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173 changes: 150 additions & 23 deletions datafusion/functions/benches/to_char.rs
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ use rand::prelude::IndexedRandom;
use rand::rngs::ThreadRng;
use rand::Rng;

fn random_date_in_range(
fn pick_date_in_range(
rng: &mut ThreadRng,
start_date: NaiveDate,
end_date: NaiveDate,
Expand All @@ -43,7 +43,7 @@ fn random_date_in_range(
start_date + TimeDelta::try_days(random_days).unwrap()
}

fn data(rng: &mut ThreadRng) -> Date32Array {
fn generate_date32_array(rng: &mut ThreadRng) -> Date32Array {
let mut data: Vec<i32> = vec![];
let unix_days_from_ce = NaiveDate::from_ymd_opt(1970, 1, 1)
.unwrap()
Expand All @@ -56,39 +56,139 @@ fn data(rng: &mut ThreadRng) -> Date32Array {
.expect("Date should parse");
for _ in 0..1000 {
data.push(
random_date_in_range(rng, start_date, end_date).num_days_from_ce()
pick_date_in_range(rng, start_date, end_date).num_days_from_ce()
- unix_days_from_ce,
);
}

Date32Array::from(data)
}

fn patterns(rng: &mut ThreadRng) -> StringArray {
let samples = [
"%Y:%m:%d".to_string(),
"%d-%m-%Y".to_string(),
"%d%m%Y".to_string(),
"%Y%m%d".to_string(),
"%Y...%m...%d".to_string(),
];
let mut data: Vec<String> = vec![];
const DATE_PATTERNS: [&str; 5] =
["%Y:%m:%d", "%d-%m-%Y", "%d%m%Y", "%Y%m%d", "%Y...%m...%d"];

const DATETIME_PATTERNS: [&str; 8] = [
"%Y:%m:%d %H:%M%S",
"%Y:%m:%d %_H:%M%S",
"%Y:%m:%d %k:%M%S",
"%d-%m-%Y %I%P-%M-%S %f",
"%d%m%Y %H",
"%Y%m%d %M-%S %.3f",
"%Y...%m...%d %T%3f",
"%c",
];

fn pick_date_pattern(rng: &mut ThreadRng) -> String {
DATE_PATTERNS
.choose(rng)
.expect("Empty list of date patterns")
.to_string()
}

fn pick_date_time_pattern(rng: &mut ThreadRng) -> String {
DATETIME_PATTERNS
.choose(rng)
.expect("Empty list of date time patterns")
.to_string()
}

fn pick_date_and_date_time_mixed_pattern(rng: &mut ThreadRng) -> String {
match rng.random_bool(0.5) {
true => pick_date_pattern(rng),
false => pick_date_time_pattern(rng),
}
}

fn generate_pattern_array(
rng: &mut ThreadRng,
pick_fn: impl Fn(&mut ThreadRng) -> String,
) -> StringArray {
let mut data = Vec::with_capacity(1000);

for _ in 0..1000 {
data.push(samples.choose(rng).unwrap().to_string());
data.push(pick_fn(rng));
}

StringArray::from(data)
}

fn generate_date_pattern_array(rng: &mut ThreadRng) -> StringArray {
generate_pattern_array(rng, pick_date_pattern)
}

fn generate_datetime_pattern_array(rng: &mut ThreadRng) -> StringArray {
generate_pattern_array(rng, pick_date_time_pattern)
}

fn generate_mixed_pattern_array(rng: &mut ThreadRng) -> StringArray {
generate_pattern_array(rng, pick_date_and_date_time_mixed_pattern)
}

fn criterion_benchmark(c: &mut Criterion) {
let config_options = Arc::new(ConfigOptions::default());

c.bench_function("to_char_array_array_1000", |b| {
c.bench_function("to_char_array_date_only_patterns_1000", |b| {
let mut rng = rand::rng();
let data_arr = generate_date32_array(&mut rng);
let batch_len = data_arr.len();
let data = ColumnarValue::Array(Arc::new(data_arr) as ArrayRef);
let patterns = ColumnarValue::Array(Arc::new(generate_date_pattern_array(
&mut rng,
)) as ArrayRef);

b.iter(|| {
black_box(
to_char()
.invoke_with_args(ScalarFunctionArgs {
args: vec![data.clone(), patterns.clone()],
arg_fields: vec![
Field::new("a", data.data_type(), true).into(),
Field::new("b", patterns.data_type(), true).into(),
],
number_rows: batch_len,
return_field: Field::new("f", DataType::Utf8, true).into(),
config_options: Arc::clone(&config_options),
})
.expect("to_char should work on valid values"),
)
})
});

