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4 changes: 4 additions & 0 deletions datafusion/common/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,10 @@ sql = ["sqlparser"]
harness = false
name = "with_hashes"

[[bench]]
harness = false
name = "scalar_to_array"

[dependencies]
ahash = { workspace = true }
apache-avro = { workspace = true, features = [
Expand Down
107 changes: 107 additions & 0 deletions datafusion/common/benches/scalar_to_array.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,107 @@
// 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 for `ScalarValue::to_array_of_size`, focusing on List
//! scalars.
use arrow::array::{Array, ArrayRef, AsArray, StringViewBuilder};
use arrow::datatypes::{DataType, Field};
use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
use datafusion_common::ScalarValue;
use datafusion_common::utils::SingleRowListArrayBuilder;
use std::sync::Arc;

/// Build a `ScalarValue::List` of `num_elements` Utf8View strings whose
/// inner StringViewArray has `num_buffers` data buffers.
fn make_list_scalar(num_elements: usize, num_buffers: usize) -> ScalarValue {
let elements_per_buffer = num_elements.div_ceil(num_buffers);

let mut small_arrays: Vec<ArrayRef> = Vec::new();
let mut remaining = num_elements;
for buf_idx in 0..num_buffers {
let count = remaining.min(elements_per_buffer);
if count == 0 {
break;
}
let start = buf_idx * elements_per_buffer;
let mut builder = StringViewBuilder::with_capacity(count);
for i in start..start + count {
builder.append_value(format!("{i:024x}"));
}
small_arrays.push(Arc::new(builder.finish()) as ArrayRef);
remaining -= count;
}

let refs: Vec<&dyn Array> = small_arrays.iter().map(|a| a.as_ref()).collect();
let concated = arrow::compute::concat(&refs).unwrap();

let list_array = SingleRowListArrayBuilder::new(concated)
.with_field(&Field::new_list_field(DataType::Utf8View, true))
.build_list_array();
ScalarValue::List(Arc::new(list_array))
}

/// We want to measure the cost of doing the conversion and then also accessing
/// the results, to model what would happen during query evaluation.
fn consume_list_array(arr: &ArrayRef) {
let list_arr = arr.as_list::<i32>();
let mut total_len: usize = 0;
for i in 0..list_arr.len() {
let inner = list_arr.value(i);
let sv = inner.as_string_view();
for j in 0..sv.len() {
total_len += sv.value(j).len();
}
}
std::hint::black_box(total_len);
}

fn bench_list_to_array_of_size(c: &mut Criterion) {
let mut group = c.benchmark_group("list_to_array_of_size");

let num_elements = 1245;
let scalar_1buf = make_list_scalar(num_elements, 1);
let scalar_50buf = make_list_scalar(num_elements, 50);

for batch_size in [256, 1024] {
group.bench_with_input(
BenchmarkId::new("1_buffer", batch_size),
&batch_size,
|b, &sz| {
b.iter(|| {
let arr = scalar_1buf.to_array_of_size(sz).unwrap();
consume_list_array(&arr);
});
},
);
group.bench_with_input(
BenchmarkId::new("50_buffers", batch_size),
&batch_size,
|b, &sz| {
b.iter(|| {
let arr = scalar_50buf.to_array_of_size(sz).unwrap();
consume_list_array(&arr);
});
},
);
}

group.finish();
}

criterion_group!(benches, bench_list_to_array_of_size);
criterion_main!(benches);
88 changes: 81 additions & 7 deletions datafusion/common/src/scalar/mod.rs
Original file line number Diff line number Diff line change
Expand Up @@ -3008,7 +3008,7 @@ impl ScalarValue {
///
/// Errors if `self` is
/// - a decimal that fails be converted to a decimal array of size
/// - a `FixedsizeList` that fails to be concatenated into an array of size
/// - a `FixedSizeList` that fails to be concatenated into an array of size
/// - a `List` that fails to be concatenated into an array of size
/// - a `Dictionary` that fails be converted to a dictionary array of size
pub fn to_array_of_size(&self, size: usize) -> Result<ArrayRef> {
Expand Down Expand Up @@ -3435,12 +3435,13 @@ impl ScalarValue {
}

fn list_to_array_of_size(arr: &dyn Array, size: usize) -> Result<ArrayRef> {
let arrays = repeat_n(arr, size).collect::<Vec<_>>();
let ret = match !arrays.is_empty() {
true => arrow::compute::concat(arrays.as_slice())?,
false => arr.slice(0, 0),
};
Ok(ret)
if size == 0 {
return Ok(arr.slice(0, 0));
}

let n = arr.len() as u32;
let indices = UInt32Array::from_iter_values((0..size).flat_map(|_| 0..n));
Ok(arrow::compute::take(arr, &indices, None)?)
}

/// Retrieve ScalarValue for each row in `array`
Expand Down Expand Up @@ -5532,6 +5533,79 @@ mod tests {
assert_eq!(empty_array.len(), 0);
}

#[test]
fn test_to_array_of_size_list_size_one() {
// size=1 takes the fast path (Arc::clone)
let arr = ListArray::from_iter_primitive::<Int32Type, _, _>(vec![Some(vec![
Some(10),
Some(20),
])]);
let sv = ScalarValue::List(Arc::new(arr.clone()));
let result = sv.to_array_of_size(1).unwrap();
assert_eq!(result.as_list::<i32>(), &arr);
}

#[test]
fn test_to_array_of_size_list_empty_inner() {
// A list scalar containing an empty list: [[]]
let arr = ListArray::from_iter_primitive::<Int32Type, _, _>(vec![Some(vec![])]);
let sv = ScalarValue::List(Arc::new(arr));
let result = sv.to_array_of_size(3).unwrap();
let result_list = result.as_list::<i32>();
assert_eq!(result_list.len(), 3);
for i in 0..3 {
assert_eq!(result_list.value(i).len(), 0);
}
}

#[test]
fn test_to_array_of_size_large_list() {
let arr =
LargeListArray::from_iter_primitive::<Int32Type, _, _>(vec![Some(vec![
Some(100),
Some(200),
])]);
let sv = ScalarValue::LargeList(Arc::new(arr));
let result = sv.to_array_of_size(3).unwrap();
let expected = LargeListArray::from_iter_primitive::<Int32Type, _, _>(vec![
Some(vec![Some(100), Some(200)]),
Some(vec![Some(100), Some(200)]),
Some(vec![Some(100), Some(200)]),
]);
assert_eq!(result.as_list::<i64>(), &expected);
}

#[test]
fn test_list_to_array_of_size_multi_row() {
// Call list_to_array_of_size directly with arr.len() > 1
let arr = Int32Array::from(vec![Some(10), None, Some(30)]);
let result = ScalarValue::list_to_array_of_size(&arr, 3).unwrap();
let result = result.as_primitive::<Int32Type>();
assert_eq!(
result.iter().collect::<Vec<_>>(),
vec![
Some(10),
None,
Some(30),
Some(10),
None,
Some(30),
Some(10),
None,
Some(30),
]
);
}

#[test]
fn test_to_array_of_size_null_list() {
let dt = DataType::List(Arc::new(Field::new_list_field(DataType::Int32, true)));
let sv = ScalarValue::try_from(&dt).unwrap();
let result = sv.to_array_of_size(3).unwrap();
assert_eq!(result.len(), 3);
assert_eq!(result.null_count(), 3);
}

/// See https://github.com/apache/datafusion/issues/18870
#[test]
fn test_to_array_of_size_for_none_fsb() {
Expand Down