MLS-C01 Data Engineering Practice Question
Network Topology
A data engineer runs the AWS CLI command above to inspect an object in S3. The engineer wants to query this metadata (kafka-offset) using Amazon Athena to track processing progress. How can the engineer make this metadata available for Athena queries without modifying the existing data pipeline?
⚠ Common exam trap
Test-takers frequently assume Athena can natively query S3 object metadata (like HTTP headers) because Athena can query data in S3, but Athena has no access to object-level metadata—it only reads the content of files, not the object's key-value metadata fields.
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
✓
Use AWS Glue to create a table that includes the metadata as a column by running an ETL job.
AWS Glue ETL jobs can read the S3 object's user-defined metadata (e.g., 'kafka-offset') and write it as a column in a new or transformed dataset, which Athena can then query. This approach does not modify the existing data pipeline, as the original objects remain unchanged; the metadata is extracted and stored in a queryable format (e.g., Parquet or CSV) in a separate location. Glue's ability to access S3 object metadata via the `getObjectMetadata` API during ETL processing makes this a clean, pipeline-agnostic solution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use S3 object tags instead of metadata and query the tags using Athena.
Why it's wrong here
Athena does not query S3 object tags.
- ✗
Use an AWS Lambda function to copy the metadata into the object's content as a new line.
Why it's wrong here
Modifying object content would change the data and is not recommended.
- ✓
Use AWS Glue to create a table that includes the metadata as a column by running an ETL job.
Why this is correct
A Glue ETL job can read objects, extract metadata, and write to a table that Athena can query.
- ✗
Use Amazon Athena to query the object metadata directly by referencing the metadata field.
Why it's wrong here
Athena cannot query S3 object metadata directly.
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
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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.