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8 changes: 8 additions & 0 deletions datafusion/physical-expr/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -58,3 +58,11 @@ regex = { version = "^1.4.3", optional = true }
sha2 = { version = "^0.10.1", optional = true }
unicode-segmentation = { version = "^1.7.1", optional = true }
uuid = { version = "^1.2", features = ["v4"] }

[dev-dependencies]
criterion = "0.4"
rand = "0.8"

[[bench]]
harness = false
name = "in_list"
120 changes: 120 additions & 0 deletions datafusion/physical-expr/benches/in_list.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,120 @@
// 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 arrow::array::{Array, ArrayRef, Float32Array, Int32Array, StringArray};
use arrow::datatypes::{Field, Schema};
use arrow::record_batch::RecordBatch;
use criterion::{black_box, criterion_group, criterion_main, Criterion};
use datafusion_common::ScalarValue;
use datafusion_physical_expr::expressions::{col, in_list, lit};
use rand::distributions::Alphanumeric;
use rand::prelude::*;
use std::sync::Arc;

fn do_bench(c: &mut Criterion, name: &str, values: ArrayRef, exprs: &[ScalarValue]) {
let schema = Schema::new(vec![Field::new("a", values.data_type().clone(), true)]);
let exprs = exprs.iter().map(|s| lit(s.clone())).collect();
let expr = in_list(col("a", &schema).unwrap(), exprs, &false, &schema).unwrap();
let batch = RecordBatch::try_new(Arc::new(schema), vec![values]).unwrap();

c.bench_function(name, |b| {
b.iter(|| black_box(expr.evaluate(black_box(&batch)).unwrap()))
});
}

fn random_string(rng: &mut StdRng, len: usize) -> String {
let value = rng.sample_iter(&Alphanumeric).take(len).collect();
String::from_utf8(value).unwrap()
}

fn do_benches(
c: &mut Criterion,
array_length: usize,
in_list_length: usize,
null_percent: f64,
) {
let mut rng = StdRng::seed_from_u64(120320);
for string_length in [5, 10, 20] {
let values: StringArray = (0..array_length)
.map(|_| {
rng.gen_bool(null_percent)
.then(|| random_string(&mut rng, string_length))
})
.collect();

let in_list: Vec<_> = (0..in_list_length)
.map(|_| ScalarValue::Utf8(Some(random_string(&mut rng, string_length))))
.collect();

do_bench(
c,
&format!(
"in_list_utf8({}) ({}, {}) IN ({}, 0)",
string_length, array_length, null_percent, in_list_length
),
Arc::new(values),
&in_list,
)
}

let values: Float32Array = (0..array_length)
.map(|_| rng.gen_bool(null_percent).then(|| rng.gen()))
.collect();

let in_list: Vec<_> = (0..in_list_length)
.map(|_| ScalarValue::Float32(Some(rng.gen())))
.collect();

do_bench(
c,
&format!(
"in_list_f32 ({}, {}) IN ({}, 0)",
array_length, null_percent, in_list_length
),
Arc::new(values),
&in_list,
);

let values: Int32Array = (0..array_length)
.map(|_| rng.gen_bool(null_percent).then(|| rng.gen()))
.collect();

let in_list: Vec<_> = (0..in_list_length)
.map(|_| ScalarValue::Int32(Some(rng.gen())))
.collect();

do_bench(
c,
&format!(
"in_list_i32 ({}, {}) IN ({}, 0)",
array_length, null_percent, in_list_length
),
Arc::new(values),
&in_list,
)
}

fn criterion_benchmark(c: &mut Criterion) {
for in_list_length in [1, 3, 10, 100] {
for null_percent in [0., 0.2] {
do_benches(c, 1024, in_list_length, null_percent)
}
}
}

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