Which of the following are stored in micro-partitions to support optimization and query processing?

• A. The range of values for each column.
• B. The number of distinct values.
• C. Additional properties used for optimization.
• D. All of the above.

Answer: (D)

The key idea is that micro-partitions carry metadata that helps prune data and speed up query processing. Snowflake uses zone maps, which record the minimum and maximum value seen in each column within a micro-partition. This allows the engine to skip partitions that cannot satisfy a filter, speeding up scans.

In addition to range information, micro-partitions maintain column statistics like how many distinct values exist and other properties that aid the optimizer in estimating selectivity and planning the execution path. Null counts and distribution-related details can also be part of this metadata, further informing pruning and join strategies.

Because micro-partitions store range information for each column, distinct-value counts, and other optimization-related properties, all of these aspects are stored to support optimization and query processing.