Clustering Depth
The clustering depth for a populated table measures the average depth (1 or greater) of the overlapping micro-partitions for specified columns in a table. The smaller the average depth, the better clustered the table is with regards to the specified columns.
Clustering depth can be used for a variety of purposes, including:
Monitoring the clustering “health” of a large table, particularly over time as DML is performed on the table.
Determining whether a large table would benefit from explicitly defining a clustering key.
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