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5 changes: 5 additions & 0 deletions datafusion/core/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -241,6 +241,11 @@ harness = false
name = "parquet_query_sql"
required-features = ["parquet"]
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Is there any reason not to just add the benchmarks to parquet_query_sql?

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I could but it’s kind of nice to be able to run them in isolation easily at least for now while we’re developing just these. And in some sense the feature we’re working on needn’t be parquet specific (eg Vortex). We can always fold them later.


[[bench]]
harness = false
name = "parquet_struct_query"
required-features = ["parquet"]

[[bench]]
harness = false
name = "range_and_generate_series"
Expand Down
312 changes: 312 additions & 0 deletions datafusion/core/benches/parquet_struct_query.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,312 @@
// 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 of SQL queries on struct columns in parquet data

use arrow::array::{ArrayRef, Int32Array, StringArray, StructArray};
use arrow::datatypes::{DataType, Field, Fields, Schema, SchemaRef};
use arrow::record_batch::RecordBatch;
use criterion::{Criterion, criterion_group, criterion_main};
use datafusion::prelude::SessionContext;
use datafusion_common::instant::Instant;
use parquet::arrow::ArrowWriter;
use parquet::file::properties::{WriterProperties, WriterVersion};
use rand::distr::Alphanumeric;
use rand::prelude::*;
use rand::rng;
use std::hint::black_box;
use std::ops::Range;
use std::path::Path;
use std::sync::Arc;
use tempfile::NamedTempFile;
use tokio::runtime::Runtime;

/// The number of batches to write
const NUM_BATCHES: usize = 128;
/// The number of rows in each record batch to write
const WRITE_RECORD_BATCH_SIZE: usize = 4096;
/// The number of rows in a row group
const ROW_GROUP_SIZE: usize = 65536;
/// The number of row groups expected
const EXPECTED_ROW_GROUPS: usize = 8;
/// The range for random string lengths
const STRING_LENGTH_RANGE: Range<usize> = 50..200;

fn schema() -> SchemaRef {
let struct_fields = Fields::from(vec![
Field::new("id", DataType::Int32, false),
Field::new("value", DataType::Utf8, false),
]);
let struct_type = DataType::Struct(struct_fields);

Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("s", struct_type, false),
]))
}

fn generate_strings(len: usize) -> ArrayRef {
let mut rng = rng();
Arc::new(StringArray::from_iter((0..len).map(|_| {
let string_len = rng.random_range(STRING_LENGTH_RANGE.clone());
Some(
(0..string_len)
.map(|_| char::from(rng.sample(Alphanumeric)))
.collect::<String>(),
)
})))
}

fn generate_batch(batch_id: usize) -> RecordBatch {
let schema = schema();
let len = WRITE_RECORD_BATCH_SIZE;

// Generate sequential IDs based on batch_id for uniqueness
let base_id = (batch_id * len) as i32;
let id_values: Vec<i32> = (0..len).map(|i| base_id + i as i32).collect();
let id_array = Arc::new(Int32Array::from(id_values.clone()));

// Create struct id array (matching top-level id)
let struct_id_array = Arc::new(Int32Array::from(id_values));

// Generate random strings for struct value field
let value_array = generate_strings(len);

// Construct StructArray
let struct_array = StructArray::from(vec![
(
Arc::new(Field::new("id", DataType::Int32, false)),
struct_id_array as ArrayRef,
),
(
Arc::new(Field::new("value", DataType::Utf8, false)),
value_array,
),
]);

RecordBatch::try_new(schema, vec![id_array, Arc::new(struct_array)]).unwrap()
}

fn generate_file() -> NamedTempFile {
let now = Instant::now();
let mut named_file = tempfile::Builder::new()
.prefix("parquet_struct_query")
.suffix(".parquet")
.tempfile()
.unwrap();

println!("Generating parquet file - {}", named_file.path().display());
let schema = schema();

let properties = WriterProperties::builder()
.set_writer_version(WriterVersion::PARQUET_2_0)
.set_max_row_group_size(ROW_GROUP_SIZE)
.build();

let mut writer =
ArrowWriter::try_new(&mut named_file, schema, Some(properties)).unwrap();

for batch_id in 0..NUM_BATCHES {
let batch = generate_batch(batch_id);
writer.write(&batch).unwrap();
}

let metadata = writer.close().unwrap();
let file_metadata = metadata.file_metadata();
let expected_rows = WRITE_RECORD_BATCH_SIZE * NUM_BATCHES;
assert_eq!(
file_metadata.num_rows() as usize,
expected_rows,
"Expected {} rows but got {}",
expected_rows,
file_metadata.num_rows()
);
assert_eq!(
metadata.row_groups().len(),
EXPECTED_ROW_GROUPS,
"Expected {} row groups but got {}",
EXPECTED_ROW_GROUPS,
metadata.row_groups().len()
);

