- A
Use G.1X or G.2X worker types and increase the number of DPUs per worker.
G.1X workers provide more memory and vCPU per worker, reducing OOM errors for memory-intensive transformations.
- B
Use Amazon Athena with CTAS queries to convert the data to Parquet.
Why wrong: Athena is interactive and incurs per-query costs; CTAS is good for one-time conversion but not for scheduled ETL workflows.
- C
Switch to S3 Batch Operations with AWS Lambda to process the files individually.
Why wrong: S3 Batch Operations is for simple object-level actions, not complex ETL like CSV-to-Parquet conversion.
- D
Increase the number of workers in the Glue job configuration.
Why wrong: Adding workers increases parallelism but does not increase memory per worker; memory errors persist if each task requires more memory.
Quick Answer
The correct answer is to use G.1X or G.2X worker types and increase the number of DPUs per worker. This resolves Glue ETL memory errors because these worker types allocate more memory per core—16 GB for G.1X and 32 GB for G.2X—directly addressing out-of-memory failures when processing large datasets. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of Glue job configuration for cost-effective reliability; a common trap is assuming that simply adding more standard workers will fix memory issues, but Spark’s shuffle operations can still cause memory pressure without increasing per-worker DPU allocation. Remember the memory tip: “G for Gigabytes—upgrade your worker type before you upgrade your worker count.”
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. 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 company uses AWS Glue ETL jobs to transform CSV data from an S3 bucket into Parquet. The jobs often fail with memory errors when processing large datasets. They want to minimize cost and improve reliability. What should they do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Use G.1X or G.2X worker types and increase the number of DPUs per worker.
Option B is correct because increasing the number of DPUs per worker and using G.1X workers provides more memory and compute per task, reducing out-of-memory errors. Option A is wrong because Spark's shuffle behavior can still cause memory issues even with more workers. Option C is wrong because S3 batch operations are not suitable for complex transformations. Option D is wrong because Presto is interactive, not designed for scheduled ETL.
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.
- ✓
Use G.1X or G.2X worker types and increase the number of DPUs per worker.
Why this is correct
G.1X workers provide more memory and vCPU per worker, reducing OOM errors for memory-intensive transformations.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Amazon Athena with CTAS queries to convert the data to Parquet.
Why it's wrong here
Athena is interactive and incurs per-query costs; CTAS is good for one-time conversion but not for scheduled ETL workflows.
- ✗
Switch to S3 Batch Operations with AWS Lambda to process the files individually.
Why it's wrong here
S3 Batch Operations is for simple object-level actions, not complex ETL like CSV-to-Parquet conversion.
- ✗
Increase the number of workers in the Glue job configuration.
Why it's wrong here
Adding workers increases parallelism but does not increase memory per worker; memory errors persist if each task requires more memory.
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.
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 MLS-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 MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use G.1X or G.2X worker types and increase the number of DPUs per worker. — Option B is correct because increasing the number of DPUs per worker and using G.1X workers provides more memory and compute per task, reducing out-of-memory errors. Option A is wrong because Spark's shuffle behavior can still cause memory issues even with more workers. Option C is wrong because S3 batch operations are not suitable for complex transformations. Option D is wrong because Presto is interactive, not designed for scheduled ETL.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-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.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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 MLS-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 MLS-C01 exam.
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