What do 'cluster max' and 'cluster min' mean in Snowflake?

In Snowflake, clustering depth is a metric that indicates how well the data in a table is physically ordered according to its clustering keys. The clustering depth is expressed as a range of values, with the maximum depth (cluster max) representing the deepest level of clustering across all partitions, and the minimum depth (cluster min) representing the shallowest level. These metrics help you gauge the effectiveness of your clustering strategy. A high cluster max relative to cluster min indicates uneven clustering, which can lead to inefficient scans. Snowflake automatically tracks these values and can trigger a reclustering operation when the difference exceeds a threshold you set. By monitoring cluster max and cluster min, you can decide when to run a manual recluster or adjust your clustering keys to improve query performance. The values are available via the TABLES or CLUSTERING_INFORMATION views and can be visualized in the Snowflake UI.