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Merged
Jefffrey merged 7 commits into from
Feb 5, 2026
Merged

feat: unify left and right functions and benches #20114

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c8087d8
Combine left and right benchmarks
theirix Feb 1, 2026
204921c
Unify left and right implementation
theirix Feb 1, 2026
aa58ff0
Move common to unicode mod
theirix Feb 2, 2026
8794229
Add license header
theirix Feb 2, 2026
614dc5b
Combine positive and negative benches
theirix Feb 3, 2026
0bb6925
Fix typo
theirix Feb 3, 2026
426997f
Simplify slicer for left
theirix Feb 3, 2026
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7 changes: 1 addition & 6 deletions datafusion/functions/Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -308,12 +308,7 @@ required-features = ["string_expressions"]

[[bench]]
harness = false
name = "left"
required-features = ["unicode_expressions"]

[[bench]]
harness = false
name = "right"
name = "left_right"
required-features = ["unicode_expressions"]

[[bench]]
Expand Down
140 changes: 0 additions & 140 deletions datafusion/functions/benches/left.rs
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130 changes: 130 additions & 0 deletions datafusion/functions/benches/left_right.rs
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Original file line number Diff line number Diff line change
@@ -0,0 +1,130 @@
// 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 std::hint::black_box;
use std::sync::Arc;

use arrow::array::{ArrayRef, Int64Array};
use arrow::datatypes::{DataType, Field};
use arrow::util::bench_util::{
create_string_array_with_len, create_string_view_array_with_len,
};
use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
use datafusion_common::config::ConfigOptions;
use datafusion_expr::{ColumnarValue, ScalarFunctionArgs};
use datafusion_functions::unicode::{left, right};

fn create_args(
size: usize,
str_len: usize,
use_negative: bool,
is_string_view: bool,
) -> Vec<ColumnarValue> {
let string_arg = if is_string_view {
ColumnarValue::Array(Arc::new(create_string_view_array_with_len(
size, 0.1, str_len, true,
)))
} else {
ColumnarValue::Array(Arc::new(create_string_array_with_len::<i32>(
size, 0.1, str_len,
)))
};

// For negative n, we want to trigger the double-iteration code path
let n_values: Vec<i64> = if use_negative {
(0..size).map(|i| -((i % 10 + 1) as i64)).collect()
} else {
(0..size).map(|i| (i % 10 + 1) as i64).collect()
};
let n_array = Arc::new(Int64Array::from(n_values));

vec![
string_arg,
ColumnarValue::Array(Arc::clone(&n_array) as ArrayRef),
]
}

fn criterion_benchmark(c: &mut Criterion) {
let left_function = left();
let right_function = right();

for function in [left_function, right_function] {
for is_string_view in [false, true] {
for is_negative in [false, true] {
for size in [1024, 4096] {
let function_name = function.name();
let mut group =
c.benchmark_group(format!("{function_name} size={size}"));

let bench_name = format!(
"{} {} n",
if is_string_view {
"string_view_array"
} else {
"string_array"
},
if is_negative { "negative" } else { "positive" },
);
let return_type = if is_string_view {
DataType::Utf8View
} else {
DataType::Utf8
};

let args = create_args(size, 32, is_negative, is_string_view);
group.bench_function(BenchmarkId::new(bench_name, size), |b| {
let arg_fields = args
.iter()
.enumerate()
.map(|(idx, arg)| {
Field::new(format!("arg_{idx}"), arg.data_type(), true)
.into()
})
.collect::<Vec<_>>();
let config_options = Arc::new(ConfigOptions::default());

b.iter(|| {
black_box(
function
.invoke_with_args(ScalarFunctionArgs {
args: args.clone(),
arg_fields: arg_fields.clone(),
number_rows: size,
return_field: Field::new(
"f",
return_type.clone(),
true,
)
.into(),
config_options: Arc::clone(&config_options),
})
.expect("should work"),
)
})
});

group.finish();
}
}
}
}
}

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