DEA-C01 Data Store Management Practice Question
A company is migrating an on-premises Hadoop cluster to AWS. The cluster processes large files in CSV format using Apache Spark. Which data store should be used as the primary storage for the data lake to optimize cost and performance?
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 S3
Amazon S3 is the most suitable primary storage for a data lake on AWS due to its high durability, scalability, and cost-effectiveness. It integrates seamlessly with Amazon EMR and Apache Spark for processing large CSV files. Option A is wrong because EMRFS is a connector that allows EMR to access data in S3, not a separate storage system; it is not an alternative to HDFS. Option B is wrong because Amazon RDS for MySQL is a relational database service, not designed for storing large-scale data lake files like CSV. Option C is wrong because Amazon EBS volumes are block-level storage for EC2 instances, which are limited in scalability and not cost-effective for large data lakes, especially when used as primary storage.
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 EMR File System (EMRFS) backed by HDFS
Why it's wrong here
EMRFS is actually a connector to S3; HDFS is ephemeral and not durable.
- ✗
Amazon RDS for MySQL
Why it's wrong here
RDS is not designed for storing large files; it is a relational database.
- ✗
Amazon EBS volumes attached to the EMR cluster
Why it's wrong here
EBS is expensive for large data volumes and not shared across instances.
- ✓
Amazon S3
Why this is correct
S3 provides unlimited storage, high durability, and integrates with EMR via EMRFS.
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
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