DEA-C01 Data Operations and Support Practice Question
A company runs a Redshift cluster and notices that query performance has degraded over time. The data engineer suspects that table statistics are stale. What should the engineer do to improve query performance?
⚠ Common exam trap
Test-takers frequently confuse the VACUUM command (which reorganizes physical storage) with the ANALYZE command (which updates query optimizer metadata), leading candidates to choose VACUUM when stale statistics are the actual culprit.
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
✓
Run the ANALYZE command on the tables
Stale table statistics cause the Redshift query optimizer to generate suboptimal execution plans, leading to degraded query performance. Running the ANALYZE command updates these statistics, allowing the optimizer to make better decisions about join order, distribution, and data scan strategies. This directly addresses the root cause of performance degradation over time.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Rebuild the tables by using CREATE TABLE AS
Why it's wrong here
Rebuilding via CREATE TABLE AS physically rewrites and re-sorts the data, which does not address stale planner statistics. ANALYZE is what refreshes them. CTAS suits scenarios needing a full data reorganisation or a new materialised copy, not a statistics refresh on an existing table.
- ✗
Increase the number of slices in the cluster
Why it's wrong here
Slices are fixed at cluster creation and cannot be increased afterwards; resizing changes node type or count, not slice count. It is tempting because more slices do raise parallel query capacity, and a new cluster with more slices would be correct for a fresh workload, but stale statistics are refreshed by running ANALYZE.
- ✓
Run the ANALYZE command on the tables
Why this is correct
Stale statistics cause the Redshift query optimiser to misjudge cardinality, producing poor join orders and distribution choices. Running ANALYZE refreshes table statistics so the optimiser generates a more efficient plan, directly addressing the degraded performance described in the stem.
- ✗
Run the VACUUM command on the tables
Why it's wrong here
VACUUM reclaims storage and re-sorts rows after deletes and updates; it does not refresh the query planner's statistics. Stale statistics require ANALYZE. VACUUM is the right choice when tables have accumulated deleted rows or unsorted data causing scan inefficiency, not when cardinality estimates are outdated.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.