- A
Increase the Spark memory overhead parameter in the Glue job configuration.
Allocates more memory per worker for Spark processing, reducing OOM errors.
- B
Use DynamicFrame instead of Spark DataFrame for transformations.
Why wrong: DynamicFrame is built on Spark; memory usage is similar.
- C
Increase the number of workers to maximum allowed.
Why wrong: More workers increase parallelism and cost but each worker still has limited memory; may not solve OOM if memory per worker is insufficient.
- D
Switch from a Spark job to a Python shell job.
Why wrong: Python shell jobs are for lightweight processing; not suitable for large transformations.
- E
Change the worker type from 'G.1x' to 'G.2x' to double memory per worker.
Doubles memory per worker, addressing OOM with moderate cost increase.
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 is using AWS Glue to run ETL jobs that transform data from Amazon S3 to Amazon Redshift. The jobs are failing intermittently with 'Out of Memory' errors. The team wants to resolve this issue without increasing costs significantly. Which TWO actions should the team take?
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 Spark memory overhead parameter in the Glue job configuration.
The correct answers are A and C. Increasing Spark memory overhead per worker (option A) provides more memory for Spark operations. Using the 'g.2x' worker type (option C) offers more memory per worker compared to 'g.1x' without doubling cost. Option B (increasing number of workers) increases cost linearly. Option D (using Python shell) is not suitable for large data. Option E (using DynamicFrame) does not address memory.
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.
- ✓
Increase the Spark memory overhead parameter in the Glue job configuration.
Why this is correct
Allocates more memory per worker for Spark processing, reducing OOM errors.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use DynamicFrame instead of Spark DataFrame for transformations.
Why it's wrong here
DynamicFrame is built on Spark; memory usage is similar.
- ✗
Increase the number of workers to maximum allowed.
Why it's wrong here
More workers increase parallelism and cost but each worker still has limited memory; may not solve OOM if memory per worker is insufficient.
- ✗
Switch from a Spark job to a Python shell job.
Why it's wrong here
Python shell jobs are for lightweight processing; not suitable for large transformations.
- ✓
Change the worker type from 'G.1x' to 'G.2x' to double memory per worker.
Why this is correct
Doubles memory per worker, addressing OOM with moderate cost increase.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Similar concept trap
DynamicFrame is built on Spark; memory usage is similar.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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 Spark memory overhead parameter in the Glue job configuration. — The correct answers are A and C. Increasing Spark memory overhead per worker (option A) provides more memory for Spark operations. Using the 'g.2x' worker type (option C) offers more memory per worker compared to 'g.1x' without doubling cost. Option B (increasing number of workers) increases cost linearly. Option D (using Python shell) is not suitable for large data. Option E (using DynamicFrame) does not address memory.
What should I do if I get this DEA-C01 question wrong?
Identify which DEA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 20, 2026
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.
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