Add parquet SQL benchmarks

datafusion/Cargo.toml

@@ -116,3 +116,7 @@ harness = false
 [[bench]]
 name = "physical_plan"
 harness = false
+
+[[bench]]
+name = "parquet_query_sql"
+harness = false

datafusion/benches/parquet_query_sql.rs

@@ -0,0 +1,237 @@
+// 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 again parquet data
+
+use arrow::array::{ArrayRef, DictionaryArray, PrimitiveArray, StringArray};
+use arrow::datatypes::{
+ ArrowPrimitiveType, DataType, Field, Float64Type, Int32Type, Int64Type, Schema,
+ SchemaRef,
+};
+use arrow::record_batch::RecordBatch;
+use criterion::{criterion_group, criterion_main, Criterion};
+use datafusion::prelude::ExecutionContext;
+use parquet::arrow::ArrowWriter;
+use parquet::file::properties::{WriterProperties, WriterVersion};
+use rand::distributions::uniform::SampleUniform;
+use rand::distributions::Alphanumeric;
+use rand::prelude::*;
+use std::fs::File;
+use std::io::Read;
+use std::ops::Range;
+use std::path::Path;
+use std::sync::Arc;
+use std::time::Instant;
+use tempfile::NamedTempFile;
+use tokio_stream::StreamExt;
+
+/// The number of batches to write
+const NUM_BATCHES: usize = 2048;
+/// The number of rows in each record batch to write
+const WRITE_RECORD_BATCH_SIZE: usize = 1024;
+/// The number of rows in a row group
+const ROW_GROUP_SIZE: usize = 1024 * 1024;
+/// The number of row groups expected
+const EXPECTED_ROW_GROUPS: usize = 2;
+
+fn schema() -> SchemaRef {
+ let string_dictionary_type =
+ DataType::Dictionary(Box::new(DataType::Int32), Box::new(DataType::Utf8));
+
+ Arc::new(Schema::new(vec![
+ Field::new("dict_10_required", string_dictionary_type.clone(), false),
+ Field::new("dict_10_optional", string_dictionary_type.clone(), true),
+ Field::new("dict_100_required", string_dictionary_type.clone(), false),
+ Field::new("dict_100_optional", string_dictionary_type.clone(), true),
+ Field::new("dict_1000_required", string_dictionary_type.clone(), false),
+ Field::new("dict_1000_optional", string_dictionary_type.clone(), true),
+ Field::new("string_required", DataType::Utf8, false),
+ Field::new("string_optional", DataType::Utf8, true),
+ Field::new("i64_required", DataType::Int64, false),
+ Field::new("i64_optional", DataType::Int64, true),
+ Field::new("f64_required", DataType::Float64, false),
+ Field::new("f64_optional", DataType::Float64, true),
+ ]))
+}
+
+fn generate_batch() -> RecordBatch {
+ let schema = schema();
+ let len = WRITE_RECORD_BATCH_SIZE;
+ RecordBatch::try_new(
+ schema,
+ vec![
+ generate_string_dictionary("prefix", 10, len, 1.0),
+ generate_string_dictionary("prefix", 10, len, 0.5),
+ generate_string_dictionary("prefix", 100, len, 1.0),
+ generate_string_dictionary("prefix", 100, len, 0.5),
+ generate_string_dictionary("prefix", 1000, len, 1.0),
+ generate_string_dictionary("prefix", 1000, len, 0.5),
+ generate_strings(0..100, len, 1.0),
+ generate_strings(0..100, len, 0.5),
+ generate_primitive::<Int64Type>(len, 1.0, -2000..2000),
+ generate_primitive::<Int64Type>(len, 0.5, -2000..2000),
+ generate_primitive::<Float64Type>(len, 1.0, -1000.0..1000.0),
+ generate_primitive::<Float64Type>(len, 0.5, -1000.0..1000.0),
+ ],
+ )
+ .unwrap()
+}
+
+fn generate_string_dictionary(
+ prefix: &str,
+ cardinality: usize,
+ len: usize,
+ valid_percent: f64,
+) -> ArrayRef {
+ let mut rng = thread_rng();
+ let strings: Vec<_> = (0..cardinality)
+ .map(|x| format!("{}#{}", prefix, x))
+ .collect();
+
+ Arc::new(DictionaryArray::<Int32Type>::from_iter((0..len).map(
+ |_| {
+ rng.gen_bool(valid_percent)
+ .then(|| strings[rng.gen_range(0..cardinality)].as_str())
+ },
+ )))
+}
+
+fn generate_strings(
+ string_length_range: Range<usize>,
+ len: usize,
+ valid_percent: f64,
+) -> ArrayRef {
+ let mut rng = thread_rng();
+ Arc::new(StringArray::from_iter((0..len).map(|_| {
+ rng.gen_bool(valid_percent).then(|| {
+ let string_len = rng.gen_range(string_length_range.clone());
+ (0..string_len)
+ .map(|_| char::from(rng.sample(Alphanumeric)))
+ .collect::<String>()
+ })
+ })))
+}
+
+fn generate_primitive<T>(
+ len: usize,
+ valid_percent: f64,
+ range: Range<T::Native>,
+) -> ArrayRef
+where
+ T: ArrowPrimitiveType,
+ T::Native: SampleUniform,
+{
+ let mut rng = thread_rng();
+ Arc::new(PrimitiveArray::<T>::from_iter((0..len).map(|_| {
+ rng.gen_bool(valid_percent)
+ .then(|| rng.gen_range(range.clone()))
+ })))
+}
+
+fn generate_file() -> NamedTempFile {
+ let now = Instant::now();
+ let named_file = tempfile::Builder::new()
+ .prefix("parquet_query_sql")
+ .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 file = named_file.as_file().try_clone().unwrap();
+ let mut writer = ArrowWriter::try_new(file, schema, Some(properties)).unwrap();
+
+ for _ in 0..NUM_BATCHES {
+ let batch = generate_batch();
+ writer.write(&batch).unwrap();
+ }
+
+ let metadata = writer.close().unwrap();
+ assert_eq!(
+ metadata.num_rows as usize,
+ WRITE_RECORD_BATCH_SIZE * NUM_BATCHES
+ );
+ assert_eq!(metadata.row_groups.len(), EXPECTED_ROW_GROUPS);
+
+ println!(
+ "Generated parquet file in {} seconds",
+ now.elapsed().as_secs_f32()
+ );
+
+ named_file
+}
+
+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 mut context = ExecutionContext::new();
+
+ let rt = tokio::runtime::Builder::new_multi_thread().build().unwrap();
+ rt.block_on(context.register_parquet("t", file_path.as_str()))
+ .unwrap();
+
+ // We read the queries from a file so they can be changed without recompiling the benchmark
+ let mut queries_file = File::open("benches/parquet_query_sql.sql").unwrap();
+ let mut queries = String::new();
+ queries_file.read_to_string(&mut queries).unwrap();
+
+ for query in queries.split(';') {
+ let query = query.trim();
+
+ // Remove comment lines
+ let query: Vec<_> = query.split('\n').filter(|x| !x.starts_with("--")).collect();
+ let query = query.join(" ");
+
+ // Ignore blank lines
+ if query.is_empty() {
+ continue;
+ }
+
+ let query = query.as_str();
+ c.bench_function(query, |b| {
+ b.iter(|| {
+ let mut context = context.clone();
+ rt.block_on(async move {
+ let query = context.sql(query).await.unwrap();
+ let mut stream = query.execute_stream().await.unwrap();
+ while let Some(_) = criterion::black_box(stream.next().await) {}
+ })
+ });
+ });
+ }
+
+ // Clean up temporary file if any
+ std::mem::drop(temp_file);
+}
+
+criterion_group!(benches, criterion_benchmark);
+criterion_main!(benches);

