A company is building a dashboard for thousands of Analysts. The dashboard presents the results of a few summary queries on tables that are regularly updated. The query conditions vary by topic according to what data each Analyst needs. Responsiveness of the dashboard queries is a top priority, and the data cache should be preserved.
How should the Data Engineer configure the compute resources to support this dashboard?
To ensure the responsiveness of the dashboard queries, especially given the high number of concurrent users and the varying query conditions, a multi-cluster virtual warehouse set to maximized mode is the most suitable configuration. This setup allows for maximum compute resources to be available at all times, ensuring that queries are processed quickly without waiting for additional clusters to start. Monitoring to determine the smallest suitable number of clusters helps in optimizing resource utilization while maintaining the necessary performance.
This mode is enabled by specifying the same value for both maximum and minimum number of clusters (note that the specified value must be larger than 1). In this mode, when the warehouse is started, Snowflake starts all the clusters so that maximum resources are available while the warehouse is running. This mode is effective for statically controlling the available compute resources, particularly if you have large numbers of concurrent user sessions and/or queries and the numbers do not fluctuate significantly. The key term here is : "The top priority is the responsiveness". A is also valid but it will have impact on the responsiveness due to economy option. The queries will queue up before scale-up happens.