merge main branch

Author: jatin

README.md

@@ -93,4 +93,6 @@ SELECT kurtosis(col) FROM VALUES (1.0), (10.0), (100.0), (10.0), (1.0) as tab(co
 - [x] `mode(expression) -> scalar` - Returns the most frequent (mode) value from a column of data.
 - [x] `max_by(expression1, expression2) -> scalar` - Returns the value of `expression1` associated with the maximum value of `expression2`.
 - [x] `min_by(expression1, expression2) -> scalar` - Returns the value of `expression1` associated with the minimum value of `expression2`.
+- [x] `kurtois_pop(expression) -> scalar` - Computes the excess kurtosis (Fisher’s definition) without bias correction.
+
 - [x] `kurtosis(expression) -> scalar` - Returns the kurtosis, a measure of the `tailedness` of the distribution, for the given numeric values in `expression`.

src/kurtosis_pop.rs

@@ -0,0 +1,188 @@
+// 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.
+
+// Copired from `datafusion/functions-aggregate/src/kurtosis_pop.rs`
+// Originally authored by goldmedal
+
+use arrow::array::{Array, ArrayRef, Float64Array, UInt64Array};
+use datafusion::arrow::datatypes::{DataType, Field};
+use datafusion::common::cast::as_float64_array;
+use datafusion::common::{downcast_value, DataFusionError, Result, ScalarValue};
+use datafusion::logical_expr::function::{AccumulatorArgs, StateFieldsArgs};
+use datafusion::logical_expr::{Accumulator, AggregateUDFImpl, Signature, Volatility};
+use std::any::Any;
+use std::fmt::Debug;
+
+make_udaf_expr_and_func!(
+    KurtosisPopFunction,
+    kurtosis_pop,
+    x,
+    "Calculates the excess kurtosis (Fisher’s definition) without bias correction.",
+    kurtosis_pop_udaf
+);
+
+pub struct KurtosisPopFunction {
+    signature: Signature,
+}
+
+impl Debug for KurtosisPopFunction {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        f.debug_struct("KurtosisPopFunction")
+            .field("signature", &self.signature)
+            .finish()
+    }
+}
+
+impl Default for KurtosisPopFunction {
+    fn default() -> Self {
+        Self::new()
+    }
+}
+
+impl KurtosisPopFunction {
+    pub fn new() -> Self {
+        Self {
+            signature: Signature::coercible(vec![DataType::Float64], Volatility::Immutable),
+        }
+    }
+}
+
+impl AggregateUDFImpl for KurtosisPopFunction {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn name(&self) -> &str {
+        "kurtosis_pop"
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
+        Ok(DataType::Float64)
+    }
+
+    fn state_fields(&self, _args: StateFieldsArgs) -> Result<Vec<Field>> {
+        Ok(vec![
+            Field::new("count", DataType::UInt64, true),
+            Field::new("sum", DataType::Float64, true),
+            Field::new("sum_sqr", DataType::Float64, true),
+            Field::new("sum_cub", DataType::Float64, true),
+            Field::new("sum_four", DataType::Float64, true),
+        ])
+    }
+
+    fn accumulator(&self, _acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
+        Ok(Box::new(KurtosisPopAccumulator::new()))
+    }
+}
+
+/// Accumulator for calculating the excess kurtosis (Fisher’s definition) without bias correction.
+/// This implementation follows the [DuckDB implementation]:
+/// <https://github.com/duckdb/duckdb/blob/main/src/core_functions/aggregate/distributive/kurtosis.cpp>
+#[derive(Debug, Default)]
+pub struct KurtosisPopAccumulator {
+    count: u64,
+    sum: f64,
+    sum_sqr: f64,
+    sum_cub: f64,
+    sum_four: f64,
+}
+
+impl KurtosisPopAccumulator {
+    pub fn new() -> Self {
+        Self {
+            count: 0,
+            sum: 0.0,
+            sum_sqr: 0.0,
+            sum_cub: 0.0,
+            sum_four: 0.0,
+        }
+    }
+}
+
+impl Accumulator for KurtosisPopAccumulator {
+    fn update_batch(&mut self, values: &[ArrayRef]) -> Result<()> {
+        let array = as_float64_array(&values[0])?;
+        for value in array.iter().flatten() {
+            self.count += 1;
+            self.sum += value;
+            self.sum_sqr += value.powi(2);
+            self.sum_cub += value.powi(3);
+            self.sum_four += value.powi(4);
+        }
+        Ok(())
+    }
+
+    fn merge_batch(&mut self, states: &[ArrayRef]) -> Result<()> {
+        let counts = downcast_value!(states[0], UInt64Array);
+        let sums = downcast_value!(states[1], Float64Array);
+        let sum_sqrs = downcast_value!(states[2], Float64Array);
+        let sum_cubs = downcast_value!(states[3], Float64Array);
+        let sum_fours = downcast_value!(states[4], Float64Array);
+
+        for i in 0..counts.len() {
+            let c = counts.value(i);
+            if c == 0 {
+                continue;
+            }
+            self.count += c;
+            self.sum += sums.value(i);
+            self.sum_sqr += sum_sqrs.value(i);
+            self.sum_cub += sum_cubs.value(i);
+            self.sum_four += sum_fours.value(i);
+        }
+
+        Ok(())
+    }
+
+    fn evaluate(&mut self) -> Result<ScalarValue> {
+        if self.count < 1 {
+            return Ok(ScalarValue::Float64(None));
+        }
+
+        let count_64 = 1_f64 / self.count as f64;
+        let m4 = count_64
+            * (self.sum_four - 4.0 * self.sum_cub * self.sum * count_64
+                + 6.0 * self.sum_sqr * self.sum.powi(2) * count_64.powi(2)
+                - 3.0 * self.sum.powi(4) * count_64.powi(3));
+
+        let m2 = (self.sum_sqr - self.sum.powi(2) * count_64) * count_64;
+        if m2 <= 0.0 {
+            return Ok(ScalarValue::Float64(None));
+        }
+
+        let target = m4 / (m2.powi(2)) - 3.0;
+        Ok(ScalarValue::Float64(Some(target)))
+    }
+
+    fn size(&self) -> usize {
+        std::mem::size_of_val(self)
+    }
+
+    fn state(&mut self) -> Result<Vec<ScalarValue>> {
+        Ok(vec![
+            ScalarValue::from(self.count),
+            ScalarValue::from(self.sum),
+            ScalarValue::from(self.sum_sqr),
+            ScalarValue::from(self.sum_cub),
+            ScalarValue::from(self.sum_four),
+        ])
+    }
+}

