DEA-C01 Data Store Management Practice Question
Exhibit
Refer to the exhibit.
CREATE TABLE users (
user_id INT PRIMARY KEY,
username VARCHAR(50),
email VARCHAR(100)
) DISTSTYLE EVEN;
INSERT INTO users VALUES (1, 'alice', 'alice@example.com');
INSERT INTO users VALUES (2, 'bob', 'bob@example.com');A data engineer runs the above SQL commands on an Amazon Redshift cluster. The table 'users' is created with DISTSTYLE EVEN. What is the effect of the DISTSTYLE EVEN on query performance?
⚠ Common exam trap
Watch out — candidates often confuse DISTSTYLE EVEN with DISTSTYLE ALL, thinking EVEN improves performance by keeping data local, when in fact EVEN distributes data to prevent skew, not to localize it.
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
✓
It ensures data is evenly distributed across all nodes to prevent data skew.
DISTSTYLE EVEN in Amazon Redshift distributes rows across all nodes in a round-robin fashion, ensuring each node holds approximately the same amount of data. This prevents data skew, which can cause some nodes to become bottlenecks, and improves overall query performance for workloads that do not benefit from key-based distribution. It is the correct choice because it directly addresses the goal of balanced data distribution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It stores all data on a single node for fast local queries.
Why it's wrong here
EVEN distributes across nodes, not single node.
- ✓
It ensures data is evenly distributed across all nodes to prevent data skew.
Why this is correct
EVEN distribution spreads rows evenly, avoiding skew.
- ✗
It reduces data movement during queries by co-locating data based on user_id.
Why it's wrong here
Co-location requires DISTKEY on the joining column.
- ✗
It improves join performance when joining on user_id.
Why it's wrong here
EVEN does not co-locate related data; for joins, KEY distribution is better.
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