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How does Snowflake utilize clustering information to improve query performance?
Correct Answer: A
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