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When sizing a Snowflake warehouse, which factor is irrelevant?

  1. Number of concurrent queries

  2. Data size and composition

  3. Number of users

  4. Number of tables being queried

The correct answer is: Number of users

When considering how to size a Snowflake warehouse, the number of users is typically irrelevant. This is because Snowflake's architecture is designed to efficiently handle multiple users and concurrent workloads without being directly limited by the number of users. Instead, the performance of the warehouse is more affected by the nature of the queries being executed, the concurrent queries that are run simultaneously, and the size and composition of the underlying data. The number of concurrent queries is important because it directly influences the required compute resources. A higher number of concurrent queries may necessitate a more powerful or larger warehouse to ensure performance does not degrade. Data size and composition are also critical factors for sizing, as they determine how much data the warehouse needs to process and the complexity involved in query execution. The number of tables being queried can impact performance as well. More tables can lead to more complex joins and additional resource demands, which can affect the overall execution time and resource needs of queries. Thus, while the actual number of users can be significant for understanding usage patterns, it does not directly dictate the sizing of the warehouse in the same way that the other options do.