Where can I find Snowflake’s data‑skipping feature, and how is it related to partitioning and moving to reduce the number of partitions?

Data‑skipping is part of Snowflake’s query optimization engine and is visible in the query profile. After a query runs, you can open the Snowflake UI, go to Query History, and view the Query Profile. In the profile, the “Pruned Micro‑Partitions” section shows how many partitions were skipped. The feature relies on the table’s clustering metadata; if you define clustering keys, Snowflake automatically maintains min/max values for each key in every micro‑partition. When you run a query with predicates on those keys, the optimizer uses that metadata to skip irrelevant partitions. You can also view clustering information via the SHOW TABLES or SHOW CLUSTERING INFORMATION commands. Moving data—such as using the RECLUSTER command—helps keep the clustering metadata tight, further improving data‑skipping efficiency. Thus, data‑skipping is tightly coupled with partitioning and clustering; proper partitioning and regular reclustering reduce the number of partitions that need to be scanned.