Snowflake Certification Practice Test

What is the method used to reduce the number of micro-partitions scanned by a query in Snowflake?

1. Governor

2. Regulator

3. Pruning

4. Filtering

The correct answer is: Pruning

The method used to reduce the number of micro-partitions scanned by a query in Snowflake is known as pruning. This technique is a fundamental feature of Snowflake's architecture that optimizes query performance by eliminating the need to scan unnecessary data. When a query is executed, Snowflake checks the metadata of the micro-partitions that contain the relevant data. Each micro-partition holds not just the actual data but also detailed statistics, including the range of values stored for each column. If the query predicates fall outside these ranges, Snowflake can skip scanning those micro-partitions entirely, thereby streamlining the process and improving performance. This capability of pruning is particularly valuable in large datasets, where scanning every piece of data would be inefficient and time-consuming. By minimizing the amount of data processed, pruning contributes to faster query execution and reduced compute costs, which are significant advantages of using Snowflake for data analysis and reporting. Other methods like filtering involve applying conditions to the dataset post-scan, which does not offer the same level of efficiency since it still requires accessing the unfiltered data before applying any constraints.