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
DISTSTYLE EVEN spreads rows across all slices of every node, not onto one node; single-node storage describes no Redshift distribution style. It is tempting because localising data avoids network transfer, but ALL distribution replicates the full table to every node, which suits small dimension tables.
- ✓
It ensures data is evenly distributed across all nodes to prevent data skew.
Why this is correct
DISTSTYLE EVEN spreads rows round-robin across every compute node slice, guaranteeing uniform row counts regardless of column values. This directly satisfies the stem's concern by preventing data skew, which would otherwise concentrate rows on some slices and force other nodes to idle during scans and joins.
- ✗
It reduces data movement during queries by co-locating data based on user_id.
Why it's wrong here
DISTSTYLE EVEN distributes rows round-robin across slices regardless of any column, so it cannot co-locate matching user_id values; that is DISTKEY's role. It is tempting because reduced data movement is the goal of distribution keys, and DISTKEY on user_id would be correct for frequent joins on that column.
- ✗
It improves join performance when joining on user_id.
Why it's wrong here
EVEN assigns rows round-robin, so matching user_id values land on different slices and joins require redistribution or broadcast across the network. It is tempting because join performance is the usual reason for choosing a distribution style, and DISTKEY on user_id would be correct when that column is joined frequently.
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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.