Stream

Stream（流）是一个来自数据源的元素队列并支持聚合操作

元素是特定类型的对象，形成一个队列。 Java中的Stream并不会存储元素，而是按需计算。
数据源流的来源。可以是集合，数组，I/O channel，产生器generator 等。
聚合操作类似SQL语句一样的操作，比如filter, map, reduce, find, match, sorted等。

和以前的Collection操作不同， Stream操作还有两个基础的特征：

Pipelining: 中间操作都会返回流对象本身。这样多个操作可以串联成一个管道，如同流式风格（fluent style）。这样做可以对操作进行优化，比如延迟执行(laziness)和短路( short-circuiting)。
内部迭代：以前对集合遍历都是通过Iterator或者For-Each的方式, 显式的在集合外部进行迭代，这叫做外部迭代。 Stream提供了内部迭代的方式，通过访问者模式(Visitor)实现。

Stream操作步骤如下：

创建Stream

在 Java 8 中, 集合接口有两个方法来生成流：

stream() − 为集合创建串行流。

parallelStream() − 为集合创建并行流。

中间操作，如map()方法、flatMap()方法、filter()方法，返回的是符合条件的流
终止操作，allMatch()、findFirst()、count()等方法，返回的是我们需要的具体的结果

Employee类

package com.wqh.demo.java8;

public class Employee {

	private int id;
	private String name;
	private int age;
	private double salary;
	private Status status;

	public Employee() {
	}

	public Employee(String name) {
		this.name = name;
	}

	public Employee(String name, int age) {
		this.name = name;
		this.age = age;
	}

	public Employee(int id, String name, int age, double salary) {
		this.id = id;
		this.name = name;
		this.age = age;
		this.salary = salary;
	}

	public Employee(int id, String name, int age, double salary, Status status) {
		this.id = id;
		this.name = name;
		this.age = age;
		this.salary = salary;
		this.status = status;
	}

	public Status getStatus() {
		return status;
	}

	public void setStatus(Status status) {
		this.status = status;
	}

	public int getId() {
		return id;
	}

	public void setId(int id) {
		this.id = id;
	}

	public String getName() {
		return name;
	}

	public void setName(String name) {
		this.name = name;
	}

	public int getAge() {
		return age;
	}

	public void setAge(int age) {
		this.age = age;
	}

	public double getSalary() {
		return salary;
	}

	public void setSalary(double salary) {
		this.salary = salary;
	}

	public String show() {
		return "测试方法引用！";
	}

	@Override
	public int hashCode() {
		final int prime = 31;
		int result = 1;
		result = prime * result + age;
		result = prime * result + id;
		result = prime * result + ((name == null) ? 0 : name.hashCode());
		long temp;
		temp = Double.doubleToLongBits(salary);
		result = prime * result + (int) (temp ^ (temp >>> 32));
		return result;
	}

	@Override
	public boolean equals(Object obj) {
		if (this == obj)
			return true;
		if (obj == null)
			return false;
		if (getClass() != obj.getClass())
			return false;
		Employee other = (Employee) obj;
		if (age != other.age)
			return false;
		if (id != other.id)
			return false;
		if (name == null) {
			if (other.name != null)
				return false;
		} else if (!name.equals(other.name))
			return false;
		if (Double.doubleToLongBits(salary) != Double.doubleToLongBits(other.salary))
			return false;
		return true;
	}

	@Override
	public String toString() {
		return "Employee [id=" + id + ", name=" + name + ", age=" + age + ", salary=" + salary + ", status=" + status
				+ "]";
	}

	public enum Status {
		FREE, BUSY, VOCATION;
	}

}

创建Stream和中间操作

package com.wqh.demo.java8;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;

import org.junit.Test;

/*
 * 一、 Stream 的操作步骤
 * 
 * 1. 创建 Stream
 * 
 * 2. 中间操作
 * 
 * 3. 终止操作
 */
public class TestStreamAPI1 {
   
   List<Employee> emps = Arrays.asList(
         new Employee(102, "李四", 59, 6666.66),
         new Employee(101, "张三", 18, 9999.99),
         new Employee(103, "王五", 28, 3333.33),
         new Employee(104, "赵六", 8, 7777.77),
         new Employee(104, "赵六", 8, 7777.77),
         new Employee(104, "赵六", 8, 7777.77),
         new Employee(105, "田七", 38, 5555.55)
   );
   