println!(
"Generated parquet file with {} rows and {} row groups in {} seconds",
file_metadata.num_rows(),
metadata.row_groups().len(),
now.elapsed().as_secs_f32()
);

named_file
}

fn create_context(file_path: &str) -> SessionContext {
let ctx = SessionContext::new();
let rt = Runtime::new().unwrap();
rt.block_on(ctx.register_parquet("t", file_path, Default::default()))
.unwrap();
ctx
}

fn query(ctx: &SessionContext, rt: &Runtime, sql: &str) {
let ctx = ctx.clone();
let sql = sql.to_string();
let df = rt.block_on(ctx.sql(&sql)).unwrap();
black_box(rt.block_on(df.collect()).unwrap());
}

fn criterion_benchmark(c: &mut Criterion) {
let (file_path, temp_file) = match std::env::var("PARQUET_FILE") {
Ok(file) => (file, None),
Err(_) => {
let temp_file = generate_file();
(temp_file.path().display().to_string(), Some(temp_file))
}
};

assert!(Path::new(&file_path).exists(), "path not found");
println!("Using parquet file {file_path}");

let ctx = create_context(&file_path);
let rt = Runtime::new().unwrap();

// Basic struct access
c.bench_function("struct_access", |b| {
b.iter(|| query(&ctx, &rt, "select id, s['id'] from t"))
});

// Filter queries
c.bench_function("filter_struct_field_eq", |b| {
b.iter(|| query(&ctx, &rt, "select id from t where s['id'] = 5"))
});

c.bench_function("filter_struct_field_with_select", |b| {
b.iter(|| query(&ctx, &rt, "select id, s['id'] from t where s['id'] = 5"))
});

c.bench_function("filter_top_level_with_struct_select", |b| {
b.iter(|| query(&ctx, &rt, "select s['id'] from t where id = 5"))
});

c.bench_function("filter_struct_string_length", |b| {
b.iter(|| query(&ctx, &rt, "select id from t where length(s['value']) > 100"))
});

c.bench_function("filter_struct_range", |b| {
b.iter(|| {
query(
&ctx,
&rt,
"select id from t where s['id'] > 100 and s['id'] < 200",
)
})
});

// Join queries (limited with WHERE id < 1000 for performance)
c.bench_function("join_struct_to_struct", |b| {
b.iter(|| query(
&ctx,
&rt,
"select t1.id from t t1 join t t2 on t1.s['id'] = t2.s['id'] where t1.id < 1000"
))
});

c.bench_function("join_struct_to_toplevel", |b| {
b.iter(|| query(
&ctx,
&rt,
"select t1.id from t t1 join t t2 on t1.s['id'] = t2.id where t1.id < 1000"
))
});

c.bench_function("join_toplevel_to_struct", |b| {
b.iter(|| query(
&ctx,
&rt,
"select t1.id from t t1 join t t2 on t1.id = t2.s['id'] where t1.id < 1000"
))
});

c.bench_function("join_struct_to_struct_with_top_level", |b| {
b.iter(|| query(
&ctx,
&rt,
"select t1.id from t t1 join t t2 on t1.s['id'] = t2.s['id'] and t1.id = t2.id where t1.id < 1000"
))
});

c.bench_function("join_struct_and_struct_value", |b| {
b.iter(|| query(
&ctx,
&rt,
"select t1.s['id'], t2.s['value'] from t t1 join t t2 on t1.id = t2.id where t1.id < 1000"
))
});

// Group by queries
c.bench_function("group_by_struct_field", |b| {
b.iter(|| query(&ctx, &rt, "select s['id'] from t group by s['id']"))
});

c.bench_function("group_by_struct_select_toplevel", |b| {
b.iter(|| query(&ctx, &rt, "select max(id) from t group by s['id']"))
});

c.bench_function("group_by_toplevel_select_struct", |b| {
b.iter(|| query(&ctx, &rt, "select max(s['id']) from t group by id"))
});

c.bench_function("group_by_struct_with_count", |b| {
b.iter(|| {
query(
&ctx,
&rt,
"select s['id'], count(*) from t group by s['id']",
)
})
});

c.bench_function("group_by_multiple_with_count", |b| {
b.iter(|| {
query(
&ctx,
&rt,
"select id, s['id'], count(*) from t group by id, s['id']",
)
})
});

// Additional queries
c.bench_function("order_by_struct_limit", |b| {
b.iter(|| {
query(
&ctx,
&rt,
"select id, s['id'] from t order by s['id'] limit 1000",
)
})
});

c.bench_function("distinct_struct_field", |b| {
b.iter(|| query(&ctx, &rt, "select distinct s['id'] from t"))
});

// Temporary file must outlive the benchmarks, it is deleted when dropped
drop(temp_file);
}

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