8.2.5. Map-reduce 并行计算

rayon-badge cat-concurrency-badge

此实例使用 rayon::filterrayon::map,以及 rayon::reduce 计算 Person 对象中年龄超过 30 岁的那些人的平均年龄。

rayon::filter 过滤集合中满足给定断言的元素。rayon::map 对每个元素执行一次计算,创建一个新的迭代;然后,基于前一次的 reduce 计算结果和当前元素一起,rayon::reduce 执行新的计算。也可以查看 rayon::sum,它与本实例中的 reduce 计算具有相同的结果。

use rayon::prelude::*;

struct Person {
    age: u32,
}

fn main() {
    let v: Vec<Person> = vec![
        Person { age: 23 },
        Person { age: 19 },
        Person { age: 42 },
        Person { age: 17 },
        Person { age: 17 },
        Person { age: 31 },
        Person { age: 30 },
    ];

    let num_over_30 = v.par_iter().filter(|&x| x.age > 30).count() as f32;
    let sum_over_30 = v.par_iter()
        .map(|x| x.age)
        .filter(|&x| x > 30)
        .reduce(|| 0, |x, y| x + y);

    let alt_sum_30: u32 = v.par_iter()
        .map(|x| x.age)
        .filter(|&x| x > 30)
        .sum();

    let avg_over_30 = sum_over_30 as f32 / num_over_30;
    let alt_avg_over_30 = alt_sum_30 as f32/ num_over_30;

    assert!((avg_over_30 - alt_avg_over_30).abs() < std::f32::EPSILON);
    println!("The average age of people older than 30 is {}", avg_over_30);
}