- A
Use AWS Glue ETL to read both datasets, join them using Spark DataFrames, and write the result to S3.
Why wrong: Glue ETL incurs DPU costs and may move data; Athena is simpler for this use case.
- B
Launch an Amazon EMR cluster with Spark, read data from S3, perform the join, and write results back to S3.
Why wrong: EMR incurs cluster costs and requires management; for ad-hoc joins, serverless options are more cost-effective.
- C
Use Amazon Athena to run a SQL query joining the two datasets directly on S3.
Athena queries data in place, charges per query scanned, and requires no infrastructure management.
- D
Load both datasets into Amazon Redshift using COPY commands, then perform the join in Redshift.
Why wrong: Redshift Spectrum can query S3 directly, but loading into Redshift incurs data transfer and storage costs.
Quick Answer
The answer is to use Amazon Athena to run a SQL query joining the two datasets directly on S3. This approach is correct because Athena is a serverless query service that allows you to join large datasets in S3 without moving data, leveraging its distributed SQL engine to scan only the necessary partitions and columns, which minimizes both data movement and cost for ad-hoc queries. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of cost-effective, serverless data processing patterns for ML training pipelines, often contrasting Athena with heavier alternatives like Redshift Spectrum (which still requires data loading for optimal performance) or EMR (which incurs cluster costs). A common trap is assuming Glue ETL is the default choice, but Glue typically moves data into a transformation environment, defeating the "no data movement" requirement. Memory tip: think "Athena = Ask directly in S3" — no moving, no provisioning, just query.
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 needs to create a training dataset by joining two large datasets (10 TB and 5 TB) stored in S3. The join key is 'user_id'. They want to minimize data movement and cost. Which approach should they use?
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 Amazon Athena to run a SQL query joining the two datasets directly on S3.
Option C is correct because Amazon Athena allows serverless SQL joins directly on S3 data without moving it, and is cost-effective for large ad-hoc queries. Option A is wrong because Redshift Spectrum still requires moving data into Redshift for optimal performance. Option B is wrong because EMR requires provisioning clusters and incurs compute costs even when idle. Option D is wrong because Glue ETL typically moves data into a transformation environment.
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 AWS Glue ETL to read both datasets, join them using Spark DataFrames, and write the result to S3.
Why it's wrong here
Glue ETL incurs DPU costs and may move data; Athena is simpler for this use case.
- ✗
Launch an Amazon EMR cluster with Spark, read data from S3, perform the join, and write results back to S3.
Why it's wrong here
EMR incurs cluster costs and requires management; for ad-hoc joins, serverless options are more cost-effective.
- ✓
Use Amazon Athena to run a SQL query joining the two datasets directly on S3.
Why this is correct
Athena queries data in place, charges per query scanned, and requires no infrastructure management.
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.
- ✗
Load both datasets into Amazon Redshift using COPY commands, then perform the join in Redshift.
Why it's wrong here
Redshift Spectrum can query S3 directly, but loading into Redshift incurs data transfer and storage costs.
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 Amazon Athena to run a SQL query joining the two datasets directly on S3. — Option C is correct because Amazon Athena allows serverless SQL joins directly on S3 data without moving it, and is cost-effective for large ad-hoc queries. Option A is wrong because Redshift Spectrum still requires moving data into Redshift for optimal performance. Option B is wrong because EMR requires provisioning clusters and incurs compute costs even when idle. Option D is wrong because Glue ETL typically moves data into a transformation environment.
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.
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Last reviewed: Jun 20, 2026
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