Java 8 Lambda Expressions and Stream API: Functional Interfaces and Common Operations

Introduction

Java 8's most significant feature is the introduction of lambda expressions, enabling functional programming by passing behavior as immutable values processed by functions.

Important Functional Interfaces in Java

What is a Functional Interface?

A functional interface contains a single abstract method and serves as the target type for lambda expressions. It can be annotated with @FunctionalInterface to let the compiler enforce this rule. Default and static methods are allowed.

Common Java 8 Functional Interfaces

public class Test {
    public static void main(String[] args) {
        Predicate
predicate = x -> x > 185;
        Student student = new Student("9龙", 23, 175);
        System.out.println("9龙的身高高于185吗？：" + predicate.test(student.getStature()));

        Consumer
consumer = System.out::println;
        consumer.accept("命运由我不由天");

        Function
function = Student::getName;
        String name = function.apply(student);
        System.out.println(name);

        Supplier
supplier = () -> Integer.valueOf(BigDecimal.TEN.toString());
        System.out.println(supplier.get());

        UnaryOperator
unaryOperator = uglily -> !uglily;
        Boolean apply2 = unaryOperator.apply(true);
        System.out.println(apply2);

        BinaryOperator
operator = (x, y) -> x * y;
        Integer integer = operator.apply(2, 3);
        System.out.println(integer);

        test(() -> "我是一个演示的函数式接口");
    }

    /**
     * Demonstrates a custom functional interface usage
     */
    public static void test(Worker worker) {
        String work = worker.work();
        System.out.println(work);
    }

    public interface Worker {
        String work();
    }
}
//9龙的身高高于185吗？：false
//命运由我不由天
//9龙
//10
//false
//6
//我是一个演示的函数式接口

The example shows lambda usage, method references (e.g., Student::getName ), and a custom functional interface.

Lazy and Eager Evaluation

Stream operations are lazy; they return another Stream until a terminal operation triggers eager evaluation to produce a result.

Common Stream Operations

collect(Collectors.toList())

Converts a Stream to a List (also toSet , toMap ) and triggers eager evaluation.

public class TestCase {
    public static void main(String[] args) {
        List
studentList = Stream.of(
            new Student("路飞", 22, 175),
            new Student("红发", 40, 180),
            new Student("白胡子", 50, 185)
        ).collect(Collectors.toList());
        System.out.println(studentList);
    }
}
//[Student{name='路飞', age=22, stature=175, specialities=null}, ...]

filter

Filters elements using a Predicate (lazy).

public class TestCase {
    public static void main(String[] args) {
        List
students = new ArrayList<>(3);
        students.add(new Student("路飞", 22, 175));
        students.add(new Student("红发", 40, 180));
        students.add(new Student("白胡子", 50, 185));
        List
list = students.stream()
            .filter(stu -> stu.getStature() < 180)
            .collect(Collectors.toList());
        System.out.println(list);
    }
}
//[Student{name='路飞', age=22, stature=175, specialities=null}]

map

Transforms each element using a Function (lazy).

public class TestCase {
    public static void main(String[] args) {
        List
students = new ArrayList<>(3);
        // add students ...
        List
names = students.stream()
            .map(Student::getName)
            .collect(Collectors.toList());
        System.out.println(names);
    }
}
//[路飞, 红发, 白胡子]

flatMap

Merges multiple Streams into one (lazy).

public class TestCase {
    public static void main(String[] args) {
        List
students = new ArrayList<>(3);
        // add students ...
        List
studentList = Stream.of(students,
            asList(new Student("艾斯", 25, 183), new Student("雷利", 48, 176)))
            .flatMap(students1 -> students1.stream())
            .collect(Collectors.toList());
        System.out.println(studentList);
    }
}
//[Student{name='路飞', ...}, Student{name='艾斯', ...}, Student{name='雷利', ...}]

max and min

Finds maximum or minimum values using a Comparator and returns an Optional to avoid null pointers.

public class TestCase {
    public static void main(String[] args) {
        List
students = new ArrayList<>(3);
        // add students ...
        Optional
max = students.stream()
            .max(Comparator.comparing(stu -> stu.getAge()));
        Optional
min = students.stream()
            .min(Comparator.comparing(stu -> stu.getAge()));
        max.ifPresent(System.out::println);
        min.ifPresent(System.out::println);
    }
}
//Student{name='白胡子', age=50, ...}
//Student{name='路飞', age=22, ...}

count

Counts elements after optional filtering (eager).

public class TestCase {
    public static void main(String[] args) {
        List
students = new ArrayList<>(3);
        // add students ...
        long count = students.stream()
            .filter(s1 -> s1.getAge() < 45)
            .count();
        System.out.println("年龄小于45岁的人数是：" + count);
    }
}
//年龄小于45岁的人数是：2

reduce

Reduces a Stream to a single value by repeatedly applying a binary operator.

public class TestCase {
    public static void main(String[] args) {
        Integer reduce = Stream.of(1, 2, 3, 4)
            .reduce(0, (acc, x) -> acc + x);
        System.out.println(reduce);
    }
}
//10

Advanced Collectors

Collecting to Values

Collectors transform a Stream into complex results, such as lists, averages, or custom objects.

public class CollectorsTest {
    public static void main(String[] args) {
        List
students1 = new ArrayList<>(3);
        // add students ...
        OutstandingClass ostClass1 = new OutstandingClass("一班", students1);
        List
students2 = new ArrayList<>(students1);
        students2.remove(1);
        OutstandingClass ostClass2 = new OutstandingClass("二班", students2);
        Stream
classStream = Stream.of(ostClass1, ostClass2);
        OutstandingClass biggest = biggestGroup(classStream);
        System.out.println("人数最多的班级是：" + biggest.getName());
        System.out.println("一班平均年龄是：" + averageNumberOfStudent(students1));
    }
    private static OutstandingClass biggestGroup(Stream
classes) {
        return classes.collect(maxBy(comparing(oc -> oc.getStudents().size())))
            .orElseGet(OutstandingClass::new);
    }
    private static double averageNumberOfStudent(List
students) {
        return students.stream().collect(averagingInt(Student::getAge));
    }
}
//人数最多的班级是：一班
//一班平均年龄是：37.666666666666664

partitioningBy

Splits a Stream into two groups based on a Predicate .

Map
> map = students.stream()
    .collect(Collectors.partitioningBy(student ->
        student.getSpecialities().contains(SpecialityEnum.SING)));

groupingBy

Groups elements by a classification function, similar to SQL's GROUP BY.

Map
> map = students.stream()
    .collect(Collectors.groupingBy(student ->
        student.getSpecialities().get(0)));

joining

Concatenates strings from a Stream with optional delimiter, prefix, and suffix.

String names = students.stream()
    .map(Student::getName)
    .collect(Collectors.joining(",", "[", "]"));
System.out.println(names);
//[路飞,红发,白胡子]

Conclusion

The article demonstrates how Java 8 lambda expressions and the Stream API simplify collection processing, making code more expressive and concise. By combining various intermediate and terminal operations, developers can efficiently handle filtering, transformation, aggregation, and grouping tasks.