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new ea0da8b8fc Add benchmarks for dictionary path of new_group_values
(#22004)
ea0da8b8fc is described below
commit ea0da8b8fcfd1c77ed8343347b48b4e6053ae068
Author: RIchard Baah <[email protected]>
AuthorDate: Thu May 7 13:46:26 2026 -0400
Add benchmarks for dictionary path of new_group_values (#22004)
## Which issue does this PR close?
benchmarks for #21765. Also related to #21860
The goal is to merge this PR and then rebase the branch on #21765 to
contain these benchmarks, so that they can be run and compared to the
original.
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## Rationale for this change
Originally this was included in #21765 but that PR is already very
large. I decided to move it to its own separate PR
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in the issue then this section is not needed.
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## What changes are included in this PR?
Adds benchmarks for the dictionary encoding array path of
**new_group_values()**.
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is sometimes worth providing a summary of the individual changes in this
PR.
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## Are these changes tested?
n/a
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## Are there any user-facing changes?
no
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---------
Co-authored-by: Kumar Ujjawal <[email protected]>
---
datafusion/physical-plan/Cargo.toml | 4 +
.../benches/dictionary_group_values.rs | 176 +++++++++++++++++++++
2 files changed, 180 insertions(+)
diff --git a/datafusion/physical-plan/Cargo.toml
b/datafusion/physical-plan/Cargo.toml
index 7c52ee6e17..c671026277 100644
--- a/datafusion/physical-plan/Cargo.toml
+++ b/datafusion/physical-plan/Cargo.toml
@@ -112,3 +112,7 @@ required-features = ["test_utils"]
harness = false
name = "aggregate_vectorized"
required-features = ["test_utils"]
+
+[[bench]]
+harness = false
+name = "dictionary_group_values"
diff --git a/datafusion/physical-plan/benches/dictionary_group_values.rs
b/datafusion/physical-plan/benches/dictionary_group_values.rs
new file mode 100644
index 0000000000..ded52aebd1
--- /dev/null
+++ b/datafusion/physical-plan/benches/dictionary_group_values.rs
@@ -0,0 +1,176 @@
+// 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 `GroupValues` over a single `Dictionary<Int32, Utf8>`
+//! column. Each iteration measures `intern` (once or N times) followed by
+//! `emit(EmitTo::All)`. The `Box<dyn GroupValues>` returned by
+//! `new_group_values` is constructed in the setup closure of
+//! `iter_batched_ref` and is not included in the timing.
+
+use arrow::array::{ArrayRef, DictionaryArray, PrimitiveArray, StringArray};
+use arrow::buffer::{Buffer, NullBuffer};
+use arrow::datatypes::{DataType, Field, Int32Type, Schema, SchemaRef};
+use criterion::{
+ BatchSize, BenchmarkId, Criterion, Throughput, criterion_group,
criterion_main,
+};
+use datafusion_expr::EmitTo;
+use datafusion_physical_plan::aggregates::group_values::new_group_values;
+use datafusion_physical_plan::aggregates::order::GroupOrdering;
+use rand::rngs::StdRng;
+use rand::seq::SliceRandom;
+use rand::{Rng, SeedableRng};
+use std::hint::black_box;
+use std::sync::Arc;
+
+const SIZES: [usize; 2] = [8 * 1024, 64 * 1024];
+const CARDS_RELATIVE: [usize; 4] = [20, 75, 300, 1000];
+const N_BATCHES: usize = 4;
+// Fixed for reproducibility.
+const SEED: u64 = 0xD1C7;
+
+fn dict_schema() -> SchemaRef {
+ let dict_ty =
+ DataType::Dictionary(Box::new(DataType::Int32),
Box::new(DataType::Utf8));
+ Arc::new(Schema::new(vec![Field::new("g", dict_ty, true)]))
+}
+
+/// Build a `Dictionary<Int32, Utf8>` column.
