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Data Engineering →easyMultiple ChoiceObjective-mapped

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 machine learning team is using Amazon SageMaker to train models on a large dataset stored in Amazon S3. The dataset is 5 TB in size and is partitioned by date. The team wants to minimize data transfer costs and reduce training time by caching frequently accessed data locally on the training instances. The training instances are EC2 instances with attached Amazon EBS volumes. The team is considering using SageMaker Pipe mode to stream data directly from S3, but they are concerned about network bandwidth. Which approach should the team use to optimize data loading for training?

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.

A
Use Amazon FSx for Lustre as a high-performance file system linked to the S3 bucket, and mount it on the training instances.
Correct. Amazon FSx for Lustre provides a high-performance file system that integrates with S3 and caches data locally on the training instances, reducing data transfer costs and training time.
B
Use SageMaker File mode with Amazon EFS, which allows multiple training instances to share the same file system and caches data from S3.
Why wrong: Incorrect. SageMaker File mode uses EBS volumes, not Amazon EFS, and does not provide a shared, cached file system across multiple jobs as described.
C
Increase the size of the EBS volumes attached to the training instances and copy the entire dataset to the volumes before training.
Why wrong: Incorrect. Copying the entire 5 TB dataset to EBS volumes before training is inefficient, time-consuming, and costly, and does not cache data across training jobs.
D
Use SageMaker Pipe mode to stream data from S3 directly to the training algorithm, which automatically caches data in memory.
Why wrong: Incorrect. SageMaker Pipe mode streams data from S3 directly without caching, so it does not reduce data transfer for repeated access and may still encounter network bandwidth issues.

Full breakdown with real-world context →

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 Amazon FSx for Lustre as a high-performance file system linked to the S3 bucket, and mount it on the training instances.

Option A is correct because Amazon FSx for Lustre is natively integrated with Amazon SageMaker as a data source, providing a high-performance file system that can be linked directly to an S3 bucket. It automatically caches frequently accessed data from S3 on the file system, reducing data transfer costs and training time by avoiding repeated downloads. The caching capability addresses network bandwidth concerns effectively. Option B is incorrect: SageMaker File mode uses EBS volumes, not Amazon EFS, and is not designed as a shared, cached file system across training jobs. Option C is incorrect: copying the entire 5 TB dataset to EBS volumes before each training job is time-consuming, increases costs, and does not provide efficient caching across jobs. Option D is incorrect: SageMaker Pipe mode streams data directly from S3 without caching, so it does not reduce repeated data transfers and may still face bandwidth issues.

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 Amazon FSx for Lustre as a high-performance file system linked to the S3 bucket, and mount it on the training instances.
Why this is correct
Correct. Amazon FSx for Lustre provides a high-performance file system that integrates with S3 and caches data locally on the training instances, reducing data transfer costs and training time.
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 SageMaker File mode with Amazon EFS, which allows multiple training instances to share the same file system and caches data from S3.
Why it's wrong here
Incorrect. SageMaker File mode uses EBS volumes, not Amazon EFS, and does not provide a shared, cached file system across multiple jobs as described.
✗
Increase the size of the EBS volumes attached to the training instances and copy the entire dataset to the volumes before training.
Why it's wrong here
Incorrect. Copying the entire 5 TB dataset to EBS volumes before training is inefficient, time-consuming, and costly, and does not cache data across training jobs.
✗
Use SageMaker Pipe mode to stream data from S3 directly to the training algorithm, which automatically caches data in memory.
Why it's wrong here
Incorrect. SageMaker Pipe mode streams data from S3 directly without caching, so it does not reduce data transfer for repeated access and may still encounter network bandwidth issues.

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.

Visual reference

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

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 Amazon FSx for Lustre as a high-performance file system linked to the S3 bucket, and mount it on the training instances. — Option A is correct because Amazon FSx for Lustre is natively integrated with Amazon SageMaker as a data source, providing a high-performance file system that can be linked directly to an S3 bucket. It automatically caches frequently accessed data from S3 on the file system, reducing data transfer costs and training time by avoiding repeated downloads. The caching capability addresses network bandwidth concerns effectively. Option B is incorrect: SageMaker File mode uses EBS volumes, not Amazon EFS, and is not designed as a shared, cached file system across training jobs. Option C is incorrect: copying the entire 5 TB dataset to EBS volumes before each training job is time-consuming, increases costs, and does not provide efficient caching across jobs. Option D is incorrect: SageMaker Pipe mode streams data directly from S3 without caching, so it does not reduce repeated data transfers and may still face bandwidth issues.

What should I do if I get this MLS-C01 question wrong?

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.

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