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5 changes: 5 additions & 0 deletions datafusion/functions/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -306,6 +306,11 @@ harness = false
name = "find_in_set"
required-features = ["unicode_expressions"]

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

[[bench]]
harness = false
name = "contains"
Expand Down
98 changes: 98 additions & 0 deletions datafusion/functions/benches/find_in_set_literal.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,98 @@
// 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.

//! Benchmarks the `find_in_set(column, constant_list)` path where the set is a
//! scalar literal. A long list exercises the pre-built lookup; a short list
//! stays on the per-row linear scan.

use arrow::array::StringArray;
use arrow::datatypes::{DataType, Field};
use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
use datafusion_common::ScalarValue;
use datafusion_common::config::ConfigOptions;
use datafusion_expr::{ColumnarValue, ScalarFunctionArgs};
use rand::prelude::StdRng;
use rand::{Rng, SeedableRng};
use std::hint::black_box;
use std::sync::Arc;

const N_ROWS: usize = 8192;

/// Builds a string column whose values are drawn from `entries` plus a small
/// fraction of misses, so both hits and misses are exercised.
fn build_column(entries: &[String]) -> StringArray {
let mut rng = StdRng::seed_from_u64(42);
let values: Vec<Option<String>> = (0..N_ROWS)
.map(|_| {
let r = rng.random::<f32>();
if r < 0.1 {
None
} else if r < 0.4 {
Some("__miss__".to_string())
} else {
let idx = rng.random_range(0..entries.len());
Some(entries[idx].clone())
}
})
.collect();
StringArray::from(values)
}

fn bench_case(c: &mut Criterion, label: &str, num_entries: usize) {
let find_in_set = datafusion_functions::unicode::find_in_set();
let entries: Vec<String> = (0..num_entries).map(|i| format!("item{i}")).collect();
let list = entries.join(",");

let column = build_column(&entries);
let args = vec![
ColumnarValue::Array(Arc::new(column)),
ColumnarValue::Scalar(ScalarValue::Utf8(Some(list))),
];
let arg_fields = args
.iter()
.map(|arg| Field::new("a", arg.data_type().clone(), true).into())
.collect::<Vec<_>>();
let return_field = Arc::new(Field::new("f", DataType::Int32, true));
let config_options = Arc::new(ConfigOptions::default());

c.bench_with_input(
BenchmarkId::new("find_in_set_literal", label),
&num_entries,
|b, _| {
b.iter(|| {
black_box(find_in_set.invoke_with_args(ScalarFunctionArgs {
args: args.clone(),
arg_fields: arg_fields.clone(),
number_rows: N_ROWS,
return_field: Arc::clone(&return_field),
config_options: Arc::clone(&config_options),
}))
})
},
);
}

fn criterion_benchmark(c: &mut Criterion) {
// Short list stays on the linear scan (below the lookup threshold).
bench_case(c, "short_list_4", 4);
// Long lists exercise the pre-built lookup.
bench_case(c, "long_list_64", 64);
bench_case(c, "long_list_256", 256);
}

criterion_group!(benches, criterion_benchmark);
criterion_main!(benches);
75 changes: 70 additions & 5 deletions datafusion/functions/src/unicode/find_in_set.rs
Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ use arrow_buffer::NullBuffer;

use crate::utils::utf8_to_int_type;
use datafusion_common::{
Result, ScalarValue, exec_err, internal_err, utils::take_function_args,
HashMap, Result, ScalarValue, exec_err, internal_err, utils::take_function_args,
};
use datafusion_expr::TypeSignature::Exact;
use datafusion_expr::{
Expand Down Expand Up @@ -316,6 +316,11 @@ where
Ok(Arc::new(PrimitiveArray::<T>::new(values.into(), nulls)) as ArrayRef)
}

/// Minimum set length at which a pre-built lookup beats a per-row linear scan.
/// Below this, the linear scan's small constant factor wins, so short sets are
/// left untouched to avoid regressing them.
const FIND_IN_SET_LOOKUP_THRESHOLD: usize = 16;

fn find_in_set_right_literal<'a, T, V>(
string_array: V,
str_list: &[&str],
Expand All @@ -329,16 +334,34 @@ where
let nulls = string_array.nulls().cloned();
let zero = T::Native::from_usize(0).unwrap();

// The set (`str_list`) is constant across all rows. For a large set, the
// per-row `position` linear scan is O(set_len). Building a lookup from each
// distinct entry to its 1-based position once turns each row into an O(1)
// probe (first occurrence wins, exactly matching `position`). Below the
// threshold the linear scan's small constant factor is faster, so the map is
// built at most once here rather than per row.
let map: Option<HashMap<&str, usize>> =
(str_list.len() >= FIND_IN_SET_LOOKUP_THRESHOLD).then(|| {
let mut map = HashMap::with_capacity(str_list.len());

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This map is reconstructed for each batch being processed. Would be better to reuse across batches.

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I looked into this, and it doesn't seem like it would improve performance much, and would be a significant change.

for (idx, entry) in str_list.iter().enumerate() {
map.entry(*entry).or_insert(idx + 1);
}
map
});

let values: Vec<T::Native> = (0..len)
.map(|i| {
if nulls.as_ref().is_some_and(|n| n.is_null(i)) {
return zero;
}
let string = string_array.value(i);
let position = str_list
.iter()
.position(|s| *s == string)
.map_or(0, |idx| idx + 1);
let position = match &map {
Some(map) => map.get(string).copied().unwrap_or(0),
None => str_list
.iter()
.position(|s| *s == string)
.map_or(0, |idx| idx + 1),
};
T::Native::from_usize(position).unwrap()
})
.collect();
Expand Down Expand Up @@ -545,4 +568,46 @@ mod tests {
],
Int32Array::from(vec![None::<i32>; 3])
);

// Exercises both the lookup-map path (list length >= threshold) and the
// linear-scan path (short list), including a duplicate entry to confirm the
// first occurrence wins in both.
#[test]
fn test_right_literal_lookup_matches_linear() {
use super::find_in_set_right_literal;
use arrow::datatypes::Int32Type;

// 40 unique entries plus a duplicate of "item5" appended at index 40, so
// the length is well over FIND_IN_SET_LOOKUP_THRESHOLD.
let mut long_list: Vec<String> = (0..40).map(|i| format!("item{i}")).collect();
long_list.push("item5".to_string());
let long_refs: Vec<&str> = long_list.iter().map(|s| s.as_str()).collect();
let short_refs = ["a", "b", "c"];

let strings = StringArray::from(vec![
Some("item0"),
Some("item39"),
Some("item5"),
Some("missing"),
None,
Some("b"),
]);

let long =
find_in_set_right_literal::<Int32Type, _>(&strings, &long_refs).unwrap();
let long = long.as_any().downcast_ref::<Int32Array>().unwrap();
assert_eq!(long.value(0), 1);
assert_eq!(long.value(1), 40);
assert_eq!(long.value(2), 6); // first occurrence of "item5"
assert_eq!(long.value(3), 0);
assert!(long.is_null(4));
assert_eq!(long.value(5), 0);

let short =
find_in_set_right_literal::<Int32Type, _>(&strings, &short_refs).unwrap();
let short = short.as_any().downcast_ref::<Int32Array>().unwrap();
assert_eq!(short.value(0), 0);
assert!(short.is_null(4));
assert_eq!(short.value(5), 2); // "b" at position 2
}
}
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