- A
Partition by date with one partition per day in a flat structure.
Why wrong: For large datasets, daily partitions can be too many; hierarchical partitioning is better.
- B
Do not partition; let Athena scan the entire dataset.
Why wrong: No partitioning leads to full scans, increasing cost and latency.
- C
Partition by year, month, and day in a hierarchical structure.
Hierarchical date partitioning enables partition pruning for date-range queries.
- D
Partition by source system first, then by date.
Why wrong: If queries often filter by date across sources, this partitioning may not be optimal.
Question 1,398 of 1,755
Hierarchical Partitioning for Date-Range Queries on Athena and Redshift Spectrum
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 data engineering team needs to build a data lake on Amazon S3 that will be queried by Amazon Athena and Amazon Redshift Spectrum. The data will be ingested from multiple sources in various formats (CSV, JSON, Parquet). Which partitioning strategy will provide the best query performance for date-range queries?
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
✓
Partition by year, month, and day in a hierarchical structure.
Option C is correct because partitioning by year, month, and day in a hierarchical structure minimizes the amount of data scanned by Amazon Athena and Redshift Spectrum for date-range queries. Athena and Redshift Spectrum both charge per byte scanned, so reducing the scan size directly improves performance and reduces cost. A hierarchical partition structure (e.g., s3://bucket/year=2023/month=11/day=01/) allows the query engine to prune partitions at each level, efficiently skipping irrelevant directories for queries like WHERE date BETWEEN '2023-11-01' AND '2023-11-30'.
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.
- ✗
Partition by date with one partition per day in a flat structure.
Why it's wrong here
For large datasets, daily partitions can be too many; hierarchical partitioning is better.
- ✗
Do not partition; let Athena scan the entire dataset.
Why it's wrong here
No partitioning leads to full scans, increasing cost and latency.
- ✓
Partition by year, month, and day in a hierarchical structure.
Why this is correct
Hierarchical date partitioning enables partition pruning for date-range queries.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Partition by source system first, then by date.
Why it's wrong here
If queries often filter by date across sources, this partitioning may not be optimal.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think a flat daily partition is simpler and sufficient, but they overlook that hierarchical partitioning (year/month/day) provides better partition pruning for range queries spanning months or years, which is a key optimization for Athena and Redshift Spectrum's cost and performance model.
Detailed technical explanation
How to think about this question
Under the hood, Athena and Redshift Spectrum use Hive-style partitioning, where partition columns are encoded as folder names in S3 (e.g., year=2023/month=11/day=01). When a query includes a filter on these columns, the query engine uses the AWS Glue Catalog or Hive Metastore to list only the relevant partitions, avoiding a full S3 LIST operation. In real-world scenarios, a hierarchical structure also reduces the number of partitions per directory (e.g., 12 months vs. 365 days), which improves the performance of partition discovery and metadata operations in highly partitioned tables.
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 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.
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: Partition by year, month, and day in a hierarchical structure. — Option C is correct because partitioning by year, month, and day in a hierarchical structure minimizes the amount of data scanned by Amazon Athena and Redshift Spectrum for date-range queries. Athena and Redshift Spectrum both charge per byte scanned, so reducing the scan size directly improves performance and reduces cost. A hierarchical partition structure (e.g., s3://bucket/year=2023/month=11/day=01/) allows the query engine to prune partitions at each level, efficiently skipping irrelevant directories for queries like WHERE date BETWEEN '2023-11-01' AND '2023-11-30'.
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.