Jimexist commented on a change in pull request #631:
URL: https://github.com/apache/arrow-datafusion/pull/631#discussion_r659313911
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File path: datafusion/src/physical_plan/window_functions.rs
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@@ -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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