MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist needs to run a one-time SQL query on a large dataset in S3 to create a training dataset. The query involves aggregations and joins. Which service is most suitable?
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
✓
Amazon Athena
Amazon Athena is the correct choice because it is a serverless service that allows running SQL queries directly on data stored in S3, ideal for one-time ad-hoc queries with aggregations and joins. Option A (AWS Glue ETL) is designed for scheduled ETL jobs, not ad-hoc queries. Option C (Amazon EMR with Spark SQL) provides powerful processing but is overkill and requires cluster management. Option D (Amazon RDS) would require moving data into a database, which is inefficient.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Glue ETL job
Why it's wrong here
AWS Glue ETL is intended for extract, transform, and load jobs, not for one-time ad-hoc SQL queries.
- ✓
Amazon Athena
Why this is correct
Amazon Athena is serverless and optimized for querying data in S3 using standard SQL, making it suitable for this use case.
- ✗
Amazon EMR with Spark SQL
Why it's wrong here
Amazon EMR with Spark SQL offers distributed processing but involves cluster setup and management, which is excessive for a one-time query.
- ✗
Amazon RDS with data loaded into it
Why it's wrong here
Amazon RDS would require importing data from S3, adding complexity and time.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.