Java 流组合

Java流 - Java流组合

reduce()操作组合流中的所有元素以产生单个值。

reduce操作采用两个称为种子(初始值)和累加器的参数。

累加器是一个函数。如果流是空的，种子是结果。

种子和一个元素被传递给累加器，它返回部分结果。然后将部分结果和下一个元素传递给累加器函数。

这重复，直到所有元素被传递到累加器。累加器返回的最后一个值是reduce操作的结果。

流相关接口包含两个称为reduce()和collect()的方法来执行通用reduce操作。

诸如sum()，max()，min()，count()等方法在IntStream，LongStream和DoubleStream接口中定义。

count()方法适用于所有类型的流。

Stream<T> 接口包含一个reduce()方法来执行reduce操作。该方法有三个重载版本:

T  reduce(T identity, BinaryOperator<T> accumulator)
<U> U reduce(U identity, BiFunction<U,? super  T,U> accumulator, BinaryOperator<U> combiner)
Optional<T> reduce(BinaryOperator<T> accumulator)

第一个版本的reduce()方法使用一个标识和一个累加器作为参数，并将流reduce为同一类型的单个值。

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

public class Main {
  public static void main(String[] args) {
    List<Integer> numbers  = Arrays.asList(1, 2, 3, 4, 5);
    int sum = numbers.stream()
    .reduce(0, Integer::sum); 
    System.out.println(sum);
  }
}

上面的代码生成以下结果。

例2

计算所有员工的收入总和。

import java.time.LocalDate;
import java.time.Month;
import java.util.Arrays;
import java.util.List;

public class Main {
  public static void main(String[] args) {
    double sum = Employee.persons()
        .stream()
        .map(Employee::getIncome)
        .reduce(0.0, Double::sum);
    System.out.println(sum);
  }
}

class Employee {
  public static enum Gender {
    MALE, FEMALE
  }

  private long id;
  private String name;
  private Gender gender;
  private LocalDate dob;
  private double income;

  public Employee(long id, String name, Gender gender, LocalDate dob,
      double income) {
    this.id = id;
    this.name = name;
    this.gender = gender;
    this.dob = dob;
    this.income = income;
  }
  public double getIncome() {
    return income;
  }
  public static List<Employee> persons() {
    Employee p1 = new Employee(1, "Jake", Gender.MALE, LocalDate.of(1971,
        Month.JANUARY, 1), 2343.0);
    Employee p2 = new Employee(2, "Jack", Gender.MALE, LocalDate.of(1972,
        Month.JULY, 21), 7100.0);
    Employee p3 = new Employee(3, "Jane", Gender.FEMALE, LocalDate.of(1973,
        Month.MAY, 29), 5455.0);
    Employee p4 = new Employee(4, "Jode", Gender.MALE, LocalDate.of(1974,
        Month.OCTOBER, 16), 1800.0);
    Employee p5 = new Employee(5, "Jeny", Gender.FEMALE, LocalDate.of(1975,
        Month.DECEMBER, 13), 1234.0);
    Employee p6 = new Employee(6, "Jason", Gender.MALE, LocalDate.of(1976,
        Month.JUNE, 9), 3211.0);

    List<Employee> persons = Arrays.asList(p1, p2, p3, p4, p5, p6);

    return persons;
  }
}

上面的代码生成以下结果。

例3

第二个版本的reduce方法如下所示允许我们执行一个map操作，随后执行reduce操作。

<U> U reduce(U identity, BiFunction<U,? super T,U> accumulator, BinaryOperator<U> combiner)

第三个参数用于组合部分结果当并行执行缩减操作时。

import java.time.LocalDate;
import java.time.Month;
import java.util.Arrays;
import java.util.List;

public class Main {
  public static void main(String[] args) {
    double sum = Employee.persons()
        .stream()
        .reduce(0.0, (partialSum, person) -> partialSum + person.getIncome(), Double::sum); 
    System.out.println(sum);

