DBS-C01 Workload-Specific Database Design Practice Question
A gaming company uses Amazon DynamoDB for player profiles. The access pattern is to retrieve a player's profile by 'player_id'. Each profile includes a list of 'achievements' that can grow up to 400 KB. Recently, the application has been encountering 'ProvisionedThroughputExceededException' errors. The table has 1000 read capacity units (RCU) and 500 write capacity units (WCU). The average item size is 200 KB. What is the MOST likely cause of the throttling?
⚠ Common exam trap
The trap here is that candidates may overlook the RCU consumption difference between strongly consistent and eventually consistent reads, assuming all reads consume the same capacity, and instead blame hot partitions or item size limits.
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
✓
The application is using strongly consistent reads, which consume double the read capacity.
Strongly consistent reads in DynamoDB consume twice the read capacity units (RCUs) as eventually consistent reads. With an average item size of 200 KB, each strongly consistent read consumes 200 KB / 4 KB = 50 RCUs (rounded up). If the application is using strongly consistent reads, a single read of a 200 KB item uses 50 RCUs, which can quickly exhaust the 1000 RCU table capacity, especially under concurrent access, leading to ProvisionedThroughputExceededException.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The item size exceeds the DynamoDB item size limit of 400 KB.
Why it's wrong here
400 KB is the limit, but the error is throughput, not size.
- ✗
The read capacity units are set too low for the number of partitions.
Why it's wrong here
RCU is table-level, not per partition.
- ✗
The partition key 'player_id' is causing hot partitions.
Why it's wrong here
'player_id' is likely evenly distributed.
- ✓
The application is using strongly consistent reads, which consume double the read capacity.
Why this is correct
Strongly consistent reads consume twice as many RCUs as eventually consistent reads.
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