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Review mode set 2 – question 23
updated 4 months, 4 weeks ago
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A large e-commerce company has an Amazon Redshift data warehouse <snip> However, there is a particular long-running query that runs for more than two hours every hour, causing other short-running queries to get queued up or take a longer time to execute.
Which of the following would be the MOST cost-effective solution to optimize query execution?
The answer is to use WLM. Why is spinning up an additional cluster CHEAPER than using SQA?
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Hello johnsher,
That’s a great question. While Short Query Acceleration (SQA) does improve responsiveness for short queries, it doesn’t actually solve the core issue in your scenario: the long-running query still takes over two hours and continues consuming cluster resources, which means other queries can still be affected when demand is high. SQA simply prioritizes short queries but doesn’t remove the underlying workload contention.
By contrast, Concurrency Scaling with a dedicated WLM queue isolates the heavy query and automatically adds extra cluster capacity only when it’s needed. Accordingly, you receive one free hour of Concurrency Scaling usage per day per cluster, and beyond that you’re charged per-second while the additional cluster is active. This model is often more cost-effective than permanently resizing the cluster, since you only pay for the bursts, and it ensures both long and short queries run without blocking each other.
If you have further questions or need additional clarification, please don’t hesitate to contact us.
Best,
Irene @ Tutorials Dojo
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