  }
}

class Employee {
  public static enum Gender {
    MALE, FEMALE
  }

  private long id;
  private String name;
  private Gender gender;
  private LocalDate dob;
  private double income;

  public Employee(long id, String name, Gender gender, LocalDate dob,
      double income) {
    this.id = id;
    this.name = name;
    this.gender = gender;
    this.dob = dob;
    this.income = income;
  }
  public double getIncome() {
    return income;
  }
  public void setIncome(double income) {
    this.income = income;
  }
  public static List<Employee> persons() {
    Employee p1 = new Employee(1, "Jake", Gender.MALE, LocalDate.of(1971,
        Month.JANUARY, 1), 2343.0);
    Employee p2 = new Employee(2, "Jack", Gender.MALE, LocalDate.of(1972,
        Month.JULY, 21), 7100.0);
    Employee p3 = new Employee(3, "Jane", Gender.FEMALE, LocalDate.of(1973,
        Month.MAY, 29), 5455.0);
    Employee p4 = new Employee(4, "Jode", Gender.MALE, LocalDate.of(1974,
        Month.OCTOBER, 16), 1800.0);
    Employee p5 = new Employee(5, "Jeny", Gender.FEMALE, LocalDate.of(1975,
        Month.DECEMBER, 13), 1234.0);
    Employee p6 = new Employee(6, "Jason", Gender.MALE, LocalDate.of(1976,
        Month.JUNE, 9), 3211.0);
    List<Employee> persons = Arrays.asList(p1, p2, p3, p4, p5, p6);
    return persons;
  }
}

上面的代码生成以下结果。

Java流映射并行reduce

Java Streams API支持并行映射缩减操作。

当使用以下reduce方法时，每个线程使用累加器累加部分结果。最后，组合器用于组合来自所有线程的部分结果以获得结果。

<U> U reduce(U identity, BiFunction<U,? super  T,U> accumulator, BinaryOperator<U> combiner)

以下代码显示了如何顺序并行reduce操作工作。

import java.time.LocalDate;
import java.time.Month;
import java.util.Arrays;
import java.util.List;

public class Main {
  public static void main(String[] args) {
    double sum = Employee
        .persons()
        .stream()
        .reduce(
            0.0,
            (Double partialSum, Employee p) -> {
              double accumulated = partialSum + p.getIncome();
              System.out.println(Thread.currentThread().getName()
                  + "  - Accumulator: partialSum  = " + partialSum
                  + ",  person = " + p + ", accumulated = " + accumulated);
              return accumulated;
            },
            (a, b) -> {
              double combined = a + b;
              System.out.println(Thread.currentThread().getName()
                  + "  - Combiner:  a  = " + a + ", b  = " + b
                  + ", combined  = " + combined);
              return combined;
            });
    System.out.println("--------------------------------------");
    System.out.println(sum);

    sum = Employee
        .persons()
        .parallelStream()
        .reduce(
            0.0,
            (Double partialSum, Employee p) -> {
              double accumulated = partialSum + p.getIncome();
              System.out.println(Thread.currentThread().getName()
                  + "  - Accumulator: partialSum  = " + partialSum
                  + ",  person = " + p + ", accumulated = " + accumulated);
              return accumulated;
            },
            (a, b) -> {
              double combined = a + b;
              System.out.println(Thread.currentThread().getName()
                  + "  - Combiner:  a  = " + a + ", b  = " + b
                  + ", combined  = " + combined);
              return combined;
            });
    System.out.println(sum);
  }
}
class Employee {
  public static enum Gender {
    MALE, FEMALE
  }
  private long id;
  private String name;
  private Gender gender;
  private LocalDate dob;
  private double income;

