perf: Optimize array_position for scalar needle

datafusion/functions-nested/Cargo.toml

@@ -96,3 +96,7 @@ name = "array_repeat"
 [[bench]]
 harness = false
 name = "array_set_ops"
+
+[[bench]]
+harness = false
+name = "array_position"

datafusion/functions-nested/benches/array_position.rs

@@ -0,0 +1,237 @@
+// 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::{ArrayRef, Int64Array, ListArray};
+use arrow::buffer::OffsetBuffer;
+use arrow::datatypes::{DataType, Field};
+use criterion::{
+    criterion_group, criterion_main, {BenchmarkId, Criterion},
+};
+use datafusion_common::ScalarValue;
+use datafusion_common::config::ConfigOptions;
+use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl};
+use datafusion_functions_nested::position::ArrayPosition;
+use rand::Rng;
+use rand::SeedableRng;
+use rand::rngs::StdRng;
+use std::hint::black_box;
+use std::sync::Arc;
+
+const NUM_ROWS: usize = 10000;
+const SEED: u64 = 42;
+const NULL_DENSITY: f64 = 0.1;
+const SENTINEL_NEEDLE: i64 = -1;
+
+fn criterion_benchmark(c: &mut Criterion) {
+    for size in [10, 100, 500] {
+        bench_array_position(c, size);
+    }
+}
+
+fn bench_array_position(c: &mut Criterion, array_size: usize) {
+    let mut group = c.benchmark_group("array_position_i64");
+    let haystack_found_once = create_haystack_with_sentinel(
+        NUM_ROWS,
+        array_size,
+        NULL_DENSITY,
+        SENTINEL_NEEDLE,
+        0,
+    );
+    let haystack_found_many = create_haystack_with_sentinels(
+        NUM_ROWS,
+        array_size,
+        NULL_DENSITY,
+        SENTINEL_NEEDLE,
+    );
+    let haystack_not_found =
+        create_haystack_without_sentinel(NUM_ROWS, array_size, NULL_DENSITY);
+    let num_rows = haystack_not_found.len();
+    let arg_fields: Vec<Arc<Field>> = vec![
+        Field::new("haystack", haystack_not_found.data_type().clone(), false).into(),
+        Field::new("needle", DataType::Int64, false).into(),
+    ];
+    let return_field: Arc<Field> = Field::new("result", DataType::UInt64, true).into();
+    let config_options = Arc::new(ConfigOptions::default());
+    let needle = ScalarValue::Int64(Some(SENTINEL_NEEDLE));
+
+    // Benchmark: one match per row.
+    let args_found_once = vec![
+        ColumnarValue::Array(haystack_found_once.clone()),
+        ColumnarValue::Scalar(needle.clone()),
+    ];
+    group.bench_with_input(
+        BenchmarkId::new("found_once", array_size),
+        &array_size,
+        |b, _| {
+            let udf = ArrayPosition::new();
+            b.iter(|| {
+                black_box(
+                    udf.invoke_with_args(ScalarFunctionArgs {
+                        args: args_found_once.clone(),
+                        arg_fields: arg_fields.clone(),
+                        number_rows: num_rows,
+                        return_field: return_field.clone(),
+                        config_options: config_options.clone(),
+                    })
+                    .unwrap(),
+                )
+            })
+        },
+    );
+
+    // Benchmark: many matches per row.
+    let args_found_many = vec![
+        ColumnarValue::Array(haystack_found_many.clone()),
+        ColumnarValue::Scalar(needle.clone()),
+    ];
+    group.bench_with_input(
+        BenchmarkId::new("found_many", array_size),
+        &array_size,
+        |b, _| {
+            let udf = ArrayPosition::new();
+            b.iter(|| {
+                black_box(
+                    udf.invoke_with_args(ScalarFunctionArgs {
+                        args: args_found_many.clone(),
+                        arg_fields: arg_fields.clone(),
+                        number_rows: num_rows,
+                        return_field: return_field.clone(),
+                        config_options: config_options.clone(),
+                    })
+                    .unwrap(),
+                )
+            })
+        },
+    );
+
+    // Benchmark: needle is not found in any row.
+    let args_not_found = vec![
+        ColumnarValue::Array(haystack_not_found.clone()),
+        ColumnarValue::Scalar(needle.clone()),
+    ];
+    group.bench_with_input(
+        BenchmarkId::new("not_found", array_size),
+        &array_size,
+        |b, _| {
+            let udf = ArrayPosition::new();
+            b.iter(|| {
+                black_box(
+                    udf.invoke_with_args(ScalarFunctionArgs {
+                        args: args_not_found.clone(),
+                        arg_fields: arg_fields.clone(),
+                        number_rows: num_rows,
+                        return_field: return_field.clone(),
+                        config_options: config_options.clone(),
+                    })
+                    .unwrap(),
+                )
+            })
+        },
+    );
+
+    group.finish();
+}
+
+fn create_haystack_without_sentinel(
+    num_rows: usize,
+    array_size: usize,
+    null_density: f64,
+) -> ArrayRef {
+    create_haystack_from_fn(num_rows, array_size, |_, _, rng| {
+        random_haystack_value(rng, array_size, null_density)
+    })
+}
+
+fn create_haystack_with_sentinel(
+    num_rows: usize,
+    array_size: usize,
+    null_density: f64,
+    sentinel: i64,
+    sentinel_index: usize,
+) -> ArrayRef {
+    assert!(sentinel_index < array_size);
+
+    create_haystack_from_fn(num_rows, array_size, |_, col, rng| {
+        if col == sentinel_index {
+            Some(sentinel)
+        } else {
+            random_haystack_value(rng, array_size, null_density)
+        }
+    })
+}
+
+fn create_haystack_with_sentinels(
+    num_rows: usize,
+    array_size: usize,
+    null_density: f64,
+    sentinel: i64,
+) -> ArrayRef {
+    create_haystack_from_fn(num_rows, array_size, |_, col, rng| {
+        // Place the sentinel in half the positions to create many matches per row.
+        if col % 2 == 0 {
+            Some(sentinel)
+        } else {
+            random_haystack_value(rng, array_size, null_density)
+        }
+    })
+}
+
+fn create_haystack_from_fn<F>(
+    num_rows: usize,
+    array_size: usize,
+    mut value_at: F,
+) -> ArrayRef
+where
+    F: FnMut(usize, usize, &mut StdRng) -> Option<i64>,
+{
+    let mut rng = StdRng::seed_from_u64(SEED);
+    let mut values = Vec::with_capacity(num_rows * array_size);
+    for row in 0..num_rows {
+        for col in 0..array_size {
+            values.push(value_at(row, col, &mut rng));
+        }
+    }
+    let values = values.into_iter().collect::<Int64Array>();
+    let offsets = (0..=num_rows)
+        .map(|i| (i * array_size) as i32)
+        .collect::<Vec<i32>>();
+
+    Arc::new(
+        ListArray::try_new(
+            Arc::new(Field::new("item", DataType::Int64, true)),
+            OffsetBuffer::new(offsets.into()),
+            Arc::new(values),
+            None,
+        )
+        .unwrap(),
+    )
+}
+
+fn random_haystack_value(
+    rng: &mut StdRng,
+    array_size: usize,
+    null_density: f64,
+) -> Option<i64> {
+    if rng.random::<f64>() < null_density {
+        None
+    } else {
+        Some(rng.random_range(0..array_size as i64))
+    }
+}
+
+criterion_group!(benches, criterion_benchmark);
+criterion_main!(benches);