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// 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 arrow::datatypes::{DataType, Field};
use criterion::{Criterion, criterion_group, criterion_main};
use datafusion_common::config::ConfigOptions;
use datafusion_expr::{ScalarFunctionArgs, ScalarUDFImpl};
use datafusion_functions::math::random::RandomFunc;
use std::hint::black_box;
use std::sync::Arc;

fn criterion_benchmark(c: &mut Criterion) {
    let random_func = RandomFunc::new();
    let return_field = Field::new("f", DataType::Float64, true).into();
    let config_options = Arc::new(ConfigOptions::default());

    // Benchmark to evaluate 1M rows in batch size 8192
    let iterations = 1_000_000 / 8192; // Calculate how many iterations are needed to reach approximately 1M rows
    c.bench_function("random_1M_rows_batch_8192", |b| {
        b.iter(|| {
            for _ in 0..iterations {
                black_box(
                    random_func
                        .invoke_with_args(ScalarFunctionArgs {
                            args: vec![],
                            arg_fields: vec![],
                            number_rows: 8192,
                            return_field: Arc::clone(&return_field),
                            config_options: Arc::clone(&config_options),
                        })
                        .unwrap(),
                );
            }
        })
    });

    let return_field = Field::new("f", DataType::Float64, true).into();
    // Benchmark to evaluate 1M rows in batch size 128
    let iterations_128 = 1_000_000 / 128; // Calculate how many iterations are needed to reach approximately 1M rows with batch size 128
    c.bench_function("random_1M_rows_batch_128", |b| {
        b.iter(|| {
            for _ in 0..iterations_128 {
                black_box(
                    random_func
                        .invoke_with_args(ScalarFunctionArgs {
                            args: vec![],
                            arg_fields: vec![],
                            number_rows: 128,
                            return_field: Arc::clone(&return_field),
                            config_options: Arc::clone(&config_options),
                        })
                        .unwrap(),
                );
            }
        })
    });
}

criterion_group!(benches, criterion_benchmark);
criterion_main!(benches);
