DEA-C01 Question 300
Select 2A company is using an Amazon Redshift cluster to store analytics data and has recently observed a significant slowdown in query performance. Upon investigation, they find that the queries are not utilizing the SORT keys effectively. As a Data Engineer, what steps should you take to improve the query performance?
- A
Redefine the SORT keys on frequently queried columns and reload the data.
- B
Enable Amazon Redshift concurrency scaling to handle the increased workload.
- C
Vacuum and analyze the Redshift tables to optimize database performance.
- D
Use distribution keys to distribute data evenly across nodes.
- E
Migrate to Amazon RDS for better query performance.
Show answer and explanation
Correct answers: A, C
Explanation
To improve query performance in Amazon Redshift, it is critical to ensure that the SORT keys are correctly defined and utilized. If the existing SORT keys are not effective, redefining them and reloading the data can optimize the query execution plan. Additionally, performing VACUUM and ANALYZE operations ensures that the database statistics are updated, and deleted rows are removed, further enhancing query performance.
- A. Correct.
Redefining the SORT keys on frequently queried columns can significantly improve query performance, as it optimizes the storage and retrieval of data. However, this requires reloading the data into the table.
- B. Incorrect.
Enabling concurrency scaling is useful for handling increased query workloads but does not address the issue of SORT key utilization or query optimization.
- C. Correct.
Vacuuming and analyzing the Redshift tables help remove deleted rows and update statistics, which ensures queries take advantage of the SORT keys and other optimizations.
- D. Incorrect.
Using distribution keys can help distribute data evenly across nodes, but it is unrelated to the specific issue of improving SORT key utilization.
- E. Incorrect.
Migrating to Amazon RDS is not a practical solution for this problem, as Redshift is specifically designed for analytics workloads and query optimization.