DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is using AWS Glue to perform ETL on data stored in an S3 bucket. The source data is in CSV format with a header row, and the target is a set of Parquet files partitioned by date. The engineer notices that the Glue job is reading all files in the source prefix, including temporary files that should be ignored. What is the MOST efficient way to exclude these temporary files?
⚠ Common exam trap
Many candidates assume Glue automatically ignores hidden or temporary files (like Spark's `_temporary` or Hadoop's `_SUCCESS`), but in reality, Glue reads all files under the specified prefix unless an explicit exclusion pattern is provided.
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 an S3 prefix exclusion pattern in the Glue job's source path.
AWS Glue supports S3 path exclusion patterns using glob-style syntax (e.g., `--exclude` or `excludePatterns` in the job parameters). By specifying a pattern like `**/_temporary/**` or `*.tmp`, the Glue job will skip those files during the read phase, avoiding unnecessary data processing and reducing costs. This is the most efficient approach as it requires no additional infrastructure or data movement.
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 source format from CSV to Parquet.
Why it's wrong here
Changing format does not exclude files; all files in the path would still be read.
- ✗
Set up an S3 event notification to trigger a Lambda function that moves temporary files.
Why it's wrong here
This adds unnecessary complexity and latency.
- ✓
Use an S3 prefix exclusion pattern in the Glue job's source path.
Why this is correct
Glue supports S3 include/exclude patterns to filter files.
- ✗
Create a custom classifier in the Glue Data Catalog.
Why it's wrong here
Classifiers are for inferring schema, not for file filtering.
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.