- A
Increase NumberOfWorkers to 20
Why wrong: Increasing NumberOfWorkers adds more parallelism but does not increase memory per worker; the OutOfMemoryError persists.
- B
Reduce NumberOfWorkers to 5
Why wrong: Reducing NumberOfWorkers decreases parallelism and reduces total memory, likely making the memory error worse.
- C
Change WorkerType to G.1X
Correct. Changing WorkerType to G.1X doubles the memory per worker (from 4 GB to 8 GB), resolving the OutOfMemoryError.
- D
Increase MaxCapacity to 20
Why wrong: Increasing MaxCapacity to 20 does not increase memory per worker when NumberOfWorkers is set to 10; it only sets a higher total DPU limit but the job still uses 10 workers each with 1 DPU.
DEA-C01 AWS Glue Worker Types Practice Question
This DEA-C01 practice question tests your understanding of data operations and support. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. A key principle to apply: aWS Glue Worker Types. 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.
Refer to the exhibit. A data engineer sees this output from the AWS CLI for a failed Glue job. The job uses 10 workers of Standard type. What is the MOST appropriate action to resolve the OutOfMemoryError?
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
Change WorkerType to G.1X
The OutOfMemoryError occurs because each Standard worker has a memory limit of 4 GB. Increasing MaxCapacity to 20 does not increase memory per worker when NumberOfWorkers is explicitly set; it only increases the total DPU allocation but the job still uses 10 workers each with 1 DPU. The correct solution is to change the worker type to G.1X, which provides 2 DPUs (8 GB memory) per worker, effectively doubling the memory per worker and resolving the error. Option A (increase workers) adds parallelism but does not increase per-worker memory. Option B (reduce workers) decreases parallelism and may aggravate memory pressure. Option D (increase MaxCapacity) is ineffective when NumberOfWorkers is fixed.
Key principle: AWS Glue Worker Types
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 NumberOfWorkers to 20
Why it's wrong here
Increasing NumberOfWorkers adds more parallelism but does not increase memory per worker; the OutOfMemoryError persists.
- ✗
Reduce NumberOfWorkers to 5
Why it's wrong here
Reducing NumberOfWorkers decreases parallelism and reduces total memory, likely making the memory error worse.
- ✓
Change WorkerType to G.1X
Why this is correct
Correct. Changing WorkerType to G.1X doubles the memory per worker (from 4 GB to 8 GB), resolving the OutOfMemoryError.
Related concept
AWS Glue Worker Types
- ✗
Increase MaxCapacity to 20
Why it's wrong here
Increasing MaxCapacity to 20 does not increase memory per worker when NumberOfWorkers is set to 10; it only sets a higher total DPU limit but the job still uses 10 workers each with 1 DPU.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often mistakenly think increasing MaxCapacity raises memory per worker, but when NumberOfWorkers is set, MaxCapacity only sets the maximum total DPU; the job still uses exactly the specified number of workers each with the default DPU for the worker type.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- AWS Glue Worker Types
- MaxCapacity vs NumberOfWorkers
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
AWS Glue Worker Types
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. AWS Glue Worker Types Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Visual reference
What to study next
Got this wrong? Here's your next step.
Review aWS Glue Worker Types, then practise related DEA-C01 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this DEA-C01 question test?
Data Operations and Support — This question tests Data Operations and Support — AWS Glue Worker Types.
What is the correct answer to this question?
The correct answer is: Change WorkerType to G.1X — The OutOfMemoryError occurs because each Standard worker has a memory limit of 4 GB. Increasing MaxCapacity to 20 does not increase memory per worker when NumberOfWorkers is explicitly set; it only increases the total DPU allocation but the job still uses 10 workers each with 1 DPU. The correct solution is to change the worker type to G.1X, which provides 2 DPUs (8 GB memory) per worker, effectively doubling the memory per worker and resolving the error. Option A (increase workers) adds parallelism but does not increase per-worker memory. Option B (reduce workers) decreases parallelism and may aggravate memory pressure. Option D (increase MaxCapacity) is ineffective when NumberOfWorkers is fixed.
What should I do if I get this DEA-C01 question wrong?
Review aWS Glue Worker Types, then practise related DEA-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
AWS Glue Worker Types
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Last reviewed: Jun 20, 2026
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