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Answer: Experiment by running the same queries against warehouses of different sizes
Snowflake recommends experimenting with different warehouse sizes by running the same queries against warehouses of different sizes (Option B) to determine the optimal size based on performance requirements and cost considerations. This empirical approach allows users to balance query performance with cost efficiency. Option A is incorrect because starting with X-Small and scaling up after 2 minutes is not a recommended practice; it may lead to inefficient resource usage. Option C is incorrect because while Snowflake provides default sizes, they may not be optimal for specific workloads. Option D is incorrect because warehouse size selection should not be based solely on table size (1 GB); it depends on query complexity, concurrency, and performance needs.
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What approach does Snowflake recommend for identifying the appropriate virtual warehouse size to choose?
A
Always start with an X-Small and increase the size if the query does not complete in 2 minutes
B
Experiment by running the same queries against warehouses of different sizes
C
Use the default size Snowflake chooses
D
Use X-Large or above for tables larger than 1 GB