The correct answer is to convert the data to Parquet or ORC columnar format and partition the data. Athena charges based on the amount of data scanned, so columnar formats like Parquet drastically reduce I/O by reading only the columns needed for the query, while partitioning limits scans to relevant subdirectories instead of the entire bucket. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Athena’s cost model and data optimization for large-scale analytics, often appearing as a trap where candidates choose compression alone or more partitions—but too many small partitions can actually degrade performance. The key insight is that Athena performs poorly on hundreds of thousands of tiny CSV files because it must launch a separate read operation per file; columnar storage and partitioning directly address this by reducing both file count and scanned bytes. Memory tip: “Partition and Parquet—cut the scan, save the plan.”
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 has a large number of small CSV files (hundreds of thousands) in an S3 bucket. A data engineer needs to run a SQL query on this data using Amazon Athena. The queries are currently slow and expensive. Which two actions will improve query performance and reduce cost?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Partition the data by a commonly filtered column (e.g., date).
Option A and D are correct. Partitioning the data reduces the amount of data scanned by Athena, improving performance and reducing cost. Converting to columnar format (Parquet) further reduces scanned data and improves compression. Option B (compression) helps but is less impactful than partitioning and columnar format. Option C (more partitions) could help but too many small partitions may hurt performance. Option E (increasing S3 request rate) is not a direct action for Athena.
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 S3 request rate per prefix to improve read throughput.
Why it's wrong here
Athena handles S3 request rates; this is not a user-configurable action.
✗
Compress the CSV files using gzip.
Why it's wrong here
Compression reduces storage size but Athena still scans the entire uncompressed data.
✓
Partition the data by a commonly filtered column (e.g., date).
Why this is correct
Partitioning limits the data scanned per query, improving performance and reducing cost.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the number of partitions by splitting files into smaller ones.
Why it's wrong here
Too many small files can increase overhead and degrade performance.
✓
Convert the data to Parquet or ORC columnar format.
Why this is correct
Columnar formats reduce scanned data and improve compression and query performance.
Related concept
Read the scenario before looking for a memorised answer.
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.
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: Partition the data by a commonly filtered column (e.g., date). — Option A and D are correct. Partitioning the data reduces the amount of data scanned by Athena, improving performance and reducing cost. Converting to columnar format (Parquet) further reduces scanned data and improves compression. Option B (compression) helps but is less impactful than partitioning and columnar format. Option C (more partitions) could help but too many small partitions may hurt performance. Option E (increasing S3 request rate) is not a direct action for Athena.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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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.
Question Discussion
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