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HomeJavajavaTutorialHow Can I Group Objects by an Attribute Using Java 8 Streams?

How Can I Group Objects by an Attribute Using Java 8 Streams?

Grouping Objects by an Attribute Using Java 8

In Java, grouping objects by an attribute can provide a structured way to organize and analyze data. For example, suppose you have a list of students and their locations. You may wish to group the students based on their location for further processing.

Here's a snippet of code that leverages the advanced features of Java 8 to achieve this:

import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.util.stream.Collectors;

public class Grouping {
    public static void main(String[] args) {

        List<student> studlist = new ArrayList();
        studlist.add(new Student("1726", "John", "New York"));
        studlist.add(new Student("4321", "Max", "California"));
        studlist.add(new Student("2234", "Andrew", "Los Angeles"));
        studlist.add(new Student("5223", "Michael", "New York"));
        studlist.add(new Student("7765", "Sam", "California"));
        studlist.add(new Student("3442", "Mark", "New York"));

        Map<string list>> studlistGrouped =
            studlist.stream().collect(Collectors.groupingBy(w -> w.stud_location));
    }
}

class Student {
    String stud_id;
    String stud_name;
    String stud_location;

    Student(String sid, String sname, String slocation) {
        this.stud_id = sid;
        this.stud_name = sname;
        this.stud_location = slocation;
    }
}</string></student>

The Collectors.groupingBy method, introduced in Java 8, allows you to create a Map that groups objects based on the value of a specified key function. In this case, we specify the stud_location field as the key function, resulting in a map where each key represents a location and the corresponding value is a list of students at that location.

This approach provides an efficient and elegant way to group a list of objects using a specific attribute. The resulting Map can be leveraged for various purposes, such as further filtering, sorting, or data visualization.

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