move Trunc, Cot, Round, iszero functions to datafusion-functions (#10000)

* move Floor, Gcd, Lcm, Pi to datafusion-functions

* remove floor fn

* move Trunc, Cot, Round, iszero functions to datafusion-functions

* Make mod iszero public, minor ordering change to keep the alphabetical ordering theme.

---------

Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>

Author: Omega359

datafusion/expr/src/built_in_function.rs

@@ -45,17 +45,8 @@ pub enum BuiltinScalarFunction {
     Exp,
     /// factorial
     Factorial,
-    /// iszero
-    Iszero,
     /// nanvl
     Nanvl,
-    /// round
-    Round,
-    /// trunc
-    Trunc,
-    /// cot
-    Cot,
-
     // string functions
     /// concat
     Concat,
@@ -123,11 +114,7 @@ impl BuiltinScalarFunction {
             BuiltinScalarFunction::Coalesce => Volatility::Immutable,
             BuiltinScalarFunction::Exp => Volatility::Immutable,
             BuiltinScalarFunction::Factorial => Volatility::Immutable,
-            BuiltinScalarFunction::Iszero => Volatility::Immutable,
             BuiltinScalarFunction::Nanvl => Volatility::Immutable,
-            BuiltinScalarFunction::Round => Volatility::Immutable,
-            BuiltinScalarFunction::Cot => Volatility::Immutable,
-            BuiltinScalarFunction::Trunc => Volatility::Immutable,
             BuiltinScalarFunction::Concat => Volatility::Immutable,
             BuiltinScalarFunction::ConcatWithSeparator => Volatility::Immutable,
             BuiltinScalarFunction::EndsWith => Volatility::Immutable,
@@ -175,16 +162,12 @@ impl BuiltinScalarFunction {
                 _ => Ok(Float64),
             },
 
-            BuiltinScalarFunction::Iszero => Ok(Boolean),
-
-            BuiltinScalarFunction::Ceil
-            | BuiltinScalarFunction::Exp
-            | BuiltinScalarFunction::Round
-            | BuiltinScalarFunction::Trunc
-            | BuiltinScalarFunction::Cot => match input_expr_types[0] {
-                Float32 => Ok(Float32),
-                _ => Ok(Float64),
-            },
+            BuiltinScalarFunction::Ceil | BuiltinScalarFunction::Exp => {
+                match input_expr_types[0] {
+                    Float32 => Ok(Float32),
+                    _ => Ok(Float64),
+                }
+            }
         }
     }
 
@@ -217,45 +200,21 @@ impl BuiltinScalarFunction {
                 self.volatility(),
             ),
             BuiltinScalarFunction::Random => Signature::exact(vec![], self.volatility()),
-            BuiltinScalarFunction::Round => Signature::one_of(
-                vec![
-                    Exact(vec![Float64, Int64]),
-                    Exact(vec![Float32, Int64]),
-                    Exact(vec![Float64]),
-                    Exact(vec![Float32]),
-                ],
-                self.volatility(),
-            ),
-            BuiltinScalarFunction::Trunc => Signature::one_of(
-                vec![
-                    Exact(vec![Float32, Int64]),
-                    Exact(vec![Float64, Int64]),
-                    Exact(vec![Float64]),
-                    Exact(vec![Float32]),
-                ],
-                self.volatility(),
-            ),
             BuiltinScalarFunction::Nanvl => Signature::one_of(
                 vec![Exact(vec![Float32, Float32]), Exact(vec![Float64, Float64])],
                 self.volatility(),
             ),
             BuiltinScalarFunction::Factorial => {
                 Signature::uniform(1, vec![Int64], self.volatility())
             }
-            BuiltinScalarFunction::Ceil
-            | BuiltinScalarFunction::Exp
-            | BuiltinScalarFunction::Cot => {
+            BuiltinScalarFunction::Ceil | BuiltinScalarFunction::Exp => {
                 // math expressions expect 1 argument of type f64 or f32
                 // priority is given to f64 because e.g. `sqrt(1i32)` is in IR (real numbers) and thus we
                 // return the best approximation for it (in f64).
                 // We accept f32 because in this case it is clear that the best approximation
                 // will be as good as the number of digits in the number
                 Signature::uniform(1, vec![Float64, Float32], self.volatility())
             }
-            BuiltinScalarFunction::Iszero => Signature::one_of(
-                vec![Exact(vec![Float32]), Exact(vec![Float64])],
-                self.volatility(),
-            ),
         }
     }
 
