DEA-C01 Data Operations and Support Practice Question
A data engineer runs an Apache Spark application on Amazon EMR that writes partitioned Parquet output to Amazon S3. A downstream AWS Glue crawler registers the table in the Data Catalog, but Athena queries return zero rows for partitions added by the most recent run, while older partitions query correctly. The S3 objects exist and are readable. Which action should the engineer take?
⚠ Common exam trap
The trap here is assuming Athena discovers partitions by listing Amazon S3 at query time, when it actually reads partition definitions from the Data Catalog.
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
✓
Run MSCK REPAIR TABLE or an ALTER TABLE ADD PARTITION statement against the table so the catalog discovers the newly written partitions.
Athena and Glue rely on partition metadata stored in the Data Catalog. Spark writes to S3 without automatically registering partitions unless the table is configured for it, so new prefixes remain invisible to the query planner and return no rows. Running MSCK REPAIR TABLE or adding partitions explicitly synchronizes the catalog with the S3 layout and makes the new data queryable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Convert the table to use Athena partition projection with a date-based template that covers the new prefix layout.
Why it's wrong here
Partition projection computes partition locations from a defined pattern and table property instead of reading catalog entries, which does solve discovery problems, but it requires the partition values to follow a strict enumerable pattern and the table properties to be configured. It is a valid redesign, not the most direct corrective action for a table that already has catalog-based partitions.
- ✓
Run MSCK REPAIR TABLE or an ALTER TABLE ADD PARTITION statement against the table so the catalog discovers the newly written partitions.
Why this is correct
Athena resolves partitions from the Data Catalog, not by listing S3 at query time. When Spark writes new partition prefixes without registering them, the catalog has no entries for those paths and the query planner filters them out, returning empty results for the new data. Registering the partitions with MSCK REPAIR TABLE or ALTER TABLE ADD PARTITION makes the new prefixes queryable.
- ✗
Grant the crawler role s3:GetObject on the new partition prefixes so the crawler can inspect the files.
Why it's wrong here
If object reads were denied, the crawler would fail outright or log permission errors rather than silently register only older partitions. The described behavior is selective: prior partitions resolve and new ones do not, which points to catalog metadata rather than access control. Adding read permissions does not update partition metadata that is already stale.
- ✗
Increase the Athena query result reuse setting so previously cached partition metadata is invalidated.
Why it's wrong here
Result reuse caches query output for identical statements and does not refresh partition metadata held in the Data Catalog. Toggling it would not make the planner aware of new prefixes because the catalog still lacks entries for them. This misidentifies a metadata synchronization issue as a caching issue.
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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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.