DEA-C01 Data Store Management Practice Question
A company uses Amazon DynamoDB to store metadata for a document management system. The table has a partition key of document_id and a sort key of version. The application frequently queries for the latest version of a document by document_id. The data engineer notices that these queries are consuming a lot of read capacity. How can the engineer optimize the read performance and reduce read capacity consumption?
⚠ Common exam trap
Test-takers frequently think changing sort key order (Option A) reduces read capacity, but DynamoDB charges RCUs based on item size and read consistency, not sort order; the real optimization lies in indexing and caching strategies like GSI and DAX.
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 (GSI) and use DynamoDB Accelerator (DAX).
Creating a Global Secondary Index (GSI) with document_id as the partition key and version as the sort key, combined with DynamoDB Accelerator (DAX), allows the application to query the latest version efficiently. The GSI can be configured to project only the necessary attributes, reducing read capacity consumption, while DAX provides an in-memory cache that offloads repeated read requests from the DynamoDB table, significantly lowering read capacity units (RCUs) consumed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the sort key to store version in descending order.
Why it's wrong here
Changing sort key order does not reduce read capacity consumption.
- ✗
Enable DynamoDB Streams and use a read replica.
Why it's wrong here
DynamoDB does not have read replicas; streams are for change data capture.
- ✗
Decrease the ReadCapacityUnits of the table to force caching.
Why it's wrong here
Decreasing capacity would cause throttling, not caching.
- ✓
Create a global secondary index (GSI) and use DynamoDB Accelerator (DAX).
Why this is correct
A GSI can support efficient queries, and DAX caches results, reducing read capacity.
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