Snowflake SnowPro Certification Practice Test

What does Warehouse Caching improve during querying?

1. Network speed

2. Data loading times

3. Compute performance

4. User interface responsiveness

The correct answer is: Compute performance

Warehouse Caching in Snowflake significantly enhances compute performance during querying. When a query is executed, Snowflake makes use of caching to store intermediate results and metadata about the data structures. This means that if identical or similar queries are run afterwards, Snowflake can retrieve these results from the cache rather than re-executing the entire query from scratch. The benefit of this mechanism is a reduction in both execution time and resource utilization, effectively optimizing the overall compute performance. It allows users to retrieve results more quickly, thus improving efficiency and reducing costs associated with compute resources. By leveraging cached data, Snowflake minimizes the need for redundant computation, ensuring that repeated queries run much faster. On the other hand, the other options do not accurately reflect the primary function of Warehouse Caching. While caching might indirectly affect some aspects of performance related to network speed or data loading due to reduced compute resource demand, those are not direct improvements attributed to caching itself. User interface responsiveness may improve due to faster query turnaround times, but again, this is a secondary effect and not the main purpose of caching. Therefore, the primary advantage of Warehouse Caching lies in enhanced compute performance during querying.