Dynamic partition pruning: Optimizer uses runtime filter values to skip partitions. E.g., JOIN fact table with dimension filtered by date; the date filter is pushed to the fact scan, so only matching partitions are read. In Spark: Enabled by default with AQE; broadcast-small-dimension pattern. Effect: Fewer I/O, faster scans. Example: fact partitioned by date; query filters dim by region and joins—Spark can prune fact partitions if correlation allows....
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