DEA-C01 Columnar Storage Practice Question
A company uses Amazon Athena to query data in S3. Recently, queries have become slow. The data is stored as CSV files in a partitioned table. What is the most effective way to improve query performance?
⚠ Common exam trap
A common trap is to think that simply increasing file size or using a more popular format like JSON will help. However, the key is switching to a columnar format (Parquet or ORC) that minimizes data scanned.
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
✓
Convert the data to Parquet format and optimize partitioning.
The correct answer. Parquet is a columnar storage format that allows Athena to read only the columns needed for a query, reducing I/O and improving performance. Combined with effective partitioning, it enables partition pruning, which further limits the data scanned. CSV files are row-based and require full scans, even with partitioning. Option A is incorrect because Athena is serverless and users cannot increase nodes; resources are managed automatically. Option C is incorrect: JSON is also row-based and verbose, making it even slower than CSV. Option D is incorrect because larger CSV files still lead to full scans; Parquet's columnar nature is more impactful than file size.
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 number of nodes in the Athena query engine.
Why it's wrong here
Increasing the number of nodes is not possible in Athena; it is serverless and scales automatically. This option is incorrect.
- ✓
Convert the data to Parquet format and optimize partitioning.
Why this is correct
Converting to Parquet (columnar) and optimizing partitioning reduces data scanned through column pruning and partition pruning, significantly improving performance. This is the correct answer.
- ✗
Convert the data to JSON format.
Why it's wrong here
Converting to JSON is a row-based format, often more verbose than CSV, leading to even larger data scans and worse performance. This option is incorrect.
- ✗
Increase the size of the CSV files to reduce the number of files.
Why it's wrong here
Increasing CSV file size alone does not help because CSV is row-based and still requires full scans. Parquet and proper partitioning are needed. This option is incorrect.
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
Related to this question
About these practice questions
One of 1,711 original DEA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
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 data engineer is troubleshooting a slow-running Amazon Athena query. The query scans a large amount of data. Which TWO actions can improve query performance? (Choose TWO.)
medium- ✓ A.Convert the data to Parquet or ORC format.
- B.Enable encryption at rest.
- C.Increase the Athena query timeout.
- ✓ D.Partition the table on frequently filtered columns.
- E.Use SELECT * to retrieve all columns.
Why A: Converting data to columnar formats like Parquet or ORC reduces the amount of data scanned, and partitioning the table on frequently filtered columns allows Athena to skip reading irrelevant partitions. Both actions improve query performance. Option B (encryption) does not affect performance. Option C (increasing timeout) only allows more time for a slow query, not improving performance. Option E (SELECT *) scans all columns, which increases data scanned and worsens performance.
JA
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.