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4 changes: 4 additions & 0 deletions datafusion/functions-aggregate/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -66,3 +66,7 @@ harness = false
[[bench]]
name = "sum"
harness = false

[[bench]]
name = "array_agg"
harness = false
186 changes: 186 additions & 0 deletions datafusion/functions-aggregate/benches/array_agg.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,186 @@
// 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 std::sync::Arc;

use arrow::array::{Array, ArrayRef, ArrowPrimitiveType, AsArray, ListArray};
use arrow::datatypes::Int64Type;
use arrow::util::bench_util::create_primitive_array;
use arrow_schema::Field;
use criterion::{black_box, criterion_group, criterion_main, Criterion};
use datafusion_expr::Accumulator;
use datafusion_functions_aggregate::array_agg::ArrayAggAccumulator;

use arrow::util::test_util::seedable_rng;
use arrow_buffer::{NullBufferBuilder, OffsetBuffer};
use rand::distributions::{Distribution, Standard};
use rand::Rng;

fn merge_batch_bench(c: &mut Criterion, name: &str, values: ArrayRef) {
let list_item_data_type = values.as_list::<i32>().values().data_type().clone();
c.bench_function(name, |b| {
b.iter(|| {
#[allow(clippy::unit_arg)]
black_box(
ArrayAggAccumulator::try_new(&list_item_data_type)
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As written this will create a new ArrayAggAccumulator on each iteration -- it might be more representative if the creation wasn't part of the measurement (aka create the accumulator outside b.iter() 🤔 )

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@rluvaton rluvaton Jan 26, 2025

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I know, but the otherwise this will add to the same local state and is not what is being tested, also creating is almost 0 cost

.unwrap()
.merge_batch(&[values.clone()])
.unwrap(),
)
})
});
}

/// Create List array with the given item data type, null density, null locations and zero length lists density
/// Creates an random (but fixed-seeded) array of a given size and null density
pub fn create_list_array<T>(
size: usize,
null_density: f32,
zero_length_lists_probability: f32,
) -> ListArray
where
T: ArrowPrimitiveType,
Standard: Distribution<T::Native>,
{
let mut nulls_builder = NullBufferBuilder::new(size);
let mut rng = seedable_rng();

let offsets = OffsetBuffer::from_lengths((0..size).map(|_| {
let is_null = rng.gen::<f32>() < null_density;

let mut length = rng.gen_range(1..10);

if is_null {
nulls_builder.append_null();

if rng.gen::<f32>() <= zero_length_lists_probability {
length = 0;
}
} else {
nulls_builder.append_non_null();
}

length
}));

let length = *offsets.last().unwrap() as usize;

let values = create_primitive_array::<T>(length, 0.0);

let field = Field::new_list_field(T::DATA_TYPE, true);

ListArray::new(
Arc::new(field),
offsets,
Arc::new(values),
nulls_builder.finish(),
)
}

fn array_agg_benchmark(c: &mut Criterion) {
let values = Arc::new(create_list_array::<Int64Type>(8192, 0.0, 1.0)) as ArrayRef;
merge_batch_bench(c, "array_agg i64 merge_batch no nulls", values);

let values = Arc::new(create_list_array::<Int64Type>(8192, 1.0, 1.0)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch all nulls, 100% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 1.0, 0.9)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch all nulls, 90% of nulls point to a zero length array",
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this comment says 90 but the function call is create_list_array::<Int64Type>(8192, 1.0, 0.1) (which is 100 right?)

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Or is the idea that 10% nulls point at a non zero length array 🤔

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all null because null density (2nd arg) is 1.0, and 90% of nulls point to a zero length array, because the 3rd argument is the probability for non-zero length so it's 10% and 100 - 10 is 90% hence the 90% of nulls

I'll rename the argument in the function to be probability for zero length array

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Thanks -- that makes a lot more sense to me and I found it easier to understand. 🙏

values,
);

// All nulls point to a 0 length array

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.3, 1.0)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 30% nulls, 100% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.7, 1.0)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 70% nulls, 100% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.3, 0.99)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 30% nulls, 99% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.7, 0.99)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 70% nulls, 99% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.3, 0.9)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 30% nulls, 90% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.7, 0.9)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 70% nulls, 90% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.3, 0.50)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 30% nulls, 50% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.7, 0.50)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 70% nulls, 50% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.3, 0.0)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 30% nulls, 0% of nulls point to a zero length array",
values,
);

let values = Arc::new(create_list_array::<Int64Type>(8192, 0.7, 0.0)) as ArrayRef;
merge_batch_bench(
c,
"array_agg i64 merge_batch 70% nulls, 0% of nulls point to a zero length array",
values,
);
}

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