DEA-C01 Data Operations and Support Practice Question
A data engineer is troubleshooting an Amazon Redshift cluster where nightly COPY loads from Amazon S3 are intermittently slow and sometimes fail with 'S3ServiceException' errors. The engineer suspects the cluster's network configuration and load design are contributing. Which TWO actions should the engineer take to improve load performance and reliability? (Choose two.)
⚠ Common exam trap
The trap here is assuming that fewer, larger compressed files reduce overhead, when Redshift COPY actually requires many files to parallelize across slices.
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
✓
Split large input files into multiple files sized roughly between 1 MB and 1 GB and load them in parallel.
Redshift COPY performance depends on parallelizing reads across slices and on a stable network path to S3. Splitting input into many files sized between 1 MB and 1 GB lets slices read concurrently, while enhanced VPC routing keeps S3 traffic inside the VPC and avoids public internet variability that produces intermittent S3ServiceException errors.
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 all input files to a single large gzip file to minimize the number of S3 GET requests during COPY.
Why it's wrong here
A single large compressed file cannot be parallelized across slices; only one slice reads it while others idle, which slows the load. Although compression reduces storage and network bytes, consolidating into one file defeats Redshift's parallel load design and can actually worsen performance rather than improve it.
- ✗
Increase the cluster's node count and change the distribution style of all tables to EVEN before every load.
Why it's wrong here
Adding nodes can increase parallelism, but changing every table to EVEN distribution before each load is unnecessary and can harm join performance for tables that benefit from KEY distribution. This does not address the network path or file layout issues causing the S3ServiceException errors and slow loads, so it is not an appropriate remedy.
- ✗
Disable compression on the input files so Redshift can parse records faster.
Why it's wrong here
Disabling compression increases the volume of data transferred from S3 and raises network and I/O load, which generally slows COPY. Redshift supports gzip, lzop, bzip2, and zstd compressed loads and benefits from the reduced transfer size, so removing compression would hurt performance and reliability rather than help.
- ✓
Split large input files into multiple files sized roughly between 1 MB and 1 GB and load them in parallel.
Why this is correct
Redshift parallelizes COPY across slices, and the number of files should be a multiple of the slice count for even distribution. Splitting large files into many smaller files within the 1 MB to 1 GB range lets each slice read its own file, dramatically improving load performance and reducing the chance that a single large file bottlenecks the load.
- ✓
Enable Amazon Redshift enhanced VPC routing so COPY traffic to S3 stays within the VPC and avoids public internet paths.
Why this is correct
Enhanced VPC routing forces COPY and UNLOAD traffic between Redshift and S3 through the VPC using endpoints and route tables, which avoids unpredictable public internet paths. This improves both reliability and throughput for S3 loads, and it lets you apply VPC security controls, directly addressing intermittent S3ServiceException errors caused by network variability.
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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JA
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.