Question 37 - ARA-C01 discussion

A multi-cluster warehouse is a virtual warehouse that can scale compute resources by adding or removing clusters based on the workload demand. A multi-cluster warehouse can improve the performance of a particular workload by reducing the query queue time and the data spillage to local storage. To identify the specific days and virtual warehouses that would benefit from a multi-cluster warehouse, you need to analyze the query history and look for the following indicators:

High average queued load: This metric shows the average number of queries waiting in the queue for each warehouse cluster. A high value indicates that the warehouse is overloaded and cannot handle the concurrency demand.

High bytes spilled to local storage: This metric shows the amount of data that was spilled from memory to local disk during query processing. A high value indicates that the warehouse size is too small and cannot fit the data in memory.

High variation in workload: This metric shows the fluctuation in the number of queries submitted to the warehouse over time. A high variation indicates that the workload is unpredictable and dynamic, and requires a flexible scaling policy.

The query in option C is the best one to identify these indicators, as it selects the date, warehouse name, bytes spilled to local storage, and sum of average queued load from the query history table, and filters the results where bytes spilled to local storage is greater than zero. This query will show the days and warehouses that experienced data spillage and high queue time, and could benefit from a multi-cluster warehouse with auto-scale mode.

The query in option A is not correct, as it only selects the date and warehouse name, and does not include any metrics to measure the performance of the workload. The query in option B is not correct, as it selects the date, warehouse name, and average execution time, which is not a good indicator of the need for a multi-cluster warehouse. The query in option D is not correct, as it selects the date, warehouse name, and average credits used, which is not a good indicator of the need for a multi-cluster warehouse either.