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What is a maximized Virtual Warehouse according to Snowflake terminology?

  1. Where the number of clusters is fixed

  2. Where the min and max amount of clusters are equal

  3. A warehouse that is always online

  4. Where scaling is automatic

The correct answer is: Where the min and max amount of clusters are equal

A maximized Virtual Warehouse in Snowflake terminology refers to a scenario where the minimum and maximum number of clusters are equal. This means that the warehouse operates at a fixed size and is consistently using a set number of clusters to handle workloads. When the minimum and maximum clusters are the same, it ensures that the Virtual Warehouse is running at its maximum capacity, providing optimal performance for queries without any need for scaling up or down during usage. This setup can be particularly beneficial for stable workloads where predictable performance is required, as it reduces the risk of performance degradation that might occur if additional clusters were added dynamically. In contrast, understanding why the other options don't fit the definition helps clarify the concept. For instance, a maximized Virtual Warehouse does not imply that the number of clusters is fixed in a way that they cannot be changed (the first option). It also does not necessarily mean that the warehouse is always online; rather, it’s about the fixed scaling setup regarding clusters. Lastly, while automatic scaling is an important feature of Snowflake that allows for handling varying workloads, it typically does not define a maximized warehouse—rather, it conforms to variable capacities based on demand. Thus, the correct interpretation aligns specifically with the fixed nature of the minimum and maximum clusters