DEA-C01 Data Store Management Practice Question
A data engineer is troubleshooting slow query performance on an Amazon Redshift cluster. The cluster has 10 nodes and is using automatic distribution style. The engineer suspects that data distribution is causing excessive data movement. Which steps should the engineer take to diagnose and resolve the issue? (Choose THREE.)
⚠ Common exam trap
Many exam-takers confuse VACUUM (which only reorganizes data within slices) with distribution optimization, or assume scaling out nodes automatically resolves distribution-related performance issues without addressing the underlying key choice.
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
✓
Choose appropriate distribution keys for large tables
Choosing appropriate distribution keys for large tables ensures that data is evenly distributed across the cluster slices, minimizing the need for data redistribution during joins and aggregations. Automatic distribution style may not always select the optimal key, leading to excessive data movement and slow query performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Choose appropriate distribution keys for large tables
Why this is correct
Proper distribution keys minimize data movement.
- ✓
Use the EXPLAIN command to analyze query plans
Why this is correct
EXPLAIN shows distribution and data movement.
- ✗
Run the VACUUM command to reclaim space
Why it's wrong here
VACUUM does not address distribution.
- ✓
Query the STL_DIST and STL_BCAST system tables
Why this is correct
These tables show data redistribution statistics.
- ✗
Increase the number of nodes in the cluster
Why it's wrong here
Adding nodes may not fix distribution skew.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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