Which property helps enable effective pruning on the table?

• A. Large enough number of distinct values to enable effective pruning on the table
• B. Small enough number of distinct values to allow Snowflake to effectively group rows in the same micro-partition
• C. Zero distinct values
• D. High cardinality unrelated to pruning

Answer: (A)

Snowflake pruning relies on the metadata Snowflake stores for each micro-partition, especially the minimum and maximum values for each column. When a query filters on a column, Snowflake can skip entire micro-partitions whose min/max range doesn’t satisfy the predicate, reading only the partitions that potentially contain the matching rows.

Having a large number of distinct values makes this pruning more effective. With high cardinality, data is spread across more micro-partitions, so the min/max ranges are more likely to exclude partitions that don’t contain the targeted value. In other words, the predicate becomes selective enough that many partitions can be ruled out without scanning their contents, reducing IO and speeding up the query.

If the column has only a few distinct values, many micro-partitions may end up with ranges that include the predicate, which reduces pruning efficiency and can force more data to be read. A column with zero distinct values (constant across the table) either provides no selective benefit for arbitrary predicates or results in a trivial scenario where pruning isn’t helpful beyond the simplest case. Hence higher cardinality directly supports more effective pruning.