How does Snowflake utilize clustering information to improve query performance?

Snowflake utilizes clustering information to enhance query performance by pruning unnecessary micro-partitions.

Clustering Metadata: Snowflake stores clustering information for each micro-partition, which includes data range and distribution.

Pruning Micro-partitions: When a query is executed, Snowflake uses this clustering metadata to identify and eliminate micro-partitions that do not match the query criteria, thereby reducing the amount of data scanned and improving query performance.

Snowflake Documentation on Clustering

Snowflake Documentation on Micro-partition Pruning