Question 652 of 1,711
DEA-C01 Data Store Management Practice Question
A data engineering team is using Amazon DynamoDB to store time-series data for a monitoring application. The table has a primary key of device_id (partition key) and timestamp (sort key). The application queries data for a specific device over a time range. The team notices that read latency is high for devices that generate large amounts of data. They need to improve query performance. Which solution should they implement?
⚠ Common exam trap
The trap here is that candidates often mistake high read latency as a pure read-throughput issue and choose to increase RCUs or add DAX, overlooking the fact that the real bottleneck is write-side hot partitions causing throttling and increased latency for reads on that partition.
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 global secondary index with device_id as partition key and a truncated timestamp as sort key to distribute writes.
Creating a global secondary index (GSI) with device_id as the partition key and a truncated timestamp as the sort key helps distribute write traffic more evenly across partitions. This reduces hot partitions caused by devices that generate large amounts of data, thereby improving read latency by preventing throttling and reducing contention on a single partition.
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
Caches reads but does not address hot partition writes.
- ✗
Change the application to use eventually consistent reads.
Why it's wrong here
May not be acceptable for the monitoring application.
- ✓
Create a global secondary index with device_id as partition key and a truncated timestamp as sort key to distribute writes.
Why this is correct
Helps spread write load and improve read performance for time-range queries.
- ✗
Increase the read capacity units for the table.
Why it's wrong here
Does not address hot partition due to write patterns.
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Last reviewed: Jun 24, 2026
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