- A
Increase the number of DPUs for the Glue job.
More DPUs increase parallelism and speed up processing.
- B
Decrease the number of workers in the Glue job.
Why wrong: Fewer workers reduce parallelism and increase time.
- C
Disable Spark shuffle operations.
Why wrong: Shuffles are often necessary for joins/aggregations; disabling may break logic.
- D
Reduce the dataset size by sampling.
Why wrong: Sampling loses data; not a performance improvement for full dataset.
Question 1,392 of 1,755
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. 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 machine learning team is using AWS Glue to prepare data for training. They notice that the ETL job takes a long time to process large datasets. Which change is most likely to improve performance?
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 for the Glue job.
Increasing the number of DPUs (Data Processing Units) for the AWS Glue job allocates more distributed computing resources, which allows the job to process data in parallel across more executors. This directly reduces the runtime for large datasets by improving the parallelism of Spark transformations and actions.
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 number of DPUs for the Glue job.
Why this is correct
More DPUs increase parallelism and speed up processing.
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.
- ✗
Decrease the number of workers in the Glue job.
Why it's wrong here
Fewer workers reduce parallelism and increase time.
- ✗
Disable Spark shuffle operations.
Why it's wrong here
Shuffles are often necessary for joins/aggregations; disabling may break logic.
- ✗
Reduce the dataset size by sampling.
Why it's wrong here
Sampling loses data; not a performance improvement for full dataset.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think reducing workers or disabling shuffle will speed up the job, but they fail to recognize that AWS Glue's performance is primarily limited by parallelism, and reducing resources or core Spark operations will degrade or break the job.
Detailed technical explanation
How to think about this question
AWS Glue uses Apache Spark under the hood, where DPUs represent a unit of processing power (4 vCPU, 16 GB memory). Increasing DPUs scales the number of Spark executors, enabling more concurrent task slots for reading, transforming, and writing data. However, there is a diminishing return beyond a certain point due to Spark driver overhead and shuffle bottlenecks, so optimal DPU count should be tuned based on dataset size and complexity.
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 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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — 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 for the Glue job. — Increasing the number of DPUs (Data Processing Units) for the AWS Glue job allocates more distributed computing resources, which allows the job to process data in parallel across more executors. This directly reduces the runtime for large datasets by improving the parallelism of Spark transformations and actions.
What should I do if I get this MLS-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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