Quick Answer
The answer is to increase the number of Glue DPUs or enable auto-scaling, as this directly allocates more parallel processing power to the job. AWS Glue ETL performance scales with compute capacity, so adding Data Processing Units (DPUs) reduces runtime by distributing the workload across more executors, while auto-scaling dynamically adjusts resources based on the data volume. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your understanding of resource optimization for large-scale ETL jobs—a common scenario where candidates mistakenly think reducing DPUs or switching engines will help. The trap is confusing monitoring tools like Spark UI with performance tuning; Spark UI only helps identify bottlenecks, not fix them. To optimize AWS Glue ETL job performance, remember the mnemonic “More DPUs, less time”—if your job is slow and logic is fixed, throw more compute at it.
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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. 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 data engineer is using AWS Glue ETL to transform a large dataset in S3. The job processes 2 TB of data daily and currently runs for 6 hours. The engineer wants to reduce runtime without changing the transformation logic. What is the best approach?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Reduce the number of DPUs to minimize overhead.
Why wrong: Fewer DPUs will increase runtime.
Use the Spark UI to analyze bottlenecks and rewrite code.
Why wrong: The question states no change to transformation logic.
Increase the number of Glue DPUs or enable auto-scaling.
More DPUs provide parallel processing and reduce runtime.
Switch from Spark to Python shell.
Why wrong: Python shell is single-node and slower for large data.
Answer choices
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 Glue DPUs or enable auto-scaling.
Increasing DPUs or enabling auto-scaling can improve performance. Option A is correct. Option B is wrong because reducing DPUs would slow the job. Option C is wrong because using a different engine may not be compatible. Option D is wrong because Spark UI is for monitoring, not performance improvement.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Reduce the number of DPUs to minimize overhead.
Why it's wrong here
Fewer DPUs will increase runtime.
Use the Spark UI to analyze bottlenecks and rewrite code.
Why it's wrong here
The question states no change to transformation logic.
Increase the number of Glue DPUs or enable auto-scaling.
Why this is correct
More DPUs provide parallel processing and reduce runtime.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
Switch from Spark to Python shell.
Why it's wrong here
Python shell is single-node and slower for large data.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
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.
What to study next
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
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FAQ
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Static NAT maps one inside address to one outside address..
The correct answer is: Increase the number of Glue DPUs or enable auto-scaling. — Increasing DPUs or enabling auto-scaling can improve performance. Option A is correct. Option B is wrong because reducing DPUs would slow the job. Option C is wrong because using a different engine may not be compatible. Option D is wrong because Spark UI is for monitoring, not performance improvement.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DEA-C01 NAT questions on configuration and troubleshooting.
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Static NAT maps one inside address to one outside address.
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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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