datafusion/benches/parquet_query_sql.sql

@@ -0,0 +1,32 @@
+-- Test scanning out dictionary columns
+select dict_10_optional from t;
+select dict_100_optional from t;
+select dict_1000_optional from t;
+
+-- Test filtering dictionary columns
+select count(*) from t where dict_10_required = 'prefix#0';
+select count(*) from t where dict_100_required = 'prefix#0';
+select count(*) from t where dict_1000_required = 'prefix#0';
+
+-- Test select integers
+select i64_optional from t where dict_10_required = 'prefix#2' and dict_1000_required = 'prefix#10';
+select i64_required from t where dict_10_required = 'prefix#2' and dict_1000_required = 'prefix#10';
+
+-- Test select integers
+select string_optional from t where dict_10_required = 'prefix#1' and dict_1000_required = 'prefix#1';
+select string_required from t where dict_10_required = 'prefix#1' and dict_1000_required = 'prefix#1';
+
+-- Test select distinct
+select distinct dict_10_required from t where dict_1000_optional is not NULL and i64_optional > 0;
+select distinct dict_10_required from t where dict_1000_optional is not NULL and i64_optional > 0;
+select distinct dict_10_required from t where dict_1000_optional is not NULL and i64_required > 0;
+select distinct dict_10_required from t where dict_1000_optional is not NULL and i64_required > 0;
+
+-- Test basic aggregations
+select dict_10_optional, count(*) from t group by dict_10_optional;
+select dict_10_optional, dict_100_optional, count(*) from t group by dict_10_optional, dict_100_optional;
+
+-- Test float aggregations
+select dict_10_optional, dict_100_optional, MIN(f64_required), MAX(f64_required), AVG(f64_required) from t group by dict_10_optional, dict_100_optional;
+select dict_10_optional, dict_100_optional, MIN(f64_optional), MAX(f64_optional), AVG(f64_optional) from t group by dict_10_optional, dict_100_optional;
+select dict_10_required, dict_100_required, MIN(f64_optional), MAX(f64_optional), AVG(f64_optional) from t group by dict_10_required, dict_100_required;

dev/release/rat_exclude_files.txt

@@ -116,6 +116,7 @@ ci/*
 **/*.svg
 **/*.csv
 **/*.json
+**/*.sql
 venv/*
 testing/*
 target/*