Question 199 of 1,711
DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is ingesting CSV files from an Amazon S3 bucket into a Glue Data Catalog table. The files have headers, but some files have extra columns not present in the first file. The engineer wants the Glue crawler to automatically detect the schema. Which crawler configuration option should be used?
⚠ Common exam trap
Watch out — candidates often assume 'Merge tables' is about combining multiple tables into one, when in fact it merges schemas from multiple files within the same S3 path into a single table definition.
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
✓
Configure the crawler to 'Create a single schema for each S3 path' and enable 'Merge tables'.
When CSV files have varying schemas (extra columns), the Glue crawler must be configured to 'Create a single schema for each S3 path' with 'Merge tables' enabled. This configuration instructs the crawler to union the schemas from all files in the S3 path, adding new columns as they appear, rather than creating separate tables for each schema variation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure the crawler to 'Inherit schema from table' and set the table name.
Why it's wrong here
That option is for updating existing tables, not schema inference.
- ✓
Configure the crawler to 'Create a single schema for each S3 path' and enable 'Merge tables'.
Why this is correct
This merges schemas from all files in the path.
- ✗
Configure the crawler to 'Create a single schema for each S3 path' without enabling 'Merge tables'.
Why it's wrong here
Only uses the first file's schema.
- ✗
Configure the crawler to 'Create a single schema for each S3 path' and set 'Each file as a separate table'.
Why it's wrong here
Creates multiple tables, not desired.
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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Same concept, more angles
1 more way this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses AWS Glue to catalog data in Amazon S3. The data arrives in Parquet format, but the crawler fails to update the schema when new columns are added. What is the most likely cause?
medium- A.The Glue Data Catalog is not configured to accept schema changes.
- B.Parquet files do not support schema evolution.
- ✓ C.The crawler configuration has 'Update the table definition' set to 'Ignore the change'.
- D.The S3 bucket has versioning disabled.
Why C: The most likely cause of the crawler failing to detect schema changes is that its configuration option 'Update the table definition' is set to 'Ignore the change'. This prevents the crawler from adding new columns. Option A is incorrect because the Glue Data Catalog itself supports schema changes; the issue is with the crawler's configuration. Option B is incorrect because Parquet files do support schema evolution. Option D is incorrect because S3 bucket versioning does not affect how the crawler updates the schema.
Last reviewed: Jun 11, 2026
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