rayon-map-reduce.md

Map-reduce in parallel

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This example uses rayon::filter, rayon::map, and rayon::reduce to calculate the average age of Person objects whose age is over 30.

rayon::filter returns elements from a collection that satisfy the given predicate. rayon::map performs an operation on every element, creating a new iteration, and rayon::reduce performs an operation given the previous reduction and the current element. Also shows use of rayon::sum, which has the same result as the reduce operation in this example.

extern crate rayon;

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);
}