aditanase commented on code in PR #20019:
URL: https://github.com/apache/datafusion/pull/20019#discussion_r2745135185
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datafusion/physical-plan/src/aggregates/mod.rs:
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@@ -144,6 +144,23 @@ pub enum AggregateMode {
/// This mode requires that the input has more than one partition, and is
/// partitioned by group key (like FinalPartitioned).
SinglePartitioned,
+ /// Combine multiple partial aggregations to produce a new partial
+ /// aggregation.
+ ///
+ /// Input is intermediate accumulator state (like Final), but output is
+ /// also intermediate accumulator state (like Partial). This enables
+ /// tree-reduce aggregation strategies where partial results from
+ /// multiple workers are combined in multiple stages before a final
+ /// evaluation.
+ ///
+ /// ```text
+ /// Final
+ /// / \
+ /// PartialReduce PartialReduce
+ /// / \ / \
+ /// Partial Partial Partial Partial
+ /// ```
+ PartialReduce,
Review Comment:
@gabotechs @njsmith the benefits are real in aggregations where the
cardinality of the aggregation key is large. That is why all the Aggregation
frameworks that I am aware of (spark, hadoop, algebird etc) have a separate
Combiner itermediate type/function for merging partial aggregates.
Both hadoop and spark do this by default and it's called map side combine.
Big +1 for the work on this PR!
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