Quick Answer
The correct answer is to create a global secondary index with score as the sort key. This strategy optimizes DynamoDB leaderboard optimization GSI sort key usage by allowing you to query the index in descending order and retrieve exactly the top 10 items, reading only those records rather than consuming read capacity units (RCUs) on a full table scan or filtering large datasets. On the AWS Certified Developer Associate DVA-C02 exam, this scenario tests your understanding of how GSIs minimize RCU consumption for read-heavy, sorted access patterns—a common trap is assuming a scan with a filter expression is efficient, but that still reads all items and wastes RCUs. Remember the memory tip: “GSI sort key for top scores—scan no more, query the door.”
This DVA-C02 practice question tests your understanding of troubleshooting and optimization. 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 developer is optimizing a DynamoDB table for a gaming leaderboard. The table stores player scores and is read-heavy. Queries often fetch the top 10 scores. Which indexing strategy best reduces RCU consumption?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Create a sparse index on player ID.
Why wrong: Sparse indexes are for non-existent attributes.
Use a local secondary index on score.
Why wrong: LSI shares RCU and does not reduce consumption.
Enable DynamoDB Accelerator (DAX) for caching.
Why wrong: DAX reduces latency but not RCU consumption.
Create a global secondary index with score as the sort key.
GSI allows efficient query for top scores.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Create a global secondary index with score as the sort key.
A global secondary index (GSI) with score as the sort key allows efficient retrieval of the top 10 scores by querying the index in descending order, reading only the required items. This minimizes read capacity unit (RCU) consumption compared to scanning the base table, as each query reads exactly 10 items (or fewer) rather than consuming RCUs for a full table scan or filtering large result sets.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Create a sparse index on player ID.
Why it's wrong here
Sparse indexes are for non-existent attributes.
Use a local secondary index on score.
Why it's wrong here
LSI shares RCU and does not reduce consumption.
Enable DynamoDB Accelerator (DAX) for caching.
Why it's wrong here
DAX reduces latency but not RCU consumption.
Create a global secondary index with score as the sort key.
Why this is correct
GSI allows efficient query for top scores.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often confuse local secondary indexes (LSIs) with global secondary indexes (GSIs), not realizing that LSIs are tied to the base table's partition key and cannot efficiently retrieve global top scores across all partitions.
Detailed technical explanation
When using a GSI with score as the sort key, DynamoDB physically stores items sorted by score within each partition, enabling efficient range queries. Querying the GSI with ScanIndexForward=false retrieves items in descending order, and setting Limit=10 ensures exactly 10 items are read, consuming only 10 RCUs (assuming items are under 4 KB each). This contrasts with a base table scan, which would read all items and consume RCUs proportional to total table size, even if only 10 results are returned.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Troubleshooting and Optimization — This question tests Troubleshooting and Optimization — Read the scenario before looking for a memorised answer..
The correct answer is: Create a global secondary index with score as the sort key. — A global secondary index (GSI) with score as the sort key allows efficient retrieval of the top 10 scores by querying the index in descending order, reading only the required items. This minimizes read capacity unit (RCU) consumption compared to scanning the base table, as each query reads exactly 10 items (or fewer) rather than consuming RCUs for a full table scan or filtering large result sets.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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