- A
Partition the large table by the foreign key column.
Why wrong: Partitioning can improve data management but may not speed up joins without proper indexing.
- B
Scale up the RDS instance to a larger size.
Why wrong: Scaling up may improve throughput but does not address the root cause of missing indexes.
- C
Add an index on the foreign key column in the large table.
An index on the join column allows the database to quickly find matching rows, dramatically improving join performance.
- D
Create a read replica and direct all read queries to it.
Why wrong: Read replicas help with read scaling but do not optimize individual query execution.
Question 1,662 of 1,730
Improve Join Performance: Adding Index on Foreign Key
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 an OLTP workload on an RDS for MySQL instance. The database has a table with 50 million rows. The application frequently runs queries that join this table with a small lookup table (1000 rows) using a foreign key. The queries are slow. Which design change would most improve performance?
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
✓
Add an index on the foreign key column in the large table.
The query joins a large table (50M rows) with a small lookup table (1000 rows) on a foreign key column. Without an index on the foreign key column in the large table, MySQL must perform a full table scan for each join, leading to slow performance. Adding an index on that column allows MySQL to use an index lookup (e.g., B-tree) to quickly locate matching rows, dramatically reducing query time.
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.
- ✗
Partition the large table by the foreign key column.
Why it's wrong here
Partitioning can improve data management but may not speed up joins without proper indexing.
- ✗
Scale up the RDS instance to a larger size.
Why it's wrong here
Scaling up may improve throughput but does not address the root cause of missing indexes.
- ✓
Add an index on the foreign key column in the large table.
Why this is correct
An index on the join column allows the database to quickly find matching rows, dramatically improving join performance.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a read replica and direct all read queries to it.
Why it's wrong here
Read replicas help with read scaling but do not optimize individual query execution.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The DBS-C01 exam often tests the misconception that partitioning or read replicas can fix join performance issues, but the real bottleneck is typically a missing index on the join column in the large table.
Detailed technical explanation
How to think about this question
In MySQL, a foreign key constraint does not automatically create an index on the referencing column in the child table (though InnoDB does create an index on the referencing column for foreign key enforcement). For a join between a large table and a small lookup table, a nested-loop join without an index on the large table's foreign key column results in a full table scan of the large table for each row in the small table (or vice versa). Adding a B-tree index on the foreign key column enables an index lookup, reducing the join complexity from O(N*M) to O(N*log(M)) or better.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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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: Add an index on the foreign key column in the large table. — The query joins a large table (50M rows) with a small lookup table (1000 rows) on a foreign key column. Without an index on the foreign key column in the large table, MySQL must perform a full table scan for each join, leading to slow performance. Adding an index on that column allows MySQL to use an index lookup (e.g., B-tree) to quickly locate matching rows, dramatically reducing query time.
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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