{"id":433,"date":"2024-06-28T11:36:57","date_gmt":"2024-06-28T11:36:57","guid":{"rendered":"https:\/\/datadandies.nl\/?p=433"},"modified":"2024-06-28T11:36:57","modified_gmt":"2024-06-28T11:36:57","slug":"clustering-depth-of-tables-in-snowflake-a-potential-indicator-of-clustering-health-of-a-table","status":"publish","type":"post","link":"https:\/\/datadandies.nl\/index.php\/2024\/06\/28\/clustering-depth-of-tables-in-snowflake-a-potential-indicator-of-clustering-health-of-a-table\/","title":{"rendered":"Clustering depth of tables in Snowflake: a potential indicator of clustering health of a table"},"content":{"rendered":"\n
Clustering depth indicates if micro-partitions are overlapping with one another. Ideally, micro-partitions are not overlapping and are contiguous. Being contiguous means that one micro-partition seamlessly connects with another micro-partition.<\/p>\n\n\n\n
Sometimes however, micro-partitions are overlapping. A reason for this could be a less than optimal clustering key. Whatever the reason, this is not ideal, because now you run the risk of unnecessarily scanning the same data twice when scanning two micro-partitions. A possible solution for a high clustering depth is choosing a clustering key that is better suited for the job.<\/p>\n\n\n\n
Below are some numbers to give you an idea of how clustering depth is defined in Snowflake.<\/p>\n\n\n\n
When you have a table with no micro-partitions (a table with no data), the clustering depth is 0.<\/p>\n\n\n\n
When you have a table that contains data and the micro-partitions are not overlapping and contiguous, the clustering depth is 1.<\/p>\n\n\n\n
You can find out the clustering depth of a table by using the system function below.<\/p>\n\n\n\n