Stream Map Reduce

Map-Reduce is a technique used for computation in distributed systems. As the name suggests the Map-Reduce function is divided into two major tasks.

First, the input data collected from multiple distributed systems are broken down into the smallest distinguished streams for easily mapping together and converted into the required format, then a reduction operation takes the output of the map and is applied to collect data into a single variable.

Map-Reduce is generally broken down into smaller units and computed via multiple threads hence is easy to scale.

Befoe java 8, it was not possible to load a lot of data in memory and perform the bulk operations but since Java 8, with the introduction of Streams in Java 8, it's possible to perform bulk operations parallelly without loading data into memory.

package org.wesome.java8;

import lombok.AllArgsConstructor;
import lombok.Data;

import java.util.Arrays;
import java.util.List;

@Data
@AllArgsConstructor
class Fruit {
    int fruitId;
    String fruitName;
    String taste;
    double price;
}

class Apple {
    public static void main(String args[]) {
        List<Fruit> fruits = Arrays.asList(new Fruit(1, "Macintosh", "sweet", 1.1), new Fruit(2, "Fuji", "sweet", 2.2), new Fruit(3, "Gala", "sour", 1.1), new Fruit(4, "Jonagold", "sour", 2.2));

        System.out.println("*--------------IntStream Sequential Map-Reduce--------------*");
        double priceSum = fruits.stream().mapToDouble(Fruit::getPrice).sum();

        System.out.println("*--------------IntStream Parallel Map-Reduce--------------*");
        priceSum = fruits.parallelStream().mapToDouble(Fruit::getPrice).sum();
    }
}