MLS-C01 Data Engineering Practice Question
A company uses Amazon Redshift for its data warehouse. The data engineering team notices that queries are slow and wants to improve performance without changing the schema. Which action is most likely to improve query performance?
⚠ Common exam trap
A common mix-up: candidates confuse 'distribution style' with 'node count' and assume that changing to EVEN will always balance data evenly and improve performance, but in practice EVEN can cause costly data redistribution during joins, whereas scaling out nodes is a safer and more direct performance lever.
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
✓
Increase the number of nodes in the cluster.
Increasing the number of nodes in an Amazon Redshift cluster distributes data and query processing across more compute resources, which directly improves parallel execution and reduces query execution time. This is the most effective way to boost performance without altering the schema, as it scales the cluster's CPU, memory, and I/O capacity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Decrease the number of nodes to reduce network overhead.
Why it's wrong here
Fewer nodes reduce parallel processing capacity.
- ✗
Disable compression on all tables to reduce CPU overhead.
Why it's wrong here
Disabling compression increases storage and I/O, slowing queries.
- ✓
Increase the number of nodes in the cluster.
Why this is correct
Adding nodes increases parallelism and improves query performance.
- ✗
Change the distribution style from AUTO to EVEN.
Why it's wrong here
This changes the schema and may not always improve performance.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.