refactor_boolean_cast_ops_add_benchmarks

Author: B Vadlamani

native/spark-expr/Cargo.toml

@@ -95,3 +95,7 @@ harness = false
 [[test]]
 name = "test_udf_registration"
 path = "tests/spark_expr_reg.rs"
+
+[[bench]]
+name = "cast_boolean"
+harness = false

native/spark-expr/benches/cast_boolean.rs

@@ -0,0 +1,74 @@
+// 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::sync::Arc;
+use arrow::array::{BooleanBuilder, RecordBatch};
+use arrow::datatypes::{DataType, Field, Schema};
+use criterion::{criterion_group, criterion_main, Criterion};
+use datafusion::physical_expr::expressions::Column;
+use datafusion::physical_expr::PhysicalExpr;
+use datafusion_comet_spark_expr::{Cast, EvalMode, SparkCastOptions};
+
+fn criterion_benchmark(c: &mut Criterion) {
+    let expr = Arc::new(Column::new("a", 0));
+    let boolean_batch = create_boolean_batch();
+    let spark_cast_options = SparkCastOptions::new(EvalMode::Legacy, "UTC", false);
+    Cast::new(expr.clone(), DataType::Int8, spark_cast_options.clone());
+    let cast_to_i8 = Cast::new(expr.clone(), DataType::Boolean, spark_cast_options.clone());
+    let cast_to_i16 = Cast::new(expr.clone(), DataType::Boolean, spark_cast_options.clone());
+    let cast_to_i32 = Cast::new(expr.clone(), DataType::Boolean, spark_cast_options.clone());
+    let cast_to_i64 = Cast::new(expr.clone(), DataType::Boolean, spark_cast_options);
+
+    let mut group = c.benchmark_group(format!("cast_bool_to_int"));
+    group.bench_function("i8", |b| {
+        b.iter(|| cast_to_i8.evaluate(&boolean_batch).unwrap());
+    });
+    group.bench_function("i16", |b| {
+        b.iter(|| cast_to_i16.evaluate(&boolean_batch).unwrap());
+    });
+    group.bench_function("i32", |b| {
+        b.iter(|| cast_to_i32.evaluate(&boolean_batch).unwrap());
+    });
+    group.bench_function("i64", |b| {
+        b.iter(|| cast_to_i64.evaluate(&boolean_batch).unwrap());
+    });
+}
+
+fn create_boolean_batch() -> RecordBatch {
+    let schema = Arc::new(Schema::new(vec![Field::new("a", DataType::Boolean, true)]));
+    let mut b = BooleanBuilder::with_capacity(1000);
+    for i in 0..1000 {
+        if i % 10 == 0 {
+            b.append_null();
+        } else {
+            b.append_value(rand::random::<bool>());
+        }
+    }
+    let array = b.finish();
+    RecordBatch::try_new(schema, vec![Arc::new(array)]).unwrap()
+}
+
+fn config() -> Criterion {
+    Criterion::default()
+}
+
+criterion_group! {
+    name = benches;
+    config = config();
+    targets = criterion_benchmark
+}
+criterion_main!(benches);