[GitHub] [arrow-datafusion] Jimexist commented on a change in pull request #631: implement rank and dense_rank function and refactor built-in window function evaluation

[GitBox <gi...@apache.org>]

Jimexist commented on a change in pull request #631:
URL: https://github.com/apache/arrow-datafusion/pull/631#discussion_r659313911



##########
File path: datafusion/src/physical_plan/window_functions.rs
##########
@@ -208,11 +210,57 @@ pub(super) fn signature_for_built_in(fun: &BuiltInWindowFunction) -> Signature {
     }
 }
 
+/// Partition evaluator
+pub(crate) trait PartitionEvaluator {
+    /// Whether the evaluator should be evaluated with rank
+    fn include_rank(&self) -> bool {
+        false
+    }
+
+    /// evaluate the partition evaluator against the partitions
+    fn evaluate(&self, partition_points: Vec<Range<usize>>) -> Result<Vec<ArrayRef>> {
+        partition_points
+            .into_iter()
+            .map(|partition| self.evaluate_partition(partition))
+            .collect()
+    }
+
+    /// evaluate the partition evaluator against the partitions with rank information
+    fn evaluate_with_rank(
+        &self,
+        partition_points: Vec<Range<usize>>,
+        sort_partition_points: Vec<Range<usize>>,
+    ) -> Result<Vec<ArrayRef>> {
+        partition_points
+            .into_iter()
+            .map(|partition| {
+                let ranks_in_partition =
+                    find_ranges_in_range(&partition, &sort_partition_points);
+                self.evaluate_partition_with_rank(partition, ranks_in_partition)
+            })
+            .collect()
+    }
+
+    /// evaluate the partition evaluator against the partition
+    fn evaluate_partition(&self, _partition: Range<usize>) -> Result<ArrayRef>;

Review comment:
       Actually I was trying to avoid generation sort partition points because a majority of the functions do not need that. Nth value not needing them, row number not needing values at all - just length info




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