   //2. 中间操作
   /*
      映射
      map——接收 Lambda ， 将元素转换成其他形式或提取信息。接收一个函数作为参数，该函数会被应用到每个元素上，并将其映射成一个新的元素。
      flatMap——接收一个函数作为参数，将流中的每个值都换成另一个流，然后把所有流连接成一个流
    */
   @Test
   public void test1(){
      // map()方法返回的是只有name的流
      Stream<String> str = emps.stream()
         .map((e) -> e.getName());

      System.out.println(str);

      System.out.println("-------------------------------------------");
      
      List<String> strList = Arrays.asList("aaa", "bbb", "ccc", "ddd", "eee");
      // map()方法返回的是每个元素都是经过大写操作的流
      Stream<String> stream = strList.stream()
            .map(String::toUpperCase);
      
      stream.forEach(System.out::println);
      
      Stream<Stream<Character>> stream2 = strList.stream()
            .map(TestStreamAPI1::filterCharacter);
      
      stream2.forEach((sm) -> {
         sm.forEach(System.out::println);
      });
      
      System.out.println("---------------------------------------------");
      
      Stream<Character> stream3 = strList.stream()
            .flatMap(TestStreamAPI1::filterCharacter);
      
      stream3.forEach(System.out::println);
   }

   public static Stream<Character> filterCharacter(String str){
      List<Character> list = new ArrayList<>();
      
      for (Character ch : str.toCharArray()) {
         list.add(ch);
      }
      
      return list.stream();
   }
   
   /*
       中间操作
      sorted()——自然排序
      sorted(Comparator com)——定制排序
    */
   @Test
   public void test2(){
      emps.stream()
         .map(Employee::getName)
         .sorted()
         .forEach(System.out::println);
      
      System.out.println("------------------------------------");
      
      emps.stream()
         .sorted((x, y) -> {
            if(x.getAge() == y.getAge()){
               return x.getName().compareTo(y.getName());
            }else{
               return Integer.compare(x.getAge(), y.getAge());
            }
         }).forEach(System.out::println);
   }
}

终止操作来得到我们需要的结果

package com.wqh.demo.java8;

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

import org.junit.Test;

import com.wqh.demo.java8.Employee.Status;

/*
 * 一、 Stream 的操作步骤
 * 
 * 1. 创建 Stream
 * 
 * 2. 中间操作
 * 
 * 3. 终止操作
 */
public class TestStreamAPI2 {
   
   List<Employee> emps = Arrays.asList(
         new Employee(102, "李四", 59, 6666.66, Status.BUSY),
         new Employee(101, "张三", 18, 9999.99, Status.FREE),
         new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
         new Employee(104, "赵六", 8, 7777.77, Status.BUSY),
         new Employee(104, "赵六", 8, 7777.77, Status.FREE),
         new Employee(104, "赵六", 8, 7777.77, Status.FREE),
         new Employee(105, "田七", 38, 5555.55, Status.BUSY)
   );
   
   //3. 终止操作
   /*
      allMatch——检查是否匹配所有元素
      anyMatch——检查是否至少匹配一个元素
      noneMatch——检查是否没有匹配的元素
      findFirst——返回第一个元素
      findAny——返回当前流中的任意元素
      count——返回流中元素的总个数
      max——返回流中最大值
      min——返回流中最小值
    */
   @Test
   public void test1(){
         boolean bl = emps.stream()
            .allMatch((e) -> e.getStatus().equals(Status.BUSY));
         
         System.out.println(bl);
         
         boolean bl1 = emps.stream()
            .anyMatch((e) -> e.getStatus().equals(Status.BUSY));
         
         System.out.println(bl1);
         
         boolean bl2 = emps.stream()
            .noneMatch((e) -> e.getStatus().equals(Status.BUSY));
         
         System.out.println(bl2);
   }
   
   @Test
   public void test2(){
      Optional<Employee> op = emps.stream()
         .sorted((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()))
         .findFirst();
      
      System.out.println(op.get());
      
      System.out.println("--------------------------------");
      
      Optional<Employee> op2 = emps.parallelStream()
         .filter((e) -> e.getStatus().equals(Status.FREE))
         .findAny();
      
      System.out.println(op2.get());
   }
   
   @Test
   public void test3(){
      long count = emps.stream()
                   .filter((e) -> e.getStatus().equals(Status.FREE))
                   .count();
      
      System.out.println(count);
      
      Optional<Double> op = emps.stream()
         .map(Employee::getSalary)
         .max(Double::compare);
      
      System.out.println(op.get());
      
      Optional<Employee> op2 = emps.stream()
         .min((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()));
      
