available, allowing Spark to handle the 2 TB dataset without changing the job logic.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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