DEA-C01 Data Store Management Practice Question
A company uses Amazon Redshift for its data warehouse. The data engineering team notices that queries against a large fact table are slow. The table is distributed using DISTSTYLE EVEN and has multiple sort keys. After analyzing the query plans, they find that most queries filter on a specific column, 'customer_id'. Which change would most likely improve query performance for these filter operations?
⚠ Common exam trap
Many candidates confuse sort keys (which optimize data ordering within a slice) with distribution keys (which control data placement across slices), leading them to choose a sort key change when the real bottleneck is data distribution.
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
✓
Change to DISTSTYLE KEY on the 'customer_id' column.
Changing to DISTSTYLE KEY on 'customer_id' ensures that rows with the same customer_id are co-located on the same node slice. This allows the Redshift query engine to perform filter operations on a single slice rather than scanning all slices, dramatically reducing data movement and improving query performance for queries that filter on that column.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a secondary sort key on 'customer_id'.
Why it's wrong here
Sort keys help with range-restricted scans but not with distribution; data may still be scattered.
- ✓
Change to DISTSTYLE KEY on the 'customer_id' column.
Why this is correct
KEY distribution on the filtered column reduces data movement during queries.
- ✗
Change to DISTSTYLE EVEN with a different sort key.
Why it's wrong here
EVEN distributes rows randomly, not improving filter performance on a specific column.
- ✗
Change to DISTSTYLE ALL for the fact table.
Why it's wrong here
ALL distribution copies the entire table to all nodes, which is inefficient for large fact tables.
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Written by Johnson Ajibi, MSc IT Security
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