Optimize performance of math::cot (~2x faster)

datafusion/functions/Cargo.toml

@@ -182,6 +182,11 @@ harness = false
 name = "character_length"
 required-features = ["unicode_expressions"]
 
+[[bench]]
+harness = false
+name = "cot"
+required-features = ["math_expressions"]
+
 [[bench]]
 harness = false
 name = "strpos"

datafusion/functions/benches/cot.rs

@@ -0,0 +1,47 @@
+// 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.
+
+extern crate criterion;
+
+use arrow::{
+    datatypes::{Float32Type, Float64Type},
+    util::bench_util::create_primitive_array,
+};
+use criterion::{black_box, criterion_group, criterion_main, Criterion};
+use datafusion_expr::ColumnarValue;
+use datafusion_functions::math::cot;
+
+use std::sync::Arc;
+
+fn criterion_benchmark(c: &mut Criterion) {
+    let cot_fn = cot();
+    for size in [1024, 4096, 8192] {
+        let f32_array = Arc::new(create_primitive_array::<Float32Type>(size, 0.2));
+        let f32_args = vec![ColumnarValue::Array(f32_array)];
+        c.bench_function(&format!("cot f32 array: {}", size), |b| {
+            b.iter(|| black_box(cot_fn.invoke(&f32_args).unwrap()))
+        });
+        let f64_array = Arc::new(create_primitive_array::<Float64Type>(size, 0.2));
+        let f64_args = vec![ColumnarValue::Array(f64_array)];
+        c.bench_function(&format!("cot f64 array: {}", size), |b| {
+            b.iter(|| black_box(cot_fn.invoke(&f64_args).unwrap()))
+        });
+    }
+}
+
+criterion_group!(benches, criterion_benchmark);
+criterion_main!(benches);

datafusion/functions/src/math/cot.rs

@@ -18,11 +18,11 @@
 use std::any::Any;
 use std::sync::Arc;
 
-use arrow::array::{ArrayRef, Float32Array, Float64Array};
-use arrow::datatypes::DataType;
+use arrow::array::{ArrayRef, AsArray};
 use arrow::datatypes::DataType::{Float32, Float64};
+use arrow::datatypes::{DataType, Float32Type, Float64Type};
 
-use datafusion_common::{exec_err, DataFusionError, Result};
+use datafusion_common::{exec_err, Result};
 use datafusion_expr::ColumnarValue;
 use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
 
@@ -85,18 +85,16 @@ impl ScalarUDFImpl for CotFunc {
 ///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),
+        Float64 => Ok(Arc::new(
+            args[0]
+                .as_primitive::<Float64Type>()
+                .unary::<_, Float64Type>(|x: f64| compute_cot64(x)),
+        ) as ArrayRef),
+        Float32 => Ok(Arc::new(
+            args[0]
+                .as_primitive::<Float32Type>()
+                .unary::<_, Float32Type>(|x: f32| compute_cot32(x)),
+        ) as ArrayRef),
         other => exec_err!("Unsupported data type {other:?} for function cot"),
     }
 }