MLS-C01 Data Engineering Practice Question
A data engineer needs to set up a data lake on S3 that supports both batch and streaming ingestion. The data must be queryable by Athena, Redshift Spectrum, and EMR. Which TWO configurations are essential? (Choose two.)
⚠ Common exam trap
It's easy for candidates to confuse the ingestion mechanism (e.g., Kinesis Data Firehose) with the essential data lake configuration, or assume that S3 Select is required for queryability, when in fact the core requirements are a unified metadata catalog and an efficient storage format.
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
✓
Store data in columnar formats like Parquet or ORC.
Columnar formats like Parquet and ORC are optimized for analytical queries, reducing I/O by reading only the necessary columns. This is essential for Athena, Redshift Spectrum, and EMR, which all benefit from the efficient compression and predicate pushdown capabilities of these formats, enabling faster query performance and lower costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Store data in columnar formats like Parquet or ORC.
Why this is correct
Columnar formats improve query performance and reduce scan costs for Athena and Redshift Spectrum.
- ✓
Use the AWS Glue Data Catalog as a central metadata repository.
Why this is correct
Athena, Redshift Spectrum, and EMR all integrate with the Glue Data Catalog.
- ✗
Enable S3 Select on the target buckets.
Why it's wrong here
S3 Select is a feature for filtering data, not a configuration required for querying.
- ✗
Enable S3 versioning on all buckets.
Why it's wrong here
Versioning is for data protection, not necessary for querying.
- ✗
Set up Kinesis Data Firehose for streaming ingestion.
Why it's wrong here
Streaming ingestion is optional; the question asks for essential configurations.
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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