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6 changes: 5 additions & 1 deletion benchmarks/Cargo.toml
Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ arrow = { workspace = true }
async-trait = "0.1"
bytes = { workspace = true }
clap = { version = "4.6.0", features = ["derive", "env", "string"] }
criterion = { workspace = true, features = ["html_reports"] }
criterion = { workspace = true, features = ["async_tokio", "html_reports"] }
datafusion = { workspace = true, default-features = true }
datafusion-common = { workspace = true, default-features = true }
datafusion-common-runtime = { workspace = true }
Expand All @@ -71,3 +71,7 @@ tempfile = { workspace = true }
[[bench]]
harness = false
name = "sql"

[[bench]]
harness = false
name = "parquet_pruning_setup_cache"
110 changes: 110 additions & 0 deletions benchmarks/benches/parquet_pruning_setup_cache.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,110 @@
// 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 end-to-end Parquet scan cost for a cache-favourable workload.
//!
//! The 128 files share one physical schema and use the same predicate and target

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what would happen if the schema is not the same? or schema is already merged?

@kosiew kosiew Aug 14, 2026

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what would happen if the schema is not the same?
Different physical file schemas produce distinct ParquetPruningSetupCache keys in #21566, so their setup is not reused across schema variants.

or schema is already merged?
Merged table schema is also not the targeted scenario in #21554.

This benchmark's purpose is to evaluate whether addressing #21554 improves performance: that issue targets avoiding repeated per-file schema adaptation, predicate rewrites, and pruning-predicate construction when many files have the same physical schema.

Schema evolution/merged-schema behavior is a separate workload and would dilute this focused benchmark.

Existing clickbench_partitioned benchmarks do not show significant improvement, I think because:

  • pruning setup work constitutes a small percentage of the work
  • the scenarios do not reuse cache

//! partition count, so pruning setup is reusable in a cache-enabled comparison
//! branch. The predicate matches every file, so each scan must adapt the
//! predicate and build (or reuse) pruning setup for all files.
//!
//! This is a focused baseline for comparing cache-disabled and cache-enabled
//! branches. It is not a general DataFusion benchmark and must not be
//! interpreted as a ClickBench performance result.

use std::{fs::File, sync::Arc};

use arrow::{
array::Int64Array,
datatypes::{DataType, Field, Schema},
record_batch::RecordBatch,
};
use criterion::{Criterion, criterion_group, criterion_main};
use datafusion::prelude::{SessionConfig, SessionContext};
use parquet::arrow::ArrowWriter;
use tempfile::TempDir;

const FILES: usize = 128;
const ROWS_PER_FILE: usize = 128;

fn write_files() -> TempDir {
let directory = tempfile::tempdir().unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int64, false)]));

for file_index in 0..FILES {
let start = i64::try_from(file_index * ROWS_PER_FILE).unwrap();
let values = Int64Array::from_iter_values(
start..start + i64::try_from(ROWS_PER_FILE).unwrap(),
);
let batch =
RecordBatch::try_new(Arc::clone(&schema), vec![Arc::new(values)]).unwrap();
let file =
File::create(directory.path().join(format!("{file_index}.parquet"))).unwrap();
let mut writer = ArrowWriter::try_new(file, Arc::clone(&schema), None).unwrap();
writer.write(&batch).unwrap();
writer.close().unwrap();
}

directory
}

fn criterion_benchmark(criterion: &mut Criterion) {
let directory = write_files();
let runtime = tokio::runtime::Runtime::new().unwrap();
let context = runtime.block_on(async {
let context = SessionContext::new_with_config(
SessionConfig::new().with_target_partitions(1),
);
context
.register_parquet("t", directory.path().to_str().unwrap(), Default::default())
.await
.unwrap();
context
});

runtime.block_on(async {
let batches = context
.sql("SELECT id FROM t WHERE id >= 0")
.await
.unwrap()
.collect()
.await
.unwrap();
assert_eq!(
batches.iter().map(RecordBatch::num_rows).sum::<usize>(),
FILES * ROWS_PER_FILE
);
});

criterion.bench_function(
"parquet_pruning_setup_cache/same_schema_files",
|bencher| {
bencher.to_async(&runtime).iter(|| async {
context
.sql("SELECT id FROM t WHERE id >= 0")
.await
.unwrap()
.collect()
.await
.unwrap()
});
},
);
}

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