MLS-C01 Amazon Athena Practice Question
A data engineer needs to transform a large dataset stored in Amazon S3 using Apache Spark. The engineer wants to minimize costs and avoid managing infrastructure. Which AWS service should be used?
⚠ Common exam trap
Candidates often select Amazon Athena because it is serverless and low‑cost, but overlook the key requirement: the question explicitly states ‘using Apache Spark.’ Only AWS Glue (serverless) and Amazon EMR (cluster‑based) natively support Spark. Between them, AWS Glue eliminates infrastructure management, making it the correct choice.
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
✓
AWS Glue
AWS Glue is the optimal choice because it provides a serverless Apache Spark environment, fully managed, that allows the engineer to run Spark transformations without provisioning or managing clusters. This meets both requirements: using Apache Spark as specified, and minimizing costs and infrastructure management through its pay‑as‑you‑go, serverless model. Amazon Athena is a SQL query service and does not execute Apache Spark code. Amazon EMR provides Spark but typically requires cluster management (unless using EMR Serverless, which is not as straightforward as Glue for serverless Spark). Amazon SageMaker is focused on machine learning, not general ETL transformations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Athena
Why it's wrong here
Amazon Athena is a serverless query service for SQL, not Apache Spark. It cannot run Spark transformations.
- ✗
Amazon SageMaker
Why it's wrong here
Amazon SageMaker is a machine learning platform, not designed for general Spark-based data transformation.
- ✗
Amazon EMR
Why it's wrong here
Amazon EMR can run Spark but requires cluster provisioning and management, incurring costs for idle resources.
- ✓
AWS Glue
Why this is correct
AWS Glue provides serverless Spark execution, automatically scaling and costing only for active compute 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.