- A
Remove the partition structure and store data as single large files.
Why wrong: Without partitions, queries will scan all data.
- B
Convert the Parquet files to JSON format for better query performance.
Why wrong: JSON is larger and slower than Parquet.
- C
Use CSV format with Gzip compression.
Why wrong: CSV is not columnar and will scan more data.
- D
Add more partition columns such as hour to reduce the scanned partitions.
More granular partitions allow queries to scan fewer files.
Question 689 of 1,755
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 company runs a data lake on Amazon S3 with partitions by year/month/day. A machine learning team needs to read daily data from the last 30 days for model retraining. The data format is Parquet. The team uses Amazon Athena to query the data, but the queries are slow and scanning too much data. The team has already optimized the file sizes and compression. What additional step can reduce the amount of data scanned?
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
✓
Add more partition columns such as hour to reduce the scanned partitions.
Option D is correct because adding more granular partition columns, such as hour, enables more precise partition pruning in Athena. If the query includes a filter on the hour column (e.g., WHERE hour BETWEEN 9 AND 17), Athena will only read the partitions corresponding to those hours, reducing the amount of data scanned. Even if the current query does not filter on hour, this additional partition provides flexibility to reduce scanned data when only specific hours are needed per day. Since the team can modify their query to include an hour filter, this step can significantly reduce the data scanned, especially when combined with existing year/month/day partitions.
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.
- ✗
Remove the partition structure and store data as single large files.
Why it's wrong here
Without partitions, queries will scan all data.
- ✗
Convert the Parquet files to JSON format for better query performance.
Why it's wrong here
JSON is larger and slower than Parquet.
- ✗
Use CSV format with Gzip compression.
Why it's wrong here
CSV is not columnar and will scan more data.
- ✓
Add more partition columns such as hour to reduce the scanned partitions.
Why this is correct
More granular partitions allow queries to scan fewer files.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think removing partitions or changing file formats (like JSON or CSV) will help, but the core issue is insufficient partition granularity; the exam tests understanding that partition pruning is the primary mechanism to reduce scanned data in Athena.
Detailed technical explanation
How to think about this question
Partition pruning in Athena works by using the Hive-style partition layout (e.g., year=2025/month=03/day=15/hour=10) to skip reading entire directories that don't match the WHERE clause. Parquet's columnar format further reduces I/O by reading only the required columns, and combining fine-grained partitions with columnar storage maximizes efficiency. In practice, adding hour-level partitions is effective when data arrives frequently and queries target specific time windows, but over-partitioning (e.g., minute-level) can create too many small files, degrading performance due to S3 list operations.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Data Engineering — study guide chapter
Learn the concepts, then practise the questions
- →
Data Engineering practice questions
Targeted practice on this topic area only
- →
All MLS-C01 questions
1,755 questions across all exam domains
- →
AWS Certified Machine Learning Specialty MLS-C01 study guide
Full concept coverage aligned to exam objectives
- →
MLS-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related MLS-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Data Engineering practice questions
Practise MLS-C01 questions linked to Data Engineering.
Machine Learning Implementation and Operations practice questions
Practise MLS-C01 questions linked to Machine Learning Implementation and Operations.
Modeling practice questions
Practise MLS-C01 questions linked to Modeling.
Exploratory Data Analysis practice questions
Practise MLS-C01 questions linked to Exploratory Data Analysis.
MLS-C01 fundamentals practice questions
Practise MLS-C01 questions linked to MLS-C01 fundamentals.
MLS-C01 scenario practice questions
Practise MLS-C01 questions linked to MLS-C01 scenario.
MLS-C01 troubleshooting practice questions
Practise MLS-C01 questions linked to MLS-C01 troubleshooting.
Practice this exam
Start a free MLS-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
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: Add more partition columns such as hour to reduce the scanned partitions. — Option D is correct because adding more granular partition columns, such as hour, enables more precise partition pruning in Athena. If the query includes a filter on the hour column (e.g., WHERE hour BETWEEN 9 AND 17), Athena will only read the partitions corresponding to those hours, reducing the amount of data scanned. Even if the current query does not filter on hour, this additional partition provides flexibility to reduce scanned data when only specific hours are needed per day. Since the team can modify their query to include an hour filter, this step can significantly reduce the data scanned, especially when combined with existing year/month/day partitions.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More MLS-C01 practice questions
- A company needs to transfer 10 TB of data from an on-premises data center to Amazon S3. The network bandwidth is limited…
- A company is using Amazon Kinesis Data Streams to ingest real-time clickstream data. The data is consumed by a Lambda fu…
- A team is building a data pipeline to process terabytes of log data daily using Amazon EMR. The data arrives in 5-minute…
- A data science team is building a real-time fraud detection system. Transactions are streamed via Amazon Kinesis Data St…
- A company uses Amazon SageMaker to train and deploy machine learning models. The training data is stored in Amazon S3 (P…
- A data engineering team is designing a data lake on AWS for machine learning workloads. The data includes structured, se…
Last reviewed: Jul 4, 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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.