MLS-C01 Data Engineering Practice Question
A company is using Amazon Redshift for data warehousing. The data engineering team observes that query performance degrades over time due to data skew. Which three strategies should the team implement to improve performance?
⚠ Common exam trap
Many exam-takers confuse Redshift's distribution and sort keys with traditional database indexes, leading them to select option E, or they mistakenly believe that scaling out nodes (option B) automatically fixes skew-related performance issues.
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 based on join and group-by columns.
Choosing appropriate distribution keys based on join and group-by columns minimizes data movement across nodes during query execution. In Amazon Redshift, data is distributed across compute nodes according to the distribution key; aligning it with frequently joined or aggregated columns ensures that related rows are co-located on the same slice, reducing network shuffling and improving 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 based on join and group-by columns.
Why this is correct
Good distribution keys reduce data movement and improve performance.
- ✗
Increase the number of nodes in the Redshift cluster.
Why it's wrong here
Adding nodes increases capacity but does not directly address data skew.
- ✓
Run VACUUM and ANALYZE commands regularly.
Why this is correct
VACUUM reclaims space and ANALYZE updates statistics for the query optimizer.
- ✓
Define appropriate sort keys to minimize the number of blocks scanned.
Why this is correct
Sort keys enable zone maps to skip irrelevant blocks, improving scan performance.
- ✗
Drop unused indexes on large tables.
Why it's wrong here
Redshift does not use indexes; it uses sort keys and distribution styles.
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