DEA-C01 Data Store Management Practice Question
A company has an Amazon Redshift cluster that stores petabytes of data. Queries are experiencing high disk usage due to large intermediate results. The data engineer needs to improve query performance without adding more nodes. Which action should the engineer take?
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
✓
Set appropriate distribution keys to minimize data movement.
Setting appropriate distribution keys can minimize data movement during joins and aggregations, which directly reduces the size of intermediate results spilled to disk. This improves query performance without adding nodes. Option C (compression) reduces storage size and I/O but does not directly address disk usage from large intermediate results. Option B (WLM) limits concurrency, not disk usage. Option D (sort keys) improves scan efficiency, not intermediate result size.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set appropriate distribution keys to minimize data movement.
Why this is correct
Distribution keys reduce data shuffling but not intermediate results.
- ✗
Configure workload management (WLM) queues to limit concurrency.
Why it's wrong here
WLM queues manage query slots, not disk usage.
- ✗
Apply column compression encoding to reduce data size.
Why it's wrong here
Compression reduces disk footprint and I/O, improving performance.
- ✗
Define sort keys on all columns used in WHERE clauses.
Why it's wrong here
Sort keys improve scan efficiency but not intermediate result size.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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