rluvaton commented on code in PR #21251: URL: https://github.com/apache/datafusion/pull/21251#discussion_r3036633137
########## datafusion/functions-nested/benches/map_extract.rs: ########## @@ -0,0 +1,281 @@ +// 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. + +use arrow::array::{ + ArrayRef, BinaryArray, BinaryViewArray, Int32Array, ListArray, StringArray, + StringViewArray, +}; +use arrow::buffer::{OffsetBuffer, ScalarBuffer}; +use arrow::datatypes::Field; +use criterion::{Criterion, criterion_group, criterion_main}; +use datafusion_common::config::ConfigOptions; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs}; +use datafusion_functions_nested::map::map_udf; +use datafusion_functions_nested::map_extract::map_extract_udf; +use rand::Rng; +use rand::prelude::ThreadRng; +use std::collections::HashSet; +use std::hash::Hash; +use std::hint::black_box; +use std::sync::Arc; + +const MAP_ROWS: usize = 1000; +const MAP_KEYS_PER_ROW: usize = 1000; + +fn gen_unique_values<T>( + rng: &mut ThreadRng, + mut make_value: impl FnMut(i32) -> T, +) -> Vec<T> +where + T: Eq + Hash, +{ + let mut values = HashSet::with_capacity(MAP_KEYS_PER_ROW); + + while values.len() < MAP_KEYS_PER_ROW { + values.insert(make_value(rng.random_range(0..10000))); + } + + values.into_iter().collect() +} + +fn gen_repeat_values<T: Clone>(values: &[T], repeats: usize) -> Vec<T> { + let mut repeated = Vec::with_capacity(values.len() * repeats); + + for _ in 0..repeats { + repeated.extend_from_slice(values); + } + + repeated +} + +fn gen_utf8_values(rng: &mut ThreadRng) -> Vec<String> { + gen_unique_values(rng, |value| value.to_string()) +} + +fn gen_binary_values(rng: &mut ThreadRng) -> Vec<Vec<u8>> { + gen_unique_values(rng, |value| value.to_le_bytes().to_vec()) +} + +fn gen_primitive_values(rng: &mut ThreadRng) -> Vec<i32> { + gen_unique_values(rng, |value| value) +} + +fn list_array(values: ArrayRef, row_count: usize, values_per_row: usize) -> ArrayRef { + let offsets = (0..=row_count) + .map(|index| (index * values_per_row) as i32) + .collect::<Vec<_>>(); + Arc::new(ListArray::new( + Arc::new(Field::new_list_field(values.data_type().clone(), true)), + OffsetBuffer::new(ScalarBuffer::from(offsets)), + values, + None, + )) +} + +fn build_map_array(keys: ArrayRef, values: ArrayRef) -> ArrayRef { + let number_rows = keys.len(); + let keys_arg = ColumnarValue::Array(keys); + let values_arg = ColumnarValue::Array(values); + let return_type = map_udf() + .return_type(&[keys_arg.data_type(), values_arg.data_type()]) + .expect("should get return type"); + let arg_fields = vec![ + Field::new("keys", keys_arg.data_type(), true).into(), + Field::new("values", values_arg.data_type(), true).into(), + ]; + let return_field = Field::new("map", return_type, true).into(); + let config_options = Arc::new(ConfigOptions::default()); + + match map_udf() + .invoke_with_args(ScalarFunctionArgs { + args: vec![keys_arg, values_arg], + arg_fields, + number_rows, + return_field, + config_options, + }) + .expect("map should work on valid values") + { + ColumnarValue::Array(array) => array, + other => panic!("expected array result, got {other:?}"), + } +} + +fn bench_map_extract_case( + c: &mut Criterion, + name: &str, + map_array: ArrayRef, + query_keys: ArrayRef, +) { + let number_rows = map_array.len(); + let map_arg = ColumnarValue::Array(map_array); + let key_arg = ColumnarValue::Array(query_keys); + let return_type = map_extract_udf() + .return_type(&[map_arg.data_type(), key_arg.data_type()]) + .expect("should get return type"); + let arg_fields = vec![ + Field::new("map", map_arg.data_type(), true).into(), + Field::new("key", key_arg.data_type(), true).into(), + ]; + let return_field = Field::new("result", return_type, true).into(); + let config_options = Arc::new(ConfigOptions::default()); + + c.bench_function(name, |b| { + b.iter(|| { + black_box( + map_extract_udf() + .invoke_with_args(ScalarFunctionArgs { + args: vec![map_arg.clone(), key_arg.clone()], + arg_fields: arg_fields.clone(), + number_rows, + return_field: Arc::clone(&return_field), + config_options: Arc::clone(&config_options), + }) Review Comment: I think it will be cleaner to extract the `ScalarFunctionArgs` creation and just do clone here -- This is an automated message from the Apache Git Service. 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