- A
Enable DynamoDB Accelerator (DAX) for the table
Why wrong: DAX provides an in-memory cache that reduces latency for repeated queries, but it does not reduce the number of read capacity units consumed on the table itself; it adds cost and complexity without improving the underlying query pattern.
- B
Increase the read capacity units on the table
Why wrong: Increasing read capacity units raises costs and does not improve query efficiency; the existing sort key already allows efficient retrieval.
- C
Use a global secondary index on post_timestamp
Why wrong: A GSI on post_timestamp lacks user_id as a partition key, so it cannot efficiently query posts for a single user; it would require a scan across all users.
- D
Create a local secondary index on user_id and post_timestamp
An LSI with the same partition and sort key as the base table allows a custom projection of attributes, reducing the amount of data read per query and thus lowering read capacity consumption. This optimizes cost for the frequent query of the five most recent posts per user.
DBS-C01 Local Secondary Index (LSI) Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. A key principle to apply: local Secondary Index (LSI). 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 social media startup stores user posts in Amazon DynamoDB with a partition key of user_id and sort key of post_timestamp. The application frequently queries the five most recent posts for a given user. Which design pattern improves query performance and reduces cost?
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
Create a local secondary index on user_id and post_timestamp
Option D is correct because creating a local secondary index (LSI) on user_id (same partition key) and post_timestamp as the sort key allows you to run a Query operation on the index with a limit of 5 items, sorted in descending order, to efficiently retrieve the most recent posts for a user. This targeted read reduces consumed read capacity units compared to scanning the base table, lowering cost. LSI also supports strongly consistent reads if needed. Option A (DAX) adds cost without reducing RCU for infrequent queries. Option B (increasing RCU) increases cost without improving efficiency. Option C (GSI on post_timestamp) cannot efficiently scope to a single user, leading to full scans and higher cost.
Key principle: Local Secondary Index (LSI)
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable DynamoDB Accelerator (DAX) for the table
Why it's wrong here
DAX provides an in-memory cache that reduces latency for repeated queries, but it does not reduce the number of read capacity units consumed on the table itself; it adds cost and complexity without improving the underlying query pattern.
- ✗
Increase the read capacity units on the table
Why it's wrong here
Increasing read capacity units raises costs and does not improve query efficiency; the existing sort key already allows efficient retrieval.
- ✗
Use a global secondary index on post_timestamp
Why it's wrong here
A GSI on post_timestamp lacks user_id as a partition key, so it cannot efficiently query posts for a single user; it would require a scan across all users.
- ✓
Create a local secondary index on user_id and post_timestamp
Why this is correct
An LSI with the same partition and sort key as the base table allows a custom projection of attributes, reducing the amount of data read per query and thus lowering read capacity consumption. This optimizes cost for the frequent query of the five most recent posts per user.
Related concept
Local Secondary Index (LSI)
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose a GSI on post_timestamp (Option C) thinking it will help with sorting, but without user_id as the partition key, the GSI cannot efficiently scope the query to a single user, leading to full scans and higher costs.
Detailed technical explanation
How to think about this question
A Local Secondary Index (LSI) maintains the same partition key (user_id) as the base table but allows a different sort key (post_timestamp). DynamoDB stores LSI data in the same partition as the base table, enabling efficient range queries with the Query API using ScanIndexForward=false and Limit=5 to retrieve the most recent posts with minimal read capacity. This design leverages DynamoDB's internal sorting and avoids the eventual consistency trade-offs of a GSI, which is critical for real-time social media feeds.
KKey Concepts to Remember
- Local Secondary Index (LSI)
- Query operation
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
Local Secondary Index (LSI)
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review local Secondary Index (LSI), then practise related DBS-C01 questions on the same topic to reinforce the concept.
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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 — Local Secondary Index (LSI).
What is the correct answer to this question?
The correct answer is: Create a local secondary index on user_id and post_timestamp — Option D is correct because creating a local secondary index (LSI) on user_id (same partition key) and post_timestamp as the sort key allows you to run a Query operation on the index with a limit of 5 items, sorted in descending order, to efficiently retrieve the most recent posts for a user. This targeted read reduces consumed read capacity units compared to scanning the base table, lowering cost. LSI also supports strongly consistent reads if needed. Option A (DAX) adds cost without reducing RCU for infrequent queries. Option B (increasing RCU) increases cost without improving efficiency. Option C (GSI on post_timestamp) cannot efficiently scope to a single user, leading to full scans and higher cost.
What should I do if I get this DBS-C01 question wrong?
Review local Secondary Index (LSI), then practise related DBS-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Local Secondary Index (LSI)
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Last reviewed: Jun 24, 2026
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