DEA-C01 Data Ingestion and Transformation Practice Question
A company uses AWS Glue ETL to transform data from Amazon RDS for MySQL to Amazon S3. The Glue job reads from a JDBC connection. The job runs once daily and processes all records, but the data volume is growing. Which change would improve performance and reduce costs?
⚠ Common exam trap
Test-takers frequently assume increasing parallelism (Option A) is the universal fix for performance, overlooking the fact that reducing the data volume processed (Option D) is a more fundamental and cost-effective optimization.
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
✓
Enable Glue job bookmarking and set the job to process only new data
Enabling Glue job bookmarking allows the job to process only new or changed data since the last run, rather than reprocessing the entire dataset. This reduces both the data volume read from the JDBC source and the transformation time, directly improving performance and lowering costs by minimizing DPU usage.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of DPUs for the Glue job
Why it's wrong here
More DPUs increase cost and may not help if bottleneck is database.
- ✗
Switch to a Glue Python shell job
Why it's wrong here
A Glue Python shell job lacks the distributed processing engine (Apache Spark) required to handle the growing data volume from the JDBC connection; it runs on a single node and cannot parallelise reads from RDS for MySQL, so it would fail to improve performance and likely increase runtime. This option is tempting because Python shell jobs are ideal for lightweight, non-distributed tasks such as running SQL queries or calling APIs, where minimal overhead and lower cost are priorities.
- ✗
Use a higher JDBC fetch size
Why it's wrong here
Larger fetch size may improve throughput but still processes all data.
- ✓
Enable Glue job bookmarking and set the job to process only new data
Why this is correct
Bookmarking enables incremental loads.
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 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.