Convert approx_median to UDAF

datafusion/core/tests/dataframe/dataframe_functions.rs

@@ -33,6 +33,7 @@ use datafusion::assert_batches_eq;
 use datafusion_common::{DFSchema, ScalarValue};
 use datafusion_expr::expr::Alias;
 use datafusion_expr::ExprSchemable;
+use datafusion_functions_aggregate::expr_fn::approx_median;
 
 fn test_schema() -> SchemaRef {
     Arc::new(Schema::new(vec![
@@ -342,7 +343,7 @@ async fn test_fn_approx_median() -> Result<()> {
 
     let expected = [
         "+-----------------------+",
-        "| APPROX_MEDIAN(test.b) |",
+        "| approx_median(test.b) |",
         "+-----------------------+",
         "| 10                    |",
         "+-----------------------+",

datafusion/expr/src/aggregate_function.rs

@@ -71,8 +71,6 @@ pub enum AggregateFunction {
     ApproxPercentileCont,
     /// Approximate continuous percentile function with weight
     ApproxPercentileContWithWeight,
-    /// ApproxMedian
-    ApproxMedian,
     /// Grouping
     Grouping,
     /// Bit And
@@ -112,7 +110,6 @@ impl AggregateFunction {
             RegrSXY => "REGR_SXY",
             ApproxPercentileCont => "APPROX_PERCENTILE_CONT",
             ApproxPercentileContWithWeight => "APPROX_PERCENTILE_CONT_WITH_WEIGHT",
-            ApproxMedian => "APPROX_MEDIAN",
             Grouping => "GROUPING",
             BitAnd => "BIT_AND",
             BitOr => "BIT_OR",
@@ -161,7 +158,6 @@ impl FromStr for AggregateFunction {
             "regr_sxy" => AggregateFunction::RegrSXY,
             // approximate
             "approx_distinct" => AggregateFunction::ApproxDistinct,
-            "approx_median" => AggregateFunction::ApproxMedian,
             "approx_percentile_cont" => AggregateFunction::ApproxPercentileCont,
             "approx_percentile_cont_with_weight" => {
                 AggregateFunction::ApproxPercentileContWithWeight
@@ -234,7 +230,6 @@ impl AggregateFunction {
             AggregateFunction::ApproxPercentileContWithWeight => {
                 Ok(coerced_data_types[0].clone())
             }
-            AggregateFunction::ApproxMedian => Ok(coerced_data_types[0].clone()),
             AggregateFunction::Grouping => Ok(DataType::Int32),
             AggregateFunction::NthValue => Ok(coerced_data_types[0].clone()),
             AggregateFunction::StringAgg => Ok(DataType::LargeUtf8),
@@ -284,7 +279,8 @@ impl AggregateFunction {
             AggregateFunction::BoolAnd | AggregateFunction::BoolOr => {
                 Signature::uniform(1, vec![DataType::Boolean], Volatility::Immutable)
             }
-            AggregateFunction::Avg | AggregateFunction::ApproxMedian => {
+
+            AggregateFunction::Avg => {
                 Signature::uniform(1, NUMERICS.to_vec(), Volatility::Immutable)
             }
             AggregateFunction::NthValue => Signature::any(2, Volatility::Immutable),

datafusion/expr/src/expr_fn.rs

@@ -284,18 +284,6 @@ pub fn approx_distinct(expr: Expr) -> Expr {
     ))
 }
 
-/// Calculate an approximation of the median for `expr`.
-pub fn approx_median(expr: Expr) -> Expr {
-    Expr::AggregateFunction(AggregateFunction::new(
-        aggregate_function::AggregateFunction::ApproxMedian,
-        vec![expr],
-        false,
-        None,
-        None,
-        None,
-    ))
-}
-
 /// Calculate an approximation of the specified `percentile` for `expr`.
 pub fn approx_percentile_cont(expr: Expr, percentile: Expr) -> Expr {
     Expr::AggregateFunction(AggregateFunction::new(

