Answer: Increase the warehouse MAX_CLUSTER_COUNT parameter.

The question describes a scenario where multiple users on the same virtual warehouse are experiencing slow query execution and query queuing, indicating concurrency issues. Option D (Increase the warehouse MAX_CLUSTER_COUNT parameter) is the correct answer because it enables multi-cluster warehousing, allowing Snowflake to automatically scale out by adding more clusters to handle increased concurrent workloads. This directly addresses both the slow performance and queuing issues by distributing the load across multiple compute clusters. Option A (Reduce STATEMENT_QUEUED_TIMEOUT_IN_SECONDS) would only cancel queued queries sooner rather than improving performance. Option B (Reduce AUTO_SUSPEND) affects warehouse suspension timing but doesn't address concurrency. Option C (Increase MAX_CONCURRENCY_LIMIT) is incorrect as this parameter doesn't exist in Snowflake; the relevant parameter is MAX_CONCURRENCY_LEVEL, but even that controls queuing behavior rather than scaling compute resources. The community discussion strongly supports D with 70% consensus and upvoted comments explaining that scale-out via multi-cluster is the proper solution for concurrency issues.

Author: LeetQuiz Editorial Team