DEA-C01 Data Store Management Practice Question
A data engineer is using AWS Glue to catalog data stored in Amazon S3. The data is in Apache Parquet format and partitioned by year, month, and day. The engineer notices that AWS Glue crawlers are taking a long time to run and are not correctly identifying new partitions. The engineer needs to improve the crawler performance and ensure new partitions are added automatically. Which action should the engineer take?
⚠ Common exam trap
The trap here is assuming that increasing crawler resources or using custom classifiers will fix partition detection, but the real solution is to bypass crawling altogether with partition projection.
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 AWS Glue partition projection instead of crawling for partitions.
Partition projection in AWS Glue allows you to specify the partitioning scheme directly in the table properties, so the crawler does not need to discover partitions. This reduces crawler runtime and ensures that new partitions are immediately available for query engines like Athena. It is the most efficient solution for regularly partitioned data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use AWS Glue partition projection instead of crawling for partitions.
Why this is correct
AWS Glue partition projection allows you to define partition patterns and ranges without running crawlers. This eliminates the need for crawlers to discover partitions, significantly improving performance and ensuring new partitions are automatically available. It is ideal for data with a known, regular partitioning scheme like year/month/day.
- ✗
Enable the crawler option to update the Data Catalog with new partitions only, and set a partition index.
Why it's wrong here
While updating only new partitions can reduce crawler runtime, the key issue is that the crawler is not detecting new partitions at all. Setting a partition index helps with query performance in Athena but does not improve crawler partition discovery. This option does not fully address the problem.
- ✗
Increase the number of data processing units (DPUs) for the crawler.
Why it's wrong here
Increasing DPUs can speed up crawler execution, but it does not solve the fundamental issue of partition discovery. Crawlers still need to list and parse all objects, which can be slow and may miss new partitions if the crawler is not run frequently. This is a costly workaround, not a solution.
- ✗
Configure the crawler to use a custom classifier for Parquet.
Why it's wrong here
AWS Glue has a built-in classifier for Parquet, so a custom classifier is unnecessary. The issue is not with parsing the file format but with partition discovery. Using a custom classifier would not address the slow crawler runs or the failure to detect new partitions.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.