c.bench_function("to_char_array_datetime_patterns_1000", |b| {
let mut rng = rand::rng();
let data_arr = generate_date32_array(&mut rng);
let batch_len = data_arr.len();
let data = ColumnarValue::Array(Arc::new(data_arr) as ArrayRef);
let patterns = ColumnarValue::Array(Arc::new(generate_datetime_pattern_array(
&mut rng,
)) as ArrayRef);

b.iter(|| {
black_box(
to_char()
.invoke_with_args(ScalarFunctionArgs {
args: vec![data.clone(), patterns.clone()],
arg_fields: vec![
Field::new("a", data.data_type(), true).into(),
Field::new("b", patterns.data_type(), true).into(),
],
number_rows: batch_len,
return_field: Field::new("f", DataType::Utf8, true).into(),
config_options: Arc::clone(&config_options),
})
.expect("to_char should work on valid values"),
)
})
});

c.bench_function("to_char_array_mixed_patterns_1000", |b| {
let mut rng = rand::rng();
let data_arr = data(&mut rng);
let data_arr = generate_date32_array(&mut rng);
let batch_len = data_arr.len();
let data = ColumnarValue::Array(Arc::new(data_arr) as ArrayRef);
let patterns = ColumnarValue::Array(Arc::new(patterns(&mut rng)) as ArrayRef);
let patterns = ColumnarValue::Array(Arc::new(generate_mixed_pattern_array(
&mut rng,
)) as ArrayRef);

b.iter(|| {
black_box(
Expand All @@ -108,13 +208,13 @@ fn criterion_benchmark(c: &mut Criterion) {
})
});

c.bench_function("to_char_array_scalar_1000", |b| {
c.bench_function("to_char_scalar_date_only_pattern_1000", |b| {
let mut rng = rand::rng();
let data_arr = data(&mut rng);
let data_arr = generate_date32_array(&mut rng);
let batch_len = data_arr.len();
let data = ColumnarValue::Array(Arc::new(data_arr) as ArrayRef);
let patterns =
ColumnarValue::Scalar(ScalarValue::Utf8(Some("%Y-%m-%d".to_string())));
ColumnarValue::Scalar(ScalarValue::Utf8(Some(pick_date_pattern(&mut rng))));

b.iter(|| {
black_box(
Expand All @@ -134,7 +234,35 @@ fn criterion_benchmark(c: &mut Criterion) {
})
});

c.bench_function("to_char_scalar_scalar_1000", |b| {
c.bench_function("to_char_scalar_datetime_pattern_1000", |b| {
let mut rng = rand::rng();
let data_arr = generate_date32_array(&mut rng);
let batch_len = data_arr.len();
let data = ColumnarValue::Array(Arc::new(data_arr) as ArrayRef);
let patterns = ColumnarValue::Scalar(ScalarValue::Utf8(Some(
pick_date_time_pattern(&mut rng),
)));

b.iter(|| {
black_box(
to_char()
.invoke_with_args(ScalarFunctionArgs {
args: vec![data.clone(), patterns.clone()],
arg_fields: vec![
Field::new("a", data.data_type(), true).into(),
Field::new("b", patterns.data_type(), true).into(),
],
number_rows: batch_len,
return_field: Field::new("f", DataType::Utf8, true).into(),
config_options: Arc::clone(&config_options),
})
.expect("to_char should work on valid values"),
)
})
});

c.bench_function("to_char_scalar_1000", |b| {
let mut rng = rand::rng();
let timestamp = "2026-07-08T09:10:11"
.parse::<NaiveDateTime>()
.unwrap()
Expand All @@ -144,9 +272,8 @@ fn criterion_benchmark(c: &mut Criterion) {
.timestamp_nanos_opt()
.unwrap();
let data = ColumnarValue::Scalar(TimestampNanosecond(Some(timestamp), None));
let pattern = ColumnarValue::Scalar(ScalarValue::Utf8(Some(
"%d-%m-%Y %H:%M:%S".to_string(),
)));
let pattern =
ColumnarValue::Scalar(ScalarValue::Utf8(Some(pick_date_pattern(&mut rng))));

b.iter(|| {
black_box(
Expand Down
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