Which function is used to understand the clustering depth of a table?

• A. System Clustering Ratio
• B. System Clustering Depth
• C. System Clustering Information
• D. System Clustering Quality

Answer: (B)

Understanding how data is laid out with clustering keys is important because Snowflake’s pruning works best when data is well aligned with those keys. The clustering depth metric tells you how far the actual data distribution is from ideal clustering. The function that reports this exact metric is System Clustering Depth; it returns a numeric depth for a given table, giving a direct read on how well the table is clustered. A lower depth means data is closer to being well-clustered, which supports better pruning and faster queries; a higher depth suggests that reclustering could yield performance benefits. If you need more detailed clues about clustering status and recommendations, you can use a function that returns broader clustering information, but for the specific depth value, System Clustering Depth is the right tool. For example: SELECT SYSTEM$CLUSTERING_DEPTH('MY_DB.MY_SCHEMA.MY_TABLE');