DEA-C01 Data Ingestion and Transformation Practice Question
A company uses AWS Glue ETL jobs to transform data stored in Amazon S3. The job reads data in Parquet format, applies transformations, and writes the output back to S3 in Parquet format. The team wants to improve the job's performance and reduce costs. Which action is MOST effective?
⚠ Common exam trap
Many exam-takers confuse 'coalesce' (reducing partitions) with 'repartition' (increasing parallelism) and assume fewer files always improve performance, ignoring that Glue ETL benefits from parallel reads across many small files when using columnar formats.
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 column pruning and predicate pushdown to read only necessary columns and filter data early.
Column pruning and predicate pushdown reduce the amount of data read from S3 by Spark-based AWS Glue ETL jobs. By reading only the necessary columns and filtering rows early in the scan, I/O and memory usage decrease, directly improving performance and reducing 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.
- ✗
Change the input format from Parquet to CSV to simplify parsing.
Why it's wrong here
CSV is less efficient than Parquet for analytics; would increase data volume and slow processing.
- ✗
Coalesce the input data into a single large file before processing.
Why it's wrong here
Single file reduces parallelism, likely increasing runtime.
- ✓
Use column pruning and predicate pushdown to read only necessary columns and filter data early.
Why this is correct
Reduces the amount of data processed, improving performance and reducing costs.
- ✗
Increase the number of workers to maximum allowed.
Why it's wrong here
More workers increase cost and may cause overhead; not optimal without need.
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
Related to this question
About these practice questions
One of 1,711 original DEA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
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.