Java Academy · Lesson

groupingBy: Classifying Elements

Group stream elements into maps by a classifier function and compose with downstream collectors.

Lesson 1 of 413 steps

groupingBy: Classifying Elements is a free Java Academy lesson on CoddyKit. This is lesson 1 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Java Academy learning path, and your progress syncs across the web and the CoddyKit app. The Java Academy course includes 4 lessons in total.

What is groupingBy?

Collectors.groupingBy() partitions stream elements into a Map where each key maps to a list of matching elements. It is the stream equivalent of SQL's GROUP BY.

import java.util.*;
import java.util.stream.*;

record Person(String name, String city) {}
List<Person> people = List.of(
    new Person("Alice","NYC"), new Person("Bob","LA"),
    new Person("Carol","NYC"), new Person("Dave","LA"),
    new Person("Eve","Chicago")
);

Map<String, List<Person>> byCity =
    people.stream().collect(Collectors.groupingBy(Person::city));
byCity.forEach((city, ps) -> System.out.println(city + ": " + ps.size()));

Downstream Collector: counting

Compose groupingBy with a downstream collector to aggregate instead of listing:

Map<String, Long> countByCity =
    people.stream().collect(
        Collectors.groupingBy(Person::city, Collectors.counting())
    );
countByCity.forEach((city, n) -> System.out.println(city + " -> " + n));
// NYC -> 2, LA -> 2, Chicago -> 1

Downstream Collector: mapping

Use Collectors.mapping() as a downstream to transform elements before collecting them:

Map<String, List<String>> namesByCity =
    people.stream().collect(
        Collectors.groupingBy(
            Person::city,
            Collectors.mapping(Person::name, Collectors.toList())
        )
    );
namesByCity.forEach((city, names) -> System.out.println(city + ": " + names));

Downstream Collector: joining

Concatenate names per group into a single comma-separated string:

Map<String, String> joinedByCity =
    people.stream().collect(
        Collectors.groupingBy(
            Person::city,
            Collectors.mapping(Person::name, Collectors.joining(", "))
        )
    );
joinedByCity.forEach((city, s) -> System.out.println(city + ": " + s));
// NYC: Alice, Carol

Multi-level groupingBy

Nest groupingBy calls for multi-dimensional classification:

record Employee(String name, String dept, String level) {}
List<Employee> emps = List.of(
    new Employee("A","Eng","Junior"), new Employee("B","Eng","Senior"),
    new Employee("C","HR","Junior"), new Employee("D","HR","Senior")
);

Map<String, Map<String, List<Employee>>> grouped =
    emps.stream().collect(
        Collectors.groupingBy(Employee::dept,
            Collectors.groupingBy(Employee::level))
    );
grouped.forEach((dept, levels) -> levels.forEach((level, list) ->
    System.out.println(dept+"/"+level+": "+list.size())));

Controlling Map Type

By default groupingBy produces a HashMap. Use the 3-arg overload to specify a different map type, such as TreeMap for sorted keys:

Map<String, Long> sorted =
    people.stream().collect(
        Collectors.groupingBy(Person::city, TreeMap::new, Collectors.counting())
    );
System.out.println(sorted); // keys in alphabetical order

Downstream: averagingInt

Compute averages per group:

record Product(String category, int price) {}
List<Product> products = List.of(
    new Product("A",10), new Product("A",20),
    new Product("B",15), new Product("B",25)
);

Map<String, Double> avgPrice =
    products.stream().collect(
        Collectors.groupingBy(Product::category,
            Collectors.averagingInt(Product::price))
    );
avgPrice.forEach((cat, avg) -> System.out.printf("%s: %.1f%n", cat, avg));

Downstream: toUnmodifiableList

Use Collectors.toUnmodifiableList() downstream to produce immutable groups:

Map<String, List<String>> immutable =
    people.stream().collect(
        Collectors.groupingBy(Person::city,
            Collectors.mapping(Person::name, Collectors.toUnmodifiableList()))
    );
// Attempting to modify throws UnsupportedOperationException

Real Use Case: Order Summary

Group orders by status and sum amounts per group:

record Order(String status, double amount) {}
List<Order> orders = List.of(
    new Order("PAID", 50.0), new Order("PENDING", 30.0),
    new Order("PAID", 75.0), new Order("CANCELLED", 20.0)
);

Map<String, Double> totalByStatus =
    orders.stream().collect(
        Collectors.groupingBy(Order::status,
            Collectors.summingDouble(Order::amount))
    );
totalByStatus.forEach((s, t) -> System.out.printf("%s: $%.2f%n", s, t));

Performance Considerations

groupingBy collects all elements into memory. For very large datasets, consider processing in chunks or using a database-level GROUP BY. The downstream collector runs per element — keep it lightweight to avoid O(n²) behavior.

Combining with filter and sorted

Chain stream operations before collecting to pre-filter or pre-sort data:

Map<String, Long> activeCities =
    people.stream()
          .filter(p -> !p.city().equals("Chicago"))
          .collect(Collectors.groupingBy(Person::city, Collectors.counting()));
System.out.println(activeCities); // {NYC=2, LA=2}

Quick Check

What type does Collectors.groupingBy(Person::city) produce when used with collect()?

Answer it in the interactive lesson

Recap: groupingBy

Key takeaways:

groupingBy(classifier) → Map<K, List<T>>
Compose with downstream collectors: counting, mapping, joining, summarizing
Nest groupingBy for multi-dimensional classification
Use 3-arg overload to control resulting map type (e.g., TreeMap)

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Group stream elements into maps by a classifier function and compose with downstream collectors. You practise Java Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

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