@@ -268,8 +227,6 @@ impl BuiltinScalarFunction {
             BuiltinScalarFunction::Ceil
                 | BuiltinScalarFunction::Exp
                 | BuiltinScalarFunction::Factorial
-                | BuiltinScalarFunction::Round
-                | BuiltinScalarFunction::Trunc
         ) {
             Some(vec![Some(true)])
         } else {
@@ -281,14 +238,10 @@ impl BuiltinScalarFunction {
     pub fn aliases(&self) -> &'static [&'static str] {
         match self {
             BuiltinScalarFunction::Ceil => &["ceil"],
-            BuiltinScalarFunction::Cot => &["cot"],
             BuiltinScalarFunction::Exp => &["exp"],
             BuiltinScalarFunction::Factorial => &["factorial"],
-            BuiltinScalarFunction::Iszero => &["iszero"],
             BuiltinScalarFunction::Nanvl => &["nanvl"],
             BuiltinScalarFunction::Random => &["random"],
-            BuiltinScalarFunction::Round => &["round"],
-            BuiltinScalarFunction::Trunc => &["trunc"],
 
             // conditional functions
             BuiltinScalarFunction::Coalesce => &["coalesce"],

datafusion/expr/src/expr_fn.rs

@@ -530,20 +530,14 @@ macro_rules! nary_scalar_expr {
 // generate methods for creating the supported unary/binary expressions
 
 // math functions
-scalar_expr!(Cot, cot, num, "cotangent of a number");
 scalar_expr!(Factorial, factorial, num, "factorial");
 scalar_expr!(
     Ceil,
     ceil,
     num,
     "nearest integer greater than or equal to argument"
 );
-nary_scalar_expr!(Round, round, "round to nearest integer");
-nary_scalar_expr!(
-    Trunc,
-    trunc,
-    "truncate toward zero, with optional precision"
-);
+
 scalar_expr!(Exp, exp, num, "exponential");
 
 scalar_expr!(InitCap, initcap, string, "converts the first letter of each word in `string` in uppercase and the remaining characters in lowercase");
@@ -557,12 +551,6 @@ nary_scalar_expr!(
 );
 nary_scalar_expr!(Concat, concat_expr, "concatenates several strings");
 scalar_expr!(Nanvl, nanvl, x y, "returns x if x is not NaN otherwise returns y");
-scalar_expr!(
-    Iszero,
-    iszero,
-    num,
-    "returns true if a given number is +0.0 or -0.0 otherwise returns false"
-);
 
 /// Create a CASE WHEN statement with literal WHEN expressions for comparison to the base expression.
 pub fn case(expr: Expr) -> CaseBuilder {
@@ -872,12 +860,6 @@ impl WindowUDFImpl for SimpleWindowUDF {
 }
 
 /// Calls a named built in function
-/// ```
-/// use datafusion_expr::{col, lit, call_fn};
-///
-/// // create the expression trunc(x) < 0.2
-/// let expr = call_fn("trunc", vec![col("x")]).unwrap().lt(lit(0.2));
-/// ```
 pub fn call_fn(name: impl AsRef<str>, args: Vec<Expr>) -> Result<Expr> {
     match name.as_ref().parse::<BuiltinScalarFunction>() {
         Ok(fun) => Ok(Expr::ScalarFunction(ScalarFunction::new(fun, args))),
@@ -935,38 +917,12 @@ mod test {
     };
 }
 
-    macro_rules! test_nary_scalar_expr {
-    ($ENUM:ident, $FUNC:ident, $($arg:ident),*) => {
-        let expected = [$(stringify!($arg)),*];
-        let result = $FUNC(
-            vec![
-                $(
-                    col(stringify!($arg.to_string()))
-                ),*
-            ]
-        );
-        if let Expr::ScalarFunction(ScalarFunction { func_def: ScalarFunctionDefinition::BuiltIn(fun), args }) = result {
-            let name = built_in_function::BuiltinScalarFunction::$ENUM;
-            assert_eq!(name, fun);
-            assert_eq!(expected.len(), args.len());
-        } else {
-            assert!(false, "unexpected: {:?}", result);
-        }
-    };
-}
-
     #[test]
     fn scalar_function_definitions() {
-        test_unary_scalar_expr!(Cot, cot);
         test_unary_scalar_expr!(Factorial, factorial);
         test_unary_scalar_expr!(Ceil, ceil);
-        test_nary_scalar_expr!(Round, round, input);
-        test_nary_scalar_expr!(Round, round, input, decimal_places);
-        test_nary_scalar_expr!(Trunc, trunc, num);
-        test_nary_scalar_expr!(Trunc, trunc, num, precision);
         test_unary_scalar_expr!(Exp, exp);
         test_scalar_expr!(Nanvl, nanvl, x, y);
-        test_scalar_expr!(Iszero, iszero, input);
 
         test_scalar_expr!(InitCap, initcap, string);
         test_scalar_expr!(EndsWith, ends_with, string, characters);

