DEA-C01 Data Ingestion and Transformation Practice Question

A data engineer is configuring an AWS Glue crawler against an Amazon S3 path that contains CSV files with inconsistent column counts across files. The crawler keeps creating multiple tables for the same data and the engineer wants a single table with a merged schema. Which crawler configuration should the engineer change?

⚠ Common exam trap

The trap here is assuming that a custom classifier or partition metadata option controls table grouping, when only the single-schema-per-S3-path setting merges compatible schemas into one table.

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

✓

Set the crawler's 'Create a single schema for each S3 path' option to true.

The 'Create a single schema for each S3 path' crawler setting merges compatible schemas found under the same S3 path into one table. For CSV files with inconsistent column counts, enabling this option produces a single table with the union of compatible columns, eliminating the multiple tables the crawler was creating.

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 crawler's 'Maximum number of tables' limit in the crawler configuration.
Why it's wrong here
There is no 'Maximum number of tables' setting in an AWS Glue crawler configuration. The crawler creates tables based on schema grouping, not a numeric cap. Increasing a nonexistent limit would not merge schemas and would not address the root cause of multiple tables being created for the same S3 path.
✗
Enable the crawler's 'Update all new and existing partitions with metadata from the table' option.
Why it's wrong here
This option controls partition metadata inheritance, not schema merging. It determines whether new partitions inherit table-level properties such as column types. It has no effect on whether the crawler creates one table or multiple tables from files with different column counts in the same S3 path.
✓
Set the crawler's 'Create a single schema for each S3 path' option to true.
Why this is correct
This option, sometimes called 'CombineCompatibleSchemas', tells the crawler to merge compatible schemas that share the same S3 path into one table. When CSV files have varying column counts but compatible types, enabling this setting produces a single table with the union of columns instead of multiple tables, which is exactly what the engineer needs.
✗
Change the crawler's classifier to a custom classifier that forces all columns to string type.
Why it's wrong here
A custom classifier changes how the crawler parses and types data, but it does not merge schemas across files. Forcing all columns to string would alter the inferred schema but would still produce separate tables for incompatible schemas. The classifier does not control table grouping, so this would not achieve a single merged table.

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

DEA-C01 Data Ingestion and Transformation Practice Question

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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