DEA-C01 Data Store Management Practice Question
A company uses Amazon Redshift for analytics. The data engineering team wants to improve query performance for frequently used aggregate queries. Which TWO actions would help achieve this?
⚠ Common exam trap
A common mix-up: candidates confuse VACUUM (which reclaims space) with performance optimization for queries, or assume adding nodes always improves query speed without considering the overhead of data redistribution.
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
✓
Use distribution keys to collocate data on the same node slices
Distribution keys determine how data is distributed across node slices in Amazon Redshift. By choosing distribution keys that align with the join and aggregation columns, the database can collocate related data on the same slice, minimizing data movement during query execution. This directly improves performance for aggregate queries by reducing network traffic and enabling local computation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of WLM query queues
Why it's wrong here
WLM queues manage concurrency, not performance of individual queries.
- ✓
Use distribution keys to collocate data on the same node slices
Why this is correct
Distribution keys reduce data movement during joins and aggregations.
- ✗
Run the VACUUM command to reclaim space from deleted rows
Why it's wrong here
VACUUM reclaims storage space, not directly improve query performance.
- ✓
Define appropriate sort keys on the tables
Why this is correct
Sort keys minimize the number of blocks scanned for range-restricted queries.
- ✗
Increase the number of nodes in the cluster
Why it's wrong here
Adding nodes increases cost but may not improve performance if the issue is data distribution.
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