datafusion/functions/src/math/cot.rs

@@ -0,0 +1,166 @@
+// 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.
+
+use std::any::Any;
+use std::sync::Arc;
+
+use arrow::array::{ArrayRef, Float32Array, Float64Array};
+use arrow::datatypes::DataType;
+use arrow::datatypes::DataType::{Float32, Float64};
+
+use datafusion_common::{exec_err, DataFusionError, Result};
+use datafusion_expr::ColumnarValue;
+use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
+
+use crate::utils::make_scalar_function;
+
+#[derive(Debug)]
+pub struct CotFunc {
+    signature: Signature,
+}
+
+impl Default for CotFunc {
+    fn default() -> Self {
+        CotFunc::new()
+    }
+}
+
+impl CotFunc {
+    pub fn new() -> Self {
+        use DataType::*;
+        Self {
+            // math expressions expect 1 argument of type f64 or f32
+            // priority is given to f64 because e.g. `sqrt(1i32)` is in IR (real numbers) and thus we
+            // return the best approximation for it (in f64).
+            // We accept f32 because in this case it is clear that the best approximation
+            // will be as good as the number of digits in the number
+            signature: Signature::uniform(
+                1,
+                vec![Float64, Float32],
+                Volatility::Immutable,
+            ),
+        }
+    }
+}
+
+impl ScalarUDFImpl for CotFunc {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn name(&self) -> &str {
+        "cot"
+    }
+
+    fn signature(&self) -> &Signature {
+        &self.signature
+    }
+
+    fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
+        match arg_types[0] {
+            Float32 => Ok(Float32),
+            _ => Ok(Float64),
+        }
+    }
+
+    fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
+        make_scalar_function(cot, vec![])(args)
+    }
+}
+
+///cot SQL function
+fn cot(args: &[ArrayRef]) -> Result<ArrayRef> {
+    match args[0].data_type() {
+        Float64 => Ok(Arc::new(make_function_scalar_inputs!(
+            &args[0],
+            "x",
+            Float64Array,
+            { compute_cot64 }
+        )) as ArrayRef),
+        Float32 => Ok(Arc::new(make_function_scalar_inputs!(
+            &args[0],
+            "x",
+            Float32Array,
+            { compute_cot32 }
+        )) as ArrayRef),
+        other => exec_err!("Unsupported data type {other:?} for function cot"),
+    }
+}
+
+fn compute_cot32(x: f32) -> f32 {
+    let a = f32::tan(x);
+    1.0 / a
+}
+
+fn compute_cot64(x: f64) -> f64 {
+    let a = f64::tan(x);
+    1.0 / a
+}
+
+#[cfg(test)]
+mod test {
+    use crate::math::cot::cot;
+    use arrow::array::{ArrayRef, Float32Array, Float64Array};
+    use datafusion_common::cast::{as_float32_array, as_float64_array};
+    use std::sync::Arc;
+
+    #[test]
+    fn test_cot_f32() {
+        let args: Vec<ArrayRef> =
+            vec![Arc::new(Float32Array::from(vec![12.1, 30.0, 90.0, -30.0]))];
+        let result = cot(&args).expect("failed to initialize function cot");
+        let floats =
+            as_float32_array(&result).expect("failed to initialize function cot");
+
+        let expected = Float32Array::from(vec![
+            -1.986_460_4,
+            -0.156_119_96,
+            -0.501_202_8,
+            0.156_119_96,
+        ]);
+
+        let eps = 1e-6;
+        assert_eq!(floats.len(), 4);
+        assert!((floats.value(0) - expected.value(0)).abs() < eps);
+        assert!((floats.value(1) - expected.value(1)).abs() < eps);
+        assert!((floats.value(2) - expected.value(2)).abs() < eps);
+        assert!((floats.value(3) - expected.value(3)).abs() < eps);
+    }
+
+    #[test]
+    fn test_cot_f64() {
+        let args: Vec<ArrayRef> =
+            vec![Arc::new(Float64Array::from(vec![12.1, 30.0, 90.0, -30.0]))];
+        let result = cot(&args).expect("failed to initialize function cot");
+        let floats =
+            as_float64_array(&result).expect("failed to initialize function cot");
+
+        let expected = Float64Array::from(vec![
+            -1.986_458_685_881_4,
+            -0.156_119_952_161_6,
+            -0.501_202_783_380_1,
+            0.156_119_952_161_6,
+        ]);
+
+        let eps = 1e-12;
+        assert_eq!(floats.len(), 4);
+        assert!((floats.value(0) - expected.value(0)).abs() < eps);
+        assert!((floats.value(1) - expected.value(1)).abs() < eps);
+        assert!((floats.value(2) - expected.value(2)).abs() < eps);
+        assert!((floats.value(3) - expected.value(3)).abs() < eps);
+    }
+}