Improve performance of constant aggregate window expression

datafusion/physical-expr/src/window/aggregate.rs

@@ -34,7 +34,7 @@ use arrow::array::ArrayRef;
 use arrow::datatypes::FieldRef;
 use arrow::record_batch::RecordBatch;
 use datafusion_common::{DataFusionError, Result, ScalarValue};
-use datafusion_expr::{Accumulator, WindowFrame};
+use datafusion_expr::{Accumulator, WindowFrame, WindowFrameBound, WindowFrameUnits};
 use datafusion_physical_expr_common::sort_expr::LexOrdering;
 
 /// A window expr that takes the form of an aggregate function.
@@ -46,6 +46,7 @@ pub struct PlainAggregateWindowExpr {
     partition_by: Vec<Arc<dyn PhysicalExpr>>,
     order_by: LexOrdering,
     window_frame: Arc<WindowFrame>,
+    is_constant_in_partition: bool,
 }
 
 impl PlainAggregateWindowExpr {
@@ -56,11 +57,14 @@ impl PlainAggregateWindowExpr {
         order_by: &LexOrdering,
         window_frame: Arc<WindowFrame>,
     ) -> Self {
+        let is_constant_in_partition =
+            Self::is_window_constant_in_partition(order_by, &window_frame);
         Self {
             aggregate,
             partition_by: partition_by.to_vec(),
             order_by: order_by.clone(),
             window_frame,
+            is_constant_in_partition,
         }
     }
 
@@ -85,6 +89,30 @@ impl PlainAggregateWindowExpr {
             );
         }
     }
+
+    // Returns true if every row in the partition has the same window frame. This allows
+    // for preventing bound + function calculation for every row due to the values being the
+    // same.
+    //
+    // This occurs when both bounds fall under either condition below:
+    //  1. Bound is unbounded (`Preceding` or `Following`)
+    //  2. Bound is `CurrentRow` while using `Range` units with no order by clause
+    //  This results in an invalid range specification. Following PostgreSQL’s convention,
+    //  we interpret this as the entire partition being used for the current window frame.
+    fn is_window_constant_in_partition(
+        order_by: &LexOrdering,
+        window_frame: &WindowFrame,
+    ) -> bool {
+        let is_constant_bound = |bound: &WindowFrameBound| match bound {
+            WindowFrameBound::CurrentRow => {
+                window_frame.units == WindowFrameUnits::Range && order_by.is_empty()
+            }
+            _ => bound.is_unbounded(),
+        };
+
+        is_constant_bound(&window_frame.start_bound)
+            && is_constant_bound(&window_frame.end_bound)
+    }
 }
 
 /// peer based evaluation based on the fact that batch is pre-sorted given the sort columns
@@ -213,4 +241,8 @@ impl AggregateWindowExpr for PlainAggregateWindowExpr {
             accumulator.evaluate()
         }
     }
+
+    fn is_constant_in_partition(&self) -> bool {
+        self.is_constant_in_partition
+    }
 }

datafusion/physical-expr/src/window/sliding_aggregate.rs

@@ -210,4 +210,8 @@ impl AggregateWindowExpr for SlidingAggregateWindowExpr {
             accumulator.evaluate()
         }
     }
+
+    fn is_constant_in_partition(&self) -> bool {
+        false
+    }
 }

datafusion/physical-expr/src/window/window_expr.rs

@@ -186,6 +186,10 @@ pub trait AggregateWindowExpr: WindowExpr {
         accumulator: &mut Box<dyn Accumulator>,
     ) -> Result<ScalarValue>;
 
+    /// Indicates whether this window function always produces the same result
+    /// for all rows in the partition.
+    fn is_constant_in_partition(&self) -> bool;
+
     /// Evaluates the window function against the batch.
     fn aggregate_evaluate(&self, batch: &RecordBatch) -> Result<ArrayRef> {
         let mut accumulator = self.get_accumulator()?;
@@ -272,8 +276,13 @@ pub trait AggregateWindowExpr: WindowExpr {
         not_end: bool,
     ) -> Result<ArrayRef> {
         let values = self.evaluate_args(record_batch)?;
-        let order_bys = get_orderby_values(self.order_by_columns(record_batch)?);
 
+        if self.is_constant_in_partition() {
+            accumulator.update_batch(&values)?;
+            let value = accumulator.evaluate()?;
+            return value.to_array_of_size(record_batch.num_rows());
+        }
+        let order_bys = get_orderby_values(self.order_by_columns(record_batch)?);
         let most_recent_row_order_bys = most_recent_row
             .map(|batch| self.order_by_columns(batch))
             .transpose()?