The correct answer is B. Add more clusters to the warehouse .
Queued queries on a multi-cluster warehouse usually indicate a concurrency problem. Multiple analysts are submitting queries at the same time, and the warehouse does not have enough active cluster capacity to process them concurrently.
Why B is correct:
Adding more clusters to a multi-cluster warehouse increases concurrency capacity. In Auto-scale mode, Snowflake can start additional clusters as needed, up to the configured maximum, to reduce queuing.
Why the other options are incorrect:
A. Scheduling or limiting reports may reduce concurrency, but it adds operational overhead and does not use Snowflake’s built-in multi-cluster scaling capability.
C. Increasing warehouse size can make individual queries faster, but it does not directly improve concurrency as effectively as adding clusters.
D. A Snowpark-optimized warehouse is intended for memory-intensive Snowpark workloads, not for reducing query queues from many concurrent BI/ad hoc users.
Official Snowflake documentation reference:
Snowflake documentation explains that multi-cluster warehouses are designed to handle concurrency by automatically scaling out with additional clusters.
[Reference: Snowflake Documentation — Multi-cluster warehouses; Warehouse load monitoring; SnowPro Core Study Guide — Snowflake Account and Resource Management., , , ]
