- A
Use the COPY command from Amazon Redshift to pull data from RDS.
Why wrong: COPY command imports data into Redshift, not export from RDS.
- B
Use the SELECT INTO OUTFILE S3 extension to export the query results directly to S3.
This RDS feature allows exporting arbitrary SQL query results to S3.
- C
Use the AWS Schema Conversion Tool (SCT) to extract the data to S3.
Why wrong: SCT is for schema conversion, not data export.
- D
Use mysqldump to export the tables and then upload the files to S3.
Why wrong: mysqldump exports table by table, not a query result with joins; requires post-processing.
Question 614 of 1,730
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company runs a MySQL database on Amazon RDS. They need to export a subset of data to Amazon S3 for analysis using Amazon Athena. The data is stored in multiple tables with complex joins. What is the MOST efficient way to export the data?
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 the SELECT INTO OUTFILE S3 extension to export the query results directly to S3.
Option B is correct because Amazon RDS for MySQL supports the `SELECT INTO OUTFILE S3` extension, which allows you to export the results of complex queries (including joins) directly to Amazon S3 in a single, efficient operation. This avoids the overhead of intermediate staging or manual file transfers, making it the most efficient method for exporting a subset of data to S3 for Athena analysis.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 the COPY command from Amazon Redshift to pull data from RDS.
Why it's wrong here
COPY command imports data into Redshift, not export from RDS.
- ✓
Use the SELECT INTO OUTFILE S3 extension to export the query results directly to S3.
Why this is correct
This RDS feature allows exporting arbitrary SQL query results to S3.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use the AWS Schema Conversion Tool (SCT) to extract the data to S3.
Why it's wrong here
SCT is for schema conversion, not data export.
- ✗
Use mysqldump to export the tables and then upload the files to S3.
Why it's wrong here
mysqldump exports table by table, not a query result with joins; requires post-processing.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the AWS Schema Conversion Tool (SCT) as a data extraction tool, when it is actually designed for schema assessment and conversion, not for efficient query-based data export to S3.
Trap categories for this question
Command / output trap
COPY command imports data into Redshift, not export from RDS.
Detailed technical explanation
How to think about this question
The `SELECT INTO OUTFILE S3` extension works by having the RDS MySQL engine stream query results directly to a specified S3 bucket using the AWS SDK, supporting parallel writes for large datasets. This feature requires the `rds_s3_role` IAM role and the `aurora_select_into_s3` or `mysql_select_into_s3` parameter group setting, and it automatically handles file partitioning and compression (e.g., GZIP) for optimal Athena performance. A real-world scenario is exporting a daily aggregated sales report from a normalized RDS database with multiple joins, where this method avoids the latency and cost of intermediate EC2 instances or ETL pipelines.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the SELECT INTO OUTFILE S3 extension to export the query results directly to S3. — Option B is correct because Amazon RDS for MySQL supports the `SELECT INTO OUTFILE S3` extension, which allows you to export the results of complex queries (including joins) directly to Amazon S3 in a single, efficient operation. This avoids the overhead of intermediate staging or manual file transfers, making it the most efficient method for exporting a subset of data to S3 for Athena analysis.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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