DEA-C01 Question 366
Select 2You are a data engineer working for a company that uses Amazon Redshift as its primary data warehouse. Your team has noticed performance issues with certain queries that involve large dataset joins and aggregations. Which of the following actions should you take to optimize query performance in Amazon Redshift? (Select TWO.)
- A
Use appropriate distribution keys to evenly distribute data across nodes.
- B
Disable automatic table maintenance to reduce overhead.
- C
Compress data while loading it into Redshift using columnar encoding.
- D
Sort data using sort keys that align with the query patterns.
- E
Increase the size of the Redshift cluster without analyzing existing workload patterns.
Show answer and explanation
Correct answers: A, D
Explanation
Performance tuning in Amazon Redshift involves strategies that directly reduce query execution time and optimize resource usage. Using appropriate distribution keys minimizes data movement during joins, while sort keys ensure efficient data retrieval for queries. These actions specifically address the performance issues described in the scenario, unlike options such as disabling table maintenance or increasing cluster size without analysis.
- A. Correct.
Using appropriate distribution keys ensures that data is evenly distributed across nodes, reducing data movement during joins and improving query performance.
- B. Incorrect.
Disabling automatic table maintenance is not recommended as it helps optimize table storage and performance over time.
- C. Incorrect.
While columnar encoding reduces storage size and improves I/O efficiency, it does not directly address query performance issues related to joins and aggregations.
- D. Correct.
Sort keys help organize data in a way that aligns with query patterns, reducing the need for scanning irrelevant data and improving query performance.
- E. Incorrect.
Simply increasing the size of the cluster without understanding the workload patterns may not effectively address performance issues and could lead to unnecessary costs.