Question

A data engineering team runs a nightly transformation job consisting of a single very large, complex analytical query that joins several billion-row tables. The query currently spills to remote storage and takes hours to complete on an X-Small warehouse. During the day, the same warehouse serves a fluctuating number of concurrent BI dashboard queries, and users report queuing during peak hours. The team wants to address BOTH problems with the correct warehouse configuration strategy. What should they do?

Accepted Answer

Scale up the warehouse to a larger size for the nightly job, and configure a multi-cluster warehouse (scale out) to handle the daytime concurrent dashboard queries.

Answer

Configure a multi-cluster warehouse for both workloads, since adding clusters increases the memory and compute available to any individual query.

Answer

Scale up to a larger warehouse size for both workloads, because a larger size automatically resolves query queuing during high concurrency.

Answer

Keep the X-Small warehouse but lower the auto-suspend value so the warehouse restarts frequently and clears the query queue.