Java 8 Functional Interfaces and Stream Operations: Concepts, Examples, and Advanced Collectors

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Important Functional Interfaces in Java

1. What is a Functional Interface

A functional interface is an interface that contains exactly one abstract method and can be used as the type of a lambda expression. When a class is annotated with @FunctionalInterface, the compiler checks that it has only one abstract method; otherwise a compilation error occurs. The interface may contain multiple default or static methods.

Note

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1.1 Common Functional Interfaces Built into Java 8

public class Test {
    public static void main(String[] args) {
        Predicate<Integer> 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<String> consumer = System.out::println;
        consumer.accept("命运由我不由天");

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

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

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

        BinaryOperator<Integer> 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
     * @param worker
     */
    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 above demonstrates the use of lambda expressions with built‑in functional interfaces and a custom functional interface.

Next, we explore how Java 8 integrates functional interfaces into streams to process collections efficiently. Note that the method reference syntax Student::getName is a concise way to write a lambda expression ( student -> student.getName()).

1.2 Lazy Evaluation and Eager Evaluation

Lazy evaluation describes a Stream that only defines operations; the result is also a Stream, and the actual computation is deferred until a terminal operation is invoked (eager evaluation).

2. Common Stream Operations

2.1 collect(Collectors.toList())

Converts a Stream into a List. Similar collectors exist for Set and Map. This is an eager operation.

public class TestCase {
    public static void main(String[] args) {
        List<Student> 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);
    }
}
// Output:
//[Student{name='路飞', age=22, stature=175, specialities=null},
// Student{name='红发', age=40, stature=180, specialities=null},
// Student{name='白胡子', age=50, stature=185, specialities=null}]

2.2 filter

Filters elements based on a Predicate. This is a lazy operation.

Example: select students with height less than 180.

public class TestCase {
    public static void main(String[] args) {
        List<Student> 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<Student> list = students.stream()
                .filter(stu -> stu.getStature() < 180)
                .collect(Collectors.toList());
        System.out.println(list);
    }
}
// Output:
//[Student{name='路飞', age=22, stature=175, specialities=null}]

2.3 map

Transforms each element using a Function. This is a lazy operation.

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

2.4 flatMap

Flattens multiple Streams into a single Stream. Lazy evaluation.

public class TestCase {
    public static void main(String[] args) {
        List<Student> 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<Student> studentList = Stream.of(students,
                asList(new Student("艾斯", 25, 183), new Student("雷利", 48, 176)))
                .flatMap(list -> list.stream())
                .collect(Collectors.toList());
        System.out.println(studentList);
    }
}
// Output includes all five students.

2.5 max and min

Find the maximum or minimum element using a Comparator. This is an eager operation that returns an Optional to avoid null pointers.

public class TestCase {
    public static void main(String[] args) {
        List<Student> 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));
        Optional<Student> max = students.stream()
                .max(Comparator.comparing(Student::getAge));
        Optional<Student> min = students.stream()
                .min(Comparator.comparing(Student::getAge));
        max.ifPresent(System.out::println);
        min.ifPresent(System.out::println);
    }
}
// Output:
//Student{name='白胡子', age=50, stature=185, specialities=null}
//Student{name='路飞', age=22, stature=175, specialities=null}

2.6 count

Counts elements that satisfy a predicate, usually combined with filter. Eager evaluation.

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

2.7 reduce

The reduce operation aggregates a stream into a single value. It underlies many other terminal operations such as sum, max, and min. Eager evaluation.

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);
    }
}
// Output:
//10

Advanced Collectors

3.1 Collecting to Values

Collectors are utilities that transform a Stream into a complex result. The examples below use static imports from java.util.stream.Collectors.

public class CollectorsTest {
    public static void main(String[] args) {
        List<Student> students1 = new ArrayList<>(3);
        students1.add(new Student("路飞", 23, 175));
        students1.add(new Student("红发", 40, 180));
        students1.add(new Student("白胡子", 50, 185));
        OutstandingClass ostClass1 = new OutstandingClass("一班", students1);
        List<Student> students2 = new ArrayList<>(students1);
        students2.remove(1);
        OutstandingClass ostClass2 = new OutstandingClass("二班", students2);
        Stream<OutstandingClass> 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<OutstandingClass> classes) {
        return classes.collect(maxBy(comparing(c -> c.getStudents().size())))
                .orElseGet(OutstandingClass::new);
    }

    private static double averageNumberOfStudent(List<Student> students) {
        return students.stream().collect(averagingInt(Student::getAge));
    }
}
// Output:
//人数最多的班级是：一班
//一班平均年龄是：37.666666666666664

3.2 Collecting to Partitions

Partitions a stream into two groups (true/false) based on a Predicate using Collectors.partitioningBy.

public class PartitioningByTest {
    public static void main(String[] args) {
        // Assume List<Student> students is initialized
        Map<Boolean, List<Student>> map = students.stream()
                .collect(Collectors.partitioningBy(s -> s.getSpecialities().contains(SpecialityEnum.SING)));
    }
}

3.3 Data Grouping

Groups elements by an arbitrary key using Collectors.groupingBy, similar to SQL's GROUP BY.

public class GroupingByTest {
    public static void main(String[] args) {
        // Assume List<Student> students is initialized
        Map<SpecialityEnum, List<Student>> map = students.stream()
                .collect(Collectors.groupingBy(s -> s.getSpecialities().get(0)));
    }
}

3.4 String Joining

Concatenates strings from a stream using Collectors.joining. The method can accept a delimiter, a prefix, and a suffix.

public class JoiningTest {
    public static void main(String[] args) {
        List<Student> 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));
        String names = students.stream()
                .map(Student::getName)
                .collect(Collectors.joining(",", "[", "]"));
        System.out.println(names);
    }
}
// Output:
//[路飞,红发,白胡子]

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