DEA-C01 Data Ingestion and Transformation Practice Question
A company is ingesting data from multiple sources into Amazon S3 using AWS Glue. The data is then transformed using Apache Spark on Amazon EMR. The data engineer wants to reduce the cost of storing and processing data by compressing the ingested files. Which THREE file formats support compression and are commonly used with Spark? (Choose THREE.)
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
✓
ORC
Correct options: A, B, and E. ORC, Parquet, and Avro all support compression and are commonly used with Spark. These formats are columnar (ORC and Parquet) or row-based with efficient compression (Avro), making them suitable for analytics. JSON and CSV support compression but are not columnar and less efficient for Spark processing; they are not the best choices for reducing storage and processing costs in this context.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
ORC
Why this is correct
ORC is a columnar format that supports compression and is optimized for Hive/Spark.
- ✓
Parquet
Why this is correct
Parquet is a columnar format that supports compression and is widely used with Spark.
- ✗
JSON
Why it's wrong here
JSON can be compressed but is not a columnar format and is less efficient for analytics.
- ✗
CSV
Why it's wrong here
CSV can be compressed but is not efficient for Spark processing.
- ✓
Avro
Why this is correct
Avro is a row-based format that supports compression and is used with Spark.
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 DEA-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 DEA-C01 exam.