  public Employee(long id, String name, Gender gender, LocalDate dob,
      double income) {
    this.id = id;
    this.name = name;
    this.gender = gender;
    this.dob = dob;
    this.income = income;
  }
  public double getIncome() {
    return income;
  }
  public static List<Employee> persons() {
    Employee p1 = new Employee(1, "Jake", Gender.MALE, LocalDate.of(1971,
        Month.JANUARY, 1), 2343.0);
    Employee p2 = new Employee(2, "Jack", Gender.MALE, LocalDate.of(1972,
        Month.JULY, 21), 7100.0);
    Employee p3 = new Employee(3, "Jane", Gender.FEMALE, LocalDate.of(1973,
        Month.MAY, 29), 5455.0);
    Employee p4 = new Employee(4, "Jode", Gender.MALE, LocalDate.of(1974,
        Month.OCTOBER, 16), 1800.0);
    Employee p5 = new Employee(5, "Jeny", Gender.FEMALE, LocalDate.of(1975,
        Month.DECEMBER, 13), 1234.0);
    Employee p6 = new Employee(6, "Jason", Gender.MALE, LocalDate.of(1976,
        Month.JUNE, 9), 3211.0);

    List<Employee> persons = Arrays.asList(p1, p2, p3, p4, p5, p6);

    return persons;
  }
}

上面的代码生成以下结果。

流reduce没有默认值

第三个版本的reduce()如下列方法用于执行没有默认值的缩减操作。

reduce(BinaryOperator<T> accumulator)

如果流是空的，我们不能使用默认值为0。

Optional<T>
用于包装结果或不存在结果。

以下代码显示如何计算流中的整数的最大值:

import java.util.Optional;
import java.util.stream.Stream;

public class Main {
  public static void main(String[] args) {
    Optional<Integer> max = Stream.of(1, 2, 3, 4, 5).reduce(Integer::max);

    if (max.isPresent()) {
      System.out.println("max = " + max.get());
    } else {
      System.out.println("max is not  defined.");
    }
    
    max = Stream.<Integer> empty().reduce(Integer::max);
    if (max.isPresent()) {
      System.out.println("max = " + max.get());
    } else {
      System.out.println("max is not  defined.");
    }
    
  }
}

上面的代码生成以下结果。

例5

以下代码打印员工列表中最高收入者的详细信息。

import java.time.LocalDate;
import java.time.Month;
import java.util.Arrays;
import java.util.List;
import java.util.Optional;

public class Main {
  public static void main(String[] args) {
    Optional<Employee> person = Employee
        .persons()
        .stream()
        .reduce((p1, p2) -> p1.getIncome() > p2.getIncome() ? p1 : p2);
    if (person.isPresent()) {
      System.out.println("Highest earner: " + person.get());
    } else {
      System.out.println("Could not  get   the   highest earner.");
    }
  }
}

class Employee {
  public static enum Gender {
    MALE, FEMALE
  }

  private long id;
  private String name;
  private Gender gender;
  private LocalDate dob;
  private double income;

  public Employee(long id, String name, Gender gender, LocalDate dob,
      double income) {
    this.id = id;
    this.name = name;
    this.gender = gender;
    this.dob = dob;
    this.income = income;
  }
  public double getIncome() {
    return income;
  }
  public static List<Employee> persons() {
    Employee p1 = new Employee(1, "Jake", Gender.MALE, LocalDate.of(1971,
        Month.JANUARY, 1), 2343.0);
    Employee p2 = new Employee(2, "Jack", Gender.MALE, LocalDate.of(1972,
        Month.JULY, 21), 7100.0);
    Employee p3 = new Employee(3, "Jane", Gender.FEMALE, LocalDate.of(1973,
        Month.MAY, 29), 5455.0);
    Employee p4 = new Employee(4, "Jode", Gender.MALE, LocalDate.of(1974,
        Month.OCTOBER, 16), 1800.0);
    Employee p5 = new Employee(5, "Jeny", Gender.FEMALE, LocalDate.of(1975,
        Month.DECEMBER, 13), 1234.0);
    Employee p6 = new Employee(6, "Jason", Gender.MALE, LocalDate.of(1976,
        Month.JUNE, 9), 3211.0);

    List<Employee> persons = Arrays.asList(p1, p2, p3, p4, p5, p6);

    return persons;
  }

  @Override
  public String toString() {
    String str = String.format("(%s, %s,  %s,  %s,  %.2f)\n", id, name, gender,
        dob, income);
    return str;
  }
}

上面的代码生成以下结果。