MLS-C01 Data Engineering Practice Question
A data scientist wants to run a one-time SQL query on a large dataset stored in Amazon S3 (CSV format, 2 TB) using Amazon Athena. The query involves joining this dataset with a smaller table stored in Amazon RDS. What is the MOST cost-effective and performant approach?
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
✓
Export the RDS table to S3 in Parquet format, then use Athena to join the two S3 datasets
Exporting the RDS table to S3 as Parquet and running the join in Athena avoids data transfer costs and leverages Athena's fast query engine. Option B (federated query) adds complexity and may be slower. Option C (Redshift Spectrum) requires a Redshift cluster. Option D (Glue ETL) is overkill for a one-time query.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Export the RDS table to S3 in Parquet format, then use Athena to join the two S3 datasets
Why this is correct
This keeps the query in Athena's environment, avoiding data movement and using columnar format for performance.
- ✗
Use Amazon Redshift Spectrum to query both S3 and RDS
Why it's wrong here
Requires a Redshift cluster, which is costly for a one-time query.
- ✗
Use Athena Federated Query to query RDS directly
Why it's wrong here
Federated query is possible but may incur higher latency and data transfer costs.
- ✗
Use AWS Glue ETL to join the data and write results back to S3, then query with Athena
Why it's wrong here
Glue ETL adds unnecessary complexity and cost for a simple SQL join.
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 |
Go deeper
Related to this question
About these practice questions
One of 1,672 original MLS-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.