DEA-C01 Question 143
Select 3You are working as a data engineer for an e-commerce company that stores its transactional data in Amazon Redshift. You notice that a SQL query processing sales data is taking too long to execute. The query includes multiple JOINs, uses SELECT *, and filters data using a WHERE clause. What are the best practices you should follow to optimize the query performance?
- A
Replace SELECT * with specific column names.
- B
Use DISTKEY and SORTKEY to optimize table design for the JOINs.
- C
Avoid using the WHERE clause to minimize filtering.
- D
Analyze the query plan using EXPLAIN to identify bottlenecks.
- E
Convert JOINs into nested subqueries for faster processing.
Show answer and explanation
Correct answers: A, B, D
Explanation
To optimize SQL query performance in Amazon Redshift, you should follow best practices such as replacing SELECT * with specific column names to fetch only the necessary data, leveraging DISTKEY and SORTKEY to optimize table design for JOIN operations, and using the EXPLAIN command to identify and resolve bottlenecks. Avoiding WHERE clauses or converting JOINs into nested subqueries can hinder performance rather than improve it.
- A. Correct.
Replacing SELECT * with specific column names reduces the amount of unnecessary data fetched, improving query performance.
- B. Correct.
DISTKEY and SORTKEY optimize data distribution and sorting in Amazon Redshift, which can significantly improve performance for JOIN operations.
- C. Incorrect.
Avoiding the WHERE clause is not a best practice. Filtering data using WHERE can reduce the amount of data processed and improve performance.
- D. Correct.
Using the EXPLAIN command helps analyze the query execution plan and identify potential bottlenecks or inefficiencies.
- E. Incorrect.
Converting JOINs into nested subqueries is typically not a recommended practice in Amazon Redshift, as JOINs are optimized for large-scale data processing.