datafusion/expr/src/type_coercion/aggregates.rs

@@ -231,16 +231,6 @@ pub fn coerce_types(
             }
             Ok(input_types.to_vec())
         }
-        AggregateFunction::ApproxMedian => {
-            if !is_approx_percentile_cont_supported_arg_type(&input_types[0]) {
-                return plan_err!(
-                    "The function {:?} does not support inputs of type {:?}.",
-                    agg_fun,
-                    input_types[0]
-                );
-            }
-            Ok(input_types.to_vec())
-        }
         AggregateFunction::NthValue => Ok(input_types.to_vec()),
         AggregateFunction::Grouping => Ok(vec![input_types[0].clone()]),
         AggregateFunction::StringAgg => {

datafusion/functions-aggregate/src/approx_median.rs

@@ -0,0 +1,129 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Defines physical expressions for APPROX_MEDIAN that can be evaluated MEDIAN at runtime during query execution
+
+use std::any::Any;
+use std::fmt::Debug;
+
+use arrow::{datatypes::DataType, datatypes::Field};
+use arrow_schema::DataType::{Float64, UInt64};
+
+use datafusion_common::{not_impl_err, plan_err, Result};
+use datafusion_expr::function::{AccumulatorArgs, StateFieldsArgs};
+use datafusion_expr::type_coercion::aggregates::NUMERICS;
+use datafusion_expr::utils::format_state_name;
+use datafusion_expr::{Accumulator, AggregateUDFImpl, Signature, Volatility};
+use datafusion_physical_expr_common::aggregate::utils::down_cast_any_ref;
+
+use crate::approx_percentile_cont::ApproxPercentileAccumulator;
+
+make_udaf_expr_and_func!(
+    ApproxMedian,
+    approx_median,
+    expression,
+    "Computes the approximate median of a set of numbers",
+    approx_median_udaf
+);
+
+/// APPROX_MEDIAN aggregate expression
+pub struct ApproxMedian {
+    signature: Signature,
+}
+
+impl Debug for ApproxMedian {
+    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
+        f.debug_struct("ApproxMedian")
+            .field("name", &self.name())
+            .field("signature", &self.signature)
+            .finish()
+    }
+}
+
+impl Default for ApproxMedian {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl ApproxMedian {
+    /// Create a new APPROX_MEDIAN aggregate function
+    pub fn new() -> Self {
+        Self {
+            signature: Signature::uniform(1, NUMERICS.to_vec(), Volatility::Immutable),
+        }
+    }
+}
+
+impl AggregateUDFImpl for ApproxMedian {
+    /// Return a reference to Any that can be used for downcasting
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn state_fields(&self, args: StateFieldsArgs) -> Result<Vec<Field>> {
+        Ok(vec![
+            Field::new(format_state_name(args.name, "max_size"), UInt64, false),
+            Field::new(format_state_name(args.name, "sum"), Float64, false),
+            Field::new(format_state_name(args.name, "count"), Float64, false),
+            Field::new(format_state_name(args.name, "max"), Float64, false),
+            Field::new(format_state_name(args.name, "min"), Float64, false),
+            Field::new_list(
+                format_state_name(args.name, "centroids"),
+                Field::new("item", Float64, true),
+                false,
+            ),
+        ])
+    }
+
+    fn name(&self) -> &str {
+        "approx_median"
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
+        if !arg_types[0].is_numeric() {
+            return plan_err!("ApproxMedian requires numeric input types");
+        }
+        Ok(arg_types[0].clone())
+    }
+
+    fn accumulator(&self, acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
+        if acc_args.is_distinct {
+            return not_impl_err!(
+                "APPROX_MEDIAN(DISTINCT) aggregations are not available"
+            );
+        }
+
+        Ok(Box::new(ApproxPercentileAccumulator::new(
+            0.5_f64,
+            acc_args.input_type.clone(),
+        )))
+    }
+}
+
+impl PartialEq<dyn Any> for ApproxMedian {
+    fn eq(&self, other: &dyn Any) -> bool {
+        down_cast_any_ref(other)
+            .downcast_ref::<Self>()
+            .map(|x| self.signature == x.signature)
+            .unwrap_or(false)
+    }
+}