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add criterion benchmark for CaseExpr (#11482)
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datafusion/physical-expr/Cargo.toml

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@@ -77,3 +77,7 @@ tokio = { workspace = true, features = ["rt-multi-thread"] }
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[[bench]]
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harness = false
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name = "in_list"
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[[bench]]
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harness = false
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name = "case_when"
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@@ -0,0 +1,94 @@
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// Licensed to the Apache Software Foundation (ASF) under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
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// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations
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// under the License.
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use arrow::datatypes::{Field, Schema};
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use arrow::record_batch::RecordBatch;
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use arrow_array::builder::{Int32Builder, StringBuilder};
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use arrow_schema::DataType;
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use criterion::{black_box, criterion_group, criterion_main, Criterion};
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use datafusion_common::ScalarValue;
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use datafusion_expr::Operator;
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use datafusion_physical_expr::expressions::{BinaryExpr, CaseExpr};
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use datafusion_physical_expr_common::expressions::column::Column;
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use datafusion_physical_expr_common::expressions::Literal;
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use datafusion_physical_expr_common::physical_expr::PhysicalExpr;
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use std::sync::Arc;
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fn make_col(name: &str, index: usize) -> Arc<dyn PhysicalExpr> {
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Arc::new(Column::new(name, index))
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}
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fn make_lit_i32(n: i32) -> Arc<dyn PhysicalExpr> {
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Arc::new(Literal::new(ScalarValue::Int32(Some(n))))
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}
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fn criterion_benchmark(c: &mut Criterion) {
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// create input data
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let mut c1 = Int32Builder::new();
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let mut c2 = StringBuilder::new();
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for i in 0..1000 {
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c1.append_value(i);
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if i % 7 == 0 {
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c2.append_null();
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} else {
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c2.append_value(&format!("string {i}"));
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}
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}
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let c1 = Arc::new(c1.finish());
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let c2 = Arc::new(c2.finish());
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let schema = Schema::new(vec![
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Field::new("c1", DataType::Int32, true),
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Field::new("c2", DataType::Utf8, true),
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]);
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let batch = RecordBatch::try_new(Arc::new(schema), vec![c1, c2]).unwrap();
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// use same predicate for all benchmarks
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let predicate = Arc::new(BinaryExpr::new(
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make_col("c1", 0),
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Operator::LtEq,
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make_lit_i32(500),
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));
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// CASE WHEN expr THEN 1 ELSE 0 END
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c.bench_function("case_when: scalar or scalar", |b| {
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let expr = Arc::new(
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CaseExpr::try_new(
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None,
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vec![(predicate.clone(), make_lit_i32(1))],
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Some(make_lit_i32(0)),
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)
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.unwrap(),
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);
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b.iter(|| black_box(expr.evaluate(black_box(&batch)).unwrap()))
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});
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// CASE WHEN expr THEN col ELSE null END
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c.bench_function("case_when: column or null", |b| {
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let expr = Arc::new(
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CaseExpr::try_new(
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None,
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vec![(predicate.clone(), make_col("c2", 1))],
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Some(Arc::new(Literal::new(ScalarValue::Utf8(None)))),
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)
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.unwrap(),
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);
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b.iter(|| black_box(expr.evaluate(black_box(&batch)).unwrap()))
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});
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}
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criterion_group!(benches, criterion_benchmark);
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criterion_main!(benches);

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