+fn make_dict(size: usize, cardinality: usize, null_density: f32, seed: u64) ->
ArrayRef {
+ let strings: Vec<String> = (0..cardinality).map(|i|
format!("v_{i:08}")).collect();
+ let values = Arc::new(StringArray::from(
+ strings.iter().map(String::as_str).collect::<Vec<_>>(),
+ ));
+
+ let mut rng = StdRng::seed_from_u64(seed);
+ let keys: Vec<i32> = if cardinality == size {
+ let mut perm: Vec<i32> = (0..size as i32).collect();
+ perm.shuffle(&mut rng);
+ perm
+ } else {
+ (0..size)
+ .map(|_| rng.random_range(0..cardinality) as i32)
+ .collect()
+ };
+ let keys_buf = Buffer::from_slice_ref(&keys);
+
+ let nulls: Option<NullBuffer> = (null_density > 0.0).then(|| {
+ (0..size)
+ .map(|_| !rng.random_bool(null_density as f64))
+ .collect()
+ });
+
+ let key_array = PrimitiveArray::<Int32Type>::new(keys_buf.into(), nulls);
+ Arc::new(DictionaryArray::<Int32Type>::try_new(key_array, values).unwrap())
+}
+
+fn bench_id(
+ label: &str,
+ size: usize,
+ cardinality: usize,
+ null_density: f32,
+) -> BenchmarkId {
+ BenchmarkId::new(
+ label,
+ format!("size_{size}_card_{cardinality}_null_{null_density:.2}"),
+ )
+}
+
+fn bench_intern_emit(c: &mut Criterion) {
+ let mut group = c.benchmark_group("dict_intern_emit");
+ let schema = dict_schema();
+ let null_density = 0.0;
+
+ for &size in &SIZES {
+ let mut cards = CARDS_RELATIVE.to_vec();
+ cards.push(size); // all-unique stress case
+ for cardinality in cards {
+ let array = make_dict(size, cardinality, null_density, SEED);
+ group.throughput(Throughput::Elements(size as u64));
+ group.bench_function(
+ bench_id("intern_emit", size, cardinality, null_density),
+ |b| {
+ b.iter_batched_ref(
+ || {
+ (
+ new_group_values(schema.clone(),
&GroupOrdering::None)
+ .unwrap(),
+ Vec::<usize>::with_capacity(size),
+ )
+ },
+ |(gv, groups)| {
+ gv.intern(std::slice::from_ref(&array),
groups).unwrap();
+ black_box(&*groups);
+ black_box(gv.emit(EmitTo::All).unwrap());
+ },
+ BatchSize::SmallInput,
+ );
+ },
+ );
+ }
+ }
+ group.finish();
+}
+
+fn bench_repeated_intern_emit(c: &mut Criterion) {
+ let mut group = c.benchmark_group("dict_repeated_intern_emit");
+ let schema = dict_schema();
+ let null_density = 0.10;
+
+ for &size in &SIZES {
+ let mut cards = CARDS_RELATIVE.to_vec();
+ cards.push(size);
+ for cardinality in cards {
+ let batches: Vec<ArrayRef> = (0..N_BATCHES)
+ .map(|i| {
+ make_dict(
+ size,
+ cardinality,
+ null_density,
+ SEED.wrapping_add(i as u64),
+ )
+ })
+ .collect();
+ group.throughput(Throughput::Elements((size * N_BATCHES) as u64));
+ group.bench_function(
+ bench_id("repeated_intern_emit", size, cardinality,
null_density),
+ |b| {
+ b.iter_batched_ref(
+ || {
+ (
+ new_group_values(schema.clone(),
&GroupOrdering::None)
+ .unwrap(),
+ Vec::<usize>::with_capacity(size),
+ )
+ },
+ |(gv, groups)| {
+ for arr in &batches {
+ gv.intern(std::slice::from_ref(arr),
groups).unwrap();
+ black_box(&*groups);
+ }
+ black_box(gv.emit(EmitTo::All).unwrap());
+ },
+ BatchSize::SmallInput,
+ );
+ },
+ );
+ }
+ }
+ group.finish();
+}
+
+criterion_group!(benches, bench_intern_emit, bench_repeated_intern_emit);
+criterion_main!(benches);
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