DEA-C01 Data Ingestion and Transformation Practice Question
Network Topology
Refer to the exhibit. A data engineer creates an AWS Glue job using this CloudFormation template. The job processes new data files in S3 and uses job bookmarks to track processed files. After initial success, the job runs again but processes all files again instead of only new ones. What is the most likely cause?
⚠ Common exam trap
Candidates often assume job bookmarks automatically track any new files in S3, but they fail to realize that without a partitioning scheme or timestamp in the path, Glue cannot differentiate new files from existing ones, leading to full reprocessing.
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
✓
The S3 input path does not have a partitioning scheme or timestamp to identify new files
AWS Glue job bookmarks rely on the structure of the input data to identify new files. Without a partitioning scheme or a timestamp-based naming convention in the S3 path, Glue cannot determine which files are new; it falls back to reprocessing all files. The job bookmark feature tracks processed files by examining the S3 path and file metadata, so a flat or non-partitioned structure prevents it from distinguishing new files from old ones.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The job bookmark option is set to 'job-bookmark-disable'
Why it's wrong here
The template shows 'job-bookmark-enable', so it is enabled.
- ✗
The enable-metrics parameter is set to true
Why it's wrong here
Metrics are for monitoring, not bookmarking.
- ✗
The MaxRetries parameter is set to 0
Why it's wrong here
MaxRetries does not affect bookmark behavior.
- ✓
The S3 input path does not have a partitioning scheme or timestamp to identify new files
Why this is correct
Job bookmarks rely on partition structure or file timestamps to track progress.
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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