Move Nanvl and random functions to datafusion-functions (#10017)

* Move Nanvl and random functions to datafusion-functions

* Remove extraneous test udf.

datafusion/core/tests/simplification.rs

@@ -28,9 +28,10 @@ use datafusion_expr::expr::ScalarFunction;
 use datafusion_expr::logical_plan::builder::table_scan_with_filters;
 use datafusion_expr::simplify::SimplifyInfo;
 use datafusion_expr::{
-    expr, table_scan, BuiltinScalarFunction, Cast, ColumnarValue, Expr, ExprSchemable,
-    LogicalPlan, LogicalPlanBuilder, ScalarUDF, Volatility,
+    expr, table_scan, Cast, ColumnarValue, Expr, ExprSchemable, LogicalPlan,
+    LogicalPlanBuilder, ScalarUDF, Volatility,
 };
+use datafusion_functions::math;
 use datafusion_optimizer::simplify_expressions::{ExprSimplifier, SimplifyExpressions};
 use datafusion_optimizer::{OptimizerContext, OptimizerRule};
 use std::sync::Arc;
@@ -383,17 +384,17 @@ fn test_const_evaluator_scalar_functions() {
 
     // volatile / stable functions should not be evaluated
     // rand() + (1 + 2) --> rand() + 3
-    let fun = BuiltinScalarFunction::Random;
-    assert_eq!(fun.volatility(), Volatility::Volatile);
-    let rand = Expr::ScalarFunction(ScalarFunction::new(fun, vec![]));
+    let fun = math::random();
+    assert_eq!(fun.signature().volatility, Volatility::Volatile);
+    let rand = Expr::ScalarFunction(ScalarFunction::new_udf(fun, vec![]));
     let expr = rand.clone() + (lit(1) + lit(2));
     let expected = rand + lit(3);
     test_evaluate(expr, expected);
 
     // parenthesization matters: can't rewrite
     // (rand() + 1) + 2 --> (rand() + 1) + 2)
-    let fun = BuiltinScalarFunction::Random;
-    let rand = Expr::ScalarFunction(ScalarFunction::new(fun, vec![]));
+    let fun = math::random();
+    let rand = Expr::ScalarFunction(ScalarFunction::new_udf(fun, vec![]));
     let expr = (rand + lit(1)) + lit(2);
     test_evaluate(expr.clone(), expr);
 }

datafusion/expr/src/built_in_function.rs

@@ -45,8 +45,6 @@ pub enum BuiltinScalarFunction {
     Exp,
     /// factorial
     Factorial,
-    /// nanvl
-    Nanvl,
     // string functions
     /// concat
     Concat,
@@ -56,8 +54,6 @@ pub enum BuiltinScalarFunction {
     EndsWith,
     /// initcap
     InitCap,
-    /// random
-    Random,
 }
 
 /// Maps the sql function name to `BuiltinScalarFunction`
@@ -114,14 +110,10 @@ impl BuiltinScalarFunction {
             BuiltinScalarFunction::Coalesce => Volatility::Immutable,
             BuiltinScalarFunction::Exp => Volatility::Immutable,
             BuiltinScalarFunction::Factorial => Volatility::Immutable,
-            BuiltinScalarFunction::Nanvl => Volatility::Immutable,
             BuiltinScalarFunction::Concat => Volatility::Immutable,
             BuiltinScalarFunction::ConcatWithSeparator => Volatility::Immutable,
             BuiltinScalarFunction::EndsWith => Volatility::Immutable,
             BuiltinScalarFunction::InitCap => Volatility::Immutable,
-
-            // Volatile builtin functions
-            BuiltinScalarFunction::Random => Volatility::Volatile,
         }
     }
 
@@ -152,16 +144,10 @@ impl BuiltinScalarFunction {
             BuiltinScalarFunction::InitCap => {
                 utf8_to_str_type(&input_expr_types[0], "initcap")
             }
-            BuiltinScalarFunction::Random => Ok(Float64),
             BuiltinScalarFunction::EndsWith => Ok(Boolean),
 
             BuiltinScalarFunction::Factorial => Ok(Int64),
 
-            BuiltinScalarFunction::Nanvl => match &input_expr_types[0] {
-                Float32 => Ok(Float32),
-                _ => Ok(Float64),
-            },
-
             BuiltinScalarFunction::Ceil | BuiltinScalarFunction::Exp => {
                 match input_expr_types[0] {
                     Float32 => Ok(Float32),
@@ -199,11 +185,6 @@ impl BuiltinScalarFunction {
                 ],
                 self.volatility(),
             ),
-            BuiltinScalarFunction::Random => Signature::exact(vec![], 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())
             }
@@ -240,8 +221,6 @@ impl BuiltinScalarFunction {
             BuiltinScalarFunction::Ceil => &["ceil"],
             BuiltinScalarFunction::Exp => &["exp"],
             BuiltinScalarFunction::Factorial => &["factorial"],
-            BuiltinScalarFunction::Nanvl => &["nanvl"],
-            BuiltinScalarFunction::Random => &["random"],
 
             // conditional functions
             BuiltinScalarFunction::Coalesce => &["coalesce"],

datafusion/expr/src/expr.rs

@@ -1903,8 +1903,8 @@ mod test {
     use crate::expr::Cast;
     use crate::expr_fn::col;
     use crate::{
-        case, lit, BuiltinScalarFunction, ColumnarValue, Expr, ScalarFunctionDefinition,
-        ScalarUDF, ScalarUDFImpl, Signature, Volatility,
+        case, lit, ColumnarValue, Expr, ScalarFunctionDefinition, ScalarUDF,
+        ScalarUDFImpl, Signature, Volatility,
     };
     use arrow::datatypes::DataType;
     use datafusion_common::Column;
@@ -2018,13 +2018,6 @@ mod test {
 