src/lib.rs

@@ -27,11 +27,12 @@ use datafusion::logical_expr::AggregateUDF;
 pub mod macros;
 pub mod common;
 pub mod kurtosis;
+pub mod kurtosis_pop;
 pub mod max_min_by;
 pub mod mode;
-
 pub mod expr_extra_fn {
     pub use super::kurtosis::kurtosis;
+    pub use super::kurtosis_pop::kurtosis_pop;
     pub use super::max_min_by::max_by;
     pub use super::max_min_by::min_by;
     pub use super::mode::mode;
@@ -43,6 +44,7 @@ pub fn all_extra_aggregate_functions() -> Vec<Arc<AggregateUDF>> {
         max_min_by::max_by_udaf(),
         max_min_by::min_by_udaf(),
         kurtosis::kurtosis_udaf(),
+        kurtosis_pop::kurtosis_pop_udaf(),
     ]
 }
 

tests/main.rs

@@ -50,7 +50,6 @@ async fn test_mode_utf8() {
           - +---------------------------+
     "###);
 }
-
 #[tokio::test]
 async fn test_mode_int64() {
     let mut execution = TestExecution::new().await.unwrap().with_setup(TEST_TABLE).await;
@@ -252,6 +251,66 @@ async fn test_max_by_and_min_by() {
     "###);
 }
 
+#[tokio::test]
+async fn test_kurtosis_pop() {
+    let mut execution = TestExecution::new().await.unwrap().with_setup(TEST_TABLE).await;
+
+    // Test with int64
+    let actual = execution
+        .run_and_format("SELECT kurtosis_pop(int64_col) FROM test_table")
+        .await;
+
+    insta::assert_yaml_snapshot!(actual, @r###"
+        - +------------------------------------+
+        - "| kurtosis_pop(test_table.int64_col) |"
+        - +------------------------------------+
+        - "| -0.9599999999999755                |"
+        - +------------------------------------+
+    "###);
+
+    // Test with float64
+    let actual = execution
+        .run_and_format("SELECT kurtosis_pop(float64_col) FROM test_table")
+        .await;
+
+    insta::assert_yaml_snapshot!(actual, @r###"
+    - +--------------------------------------+
+    - "| kurtosis_pop(test_table.float64_col) |"
+    - +--------------------------------------+
+    - "| -0.9599999999999755                  |"
+    - +--------------------------------------+
+"###);
+
+    let actual = execution
+        .run_and_format("SELECT kurtosis_pop(col) FROM VALUES (1.0) as tab(col)")
+        .await;
+    insta::assert_yaml_snapshot!(actual, @r###"
+    - +-----------------------+
+    - "| kurtosis_pop(tab.col) |"
+    - +-----------------------+
+    - "|                       |"
+    - +-----------------------+
+"###);
+
+    let actual = execution.run_and_format("SELECT kurtosis_pop(1.0)").await;
+    insta::assert_yaml_snapshot!(actual, @r###"
+    - +--------------------------+
+    - "| kurtosis_pop(Float64(1)) |"
+    - +--------------------------+
+    - "|                          |"
+    - +--------------------------+
+"###);
+
+    let actual = execution.run_and_format("SELECT kurtosis_pop(null)").await;
+    insta::assert_yaml_snapshot!(actual, @r###"
+- +--------------------+
+- "| kurtosis_pop(NULL) |"
+- +--------------------+
+- "|                    |"
+- +--------------------+
+"###);
+}
+
 #[tokio::test]
 async fn test_kurtosis() {
     let mut execution = TestExecution::new().await.unwrap();