     #[test]
     fn test_is_volatile_scalar_func_definition() {
-        // BuiltIn
-        assert!(
-            ScalarFunctionDefinition::BuiltIn(BuiltinScalarFunction::Random)
-                .is_volatile()
-                .unwrap()
-        );
-
         // UDF
         #[derive(Debug)]
         struct TestScalarUDF {

datafusion/expr/src/expr_fn.rs

@@ -297,11 +297,6 @@ pub fn concat_ws(sep: Expr, values: Vec<Expr>) -> Expr {
     ))
 }
 
-/// Returns a random value in the range 0.0 <= x < 1.0
-pub fn random() -> Expr {
-    Expr::ScalarFunction(ScalarFunction::new(BuiltinScalarFunction::Random, vec![]))
-}
-
 /// Returns the approximate number of distinct input values.
 /// This function provides an approximation of count(DISTINCT x).
 /// Zero is returned if all input values are null.
@@ -550,7 +545,6 @@ nary_scalar_expr!(
     "concatenates several strings, placing a seperator between each one"
 );
 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");
 
 /// Create a CASE WHEN statement with literal WHEN expressions for comparison to the base expression.
 pub fn case(expr: Expr) -> CaseBuilder {
@@ -922,7 +916,6 @@ mod test {
         test_unary_scalar_expr!(Factorial, factorial);
         test_unary_scalar_expr!(Ceil, ceil);
         test_unary_scalar_expr!(Exp, exp);
-        test_scalar_expr!(Nanvl, nanvl, x, y);
 
         test_scalar_expr!(InitCap, initcap, string);
         test_scalar_expr!(EndsWith, ends_with, string, characters);

datafusion/expr/src/signature.rs

@@ -51,7 +51,7 @@ pub enum Volatility {
     Stable,
     /// A volatile function may change the return value from evaluation to evaluation.
     /// Multiple invocations of a volatile function may return different results when used in the
-    /// same query. An example of this is [super::BuiltinScalarFunction::Random]. DataFusion
+    /// same query. An example of this is the random() function. DataFusion
     /// can not evaluate such functions during planning.
     /// In the query `select col1, random() from t1`, `random()` function will be evaluated
     /// for each output row, resulting in a unique random value for each row.

datafusion/functions/Cargo.toml

@@ -77,6 +77,7 @@ hex = { version = "0.4", optional = true }
 itertools = { workspace = true }
 log = { workspace = true }
 md-5 = { version = "^0.10.0", optional = true }
+rand = { workspace = true }
 regex = { version = "1.8", optional = true }
 sha2 = { version = "^0.10.1", optional = true }
 unicode-segmentation = { version = "^1.7.1", optional = true }

datafusion/functions/src/math/mod.rs

@@ -27,8 +27,10 @@ pub mod iszero;
 pub mod lcm;
 pub mod log;
 pub mod nans;
+pub mod nanvl;
 pub mod pi;
 pub mod power;
+pub mod random;
 pub mod round;
 pub mod trunc;
 
@@ -55,9 +57,11 @@ make_udf_function!(lcm::LcmFunc, LCM, lcm);
 make_math_unary_udf!(LnFunc, LN, ln, ln, Some(vec![Some(true)]));
 make_math_unary_udf!(Log2Func, LOG2, log2, log2, Some(vec![Some(true)]));
 make_math_unary_udf!(Log10Func, LOG10, log10, log10, Some(vec![Some(true)]));
+make_udf_function!(nanvl::NanvlFunc, NANVL, nanvl);
 make_udf_function!(pi::PiFunc, PI, pi);
 make_udf_function!(power::PowerFunc, POWER, power);
 make_math_unary_udf!(RadiansFunc, RADIANS, radians, to_radians, None);
+make_udf_function!(random::RandomFunc, RANDOM, random);
 make_udf_function!(round::RoundFunc, ROUND, round);
 make_math_unary_udf!(SignumFunc, SIGNUM, signum, signum, None);
 make_math_unary_udf!(SinFunc, SIN, sin, sin, None);
@@ -180,6 +184,11 @@ pub mod expr_fn {
         super::log10().call(vec![num])
     }
 
+    #[doc = "returns x if x is not NaN otherwise returns y"]
+    pub fn nanvl(x: Expr, y: Expr) -> Expr {
+        super::nanvl().call(vec![x, y])
+    }
+
     #[doc = "Returns an approximate value of π"]
     pub fn pi() -> Expr {
         super::pi().call(vec![])
@@ -195,6 +204,11 @@ pub mod expr_fn {
         super::radians().call(vec![num])
     }
 
+    #[doc = "Returns a random value in the range 0.0 <= x < 1.0"]
+    pub fn random() -> Expr {
+        super::random().call(vec![])
+    }
+
     #[doc = "round to nearest integer"]
     pub fn round(args: Vec<Expr>) -> Expr {
         super::round().call(args)
@@ -261,9 +275,11 @@ pub fn functions() -> Vec<Arc<ScalarUDF>> {
         log(),
         log2(),
         log10(),
+        nanvl(),
         pi(),
         power(),
         radians(),
+        random(),
         round(),
         signum(),
         sin(),