      System.out.println(op2.get());
   }
   
   //注意：流进行了终止操作后，不能再次使用
   @Test
   public void test4(){
      Stream<Employee> stream = emps.stream()
       .filter((e) -> e.getStatus().equals(Status.FREE));
      
      long count = stream.count();
      
      stream.map(Employee::getSalary)
         .max(Double::compare);
   }
}

package com.wqh.demo.java8;

import java.util.Arrays;
import java.util.DoubleSummaryStatistics;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.Set;
import java.util.stream.Collectors;

import org.junit.Test;

import com.wqh.demo.java8.Employee.Status;

public class TestStreamAPI3 {
   
   List<Employee> emps = Arrays.asList(
         new Employee(102, "李四", 79, 6666.66, Status.BUSY),
         new Employee(101, "张三", 18, 9999.99, Status.FREE),
         new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
         new Employee(104, "赵六", 8, 7777.77, Status.BUSY),
         new Employee(104, "赵六", 8, 7777.77, Status.FREE),
         new Employee(104, "赵六", 8, 7777.77, Status.FREE),
         new Employee(105, "田七", 38, 5555.55, Status.BUSY)
   );
   
   //3. 终止操作
   /*
      归约
      reduce(T identity, BinaryOperator) / reduce(BinaryOperator) ——可以将流中元素反复结合起来，得到一个值。
    */
   @Test
   public void test1(){
      List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8,9,10);
      
      Integer sum = list.stream()
         .reduce(0, (x, y) -> x * y);
      
      System.out.println(sum);
      
      System.out.println("----------------------------------------");
      
      Optional<Double> op = emps.stream()
         .map(Employee::getSalary)
         .reduce(Double::sum);
      
      System.out.println(op.get());
   }
   
   //需求：搜索名字中 “六” 出现的次数
   @Test
   public void test2(){
      Optional<Integer> sum = emps.stream()
         .map(Employee::getName)
         .flatMap(TestStreamAPI1::filterCharacter)
         .map((ch) -> {
            if(ch.equals('六')) {
               return 1;
            } else {
               return 0;
            }
         }).reduce(Integer::sum);
      
      System.out.println(sum.get());
   }
   
   //collect——将流转换为其他形式。接收一个 Collector接口的实现，用于给Stream中元素做汇总的方法
   @Test
   public void test3(){
      List<String> list = emps.stream()
         .map(Employee::getName)
         .collect(Collectors.toList());
      
      list.forEach(System.out::println);
      
      System.out.println("----------------------------------");
      
      Set<String> set = emps.stream()
         .map(Employee::getName)
         .collect(Collectors.toSet());
      
      set.forEach(System.out::println);

      System.out.println("----------------------------------");
      
      HashSet<String> hs = emps.stream()
         .map(Employee::getName)
         .collect(Collectors.toCollection(HashSet::new));
      
      hs.forEach(System.out::println);
   }
   
   @Test
   public void test4(){
      Optional<Double> max = emps.stream()
         .map(Employee::getSalary)
         .collect(Collectors.maxBy(Double::compare));
      
      System.out.println(max.get());
      
      Optional<Employee> op = emps.stream()
         .collect(Collectors.minBy((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary())));
      
      System.out.println(op.get());
      
      Double sum = emps.stream()
         .collect(Collectors.summingDouble(Employee::getSalary));
      
      System.out.println(sum);
      
      Double avg = emps.stream()
         .collect(Collectors.averagingDouble(Employee::getSalary));
      
      System.out.println(avg);
      
      Long count = emps.stream()
         .collect(Collectors.counting());
      
      System.out.println(count);
      
      System.out.println("--------------------------------------------");
      
      DoubleSummaryStatistics dss = emps.stream()
         .collect(Collectors.summarizingDouble(Employee::getSalary));
      
      System.out.println(dss.getMax());
   }
   
   //分组
   @Test
   public void test5(){
      Map<Status, List<Employee>> map = emps.stream()
         .collect(Collectors.groupingBy(Employee::getStatus));
      
      System.out.println(map);
   }
   
   //多级分组
   @Test
   public void test6(){
      Map<Status, Map<String, List<Employee>>> map = emps.stream()
         .collect(Collectors.groupingBy(Employee::getStatus, Collectors.groupingBy((e) -> {
            if (e.getAge() >= 60) {
               return "老年";
            } else if (e.getAge() >= 35) {
               return "中年";
            } else {
               return "成年";
            }
         })));
      
      System.out.println(map);
   }
   
   //分区
   @Test
   public void test7(){
      Map<Boolean, List<Employee>> map = emps.stream()
         .collect(Collectors.partitioningBy((e) -> e.getSalary() >= 5000));
      
      System.out.println(map);
   }
   
   //
   @Test
   public void test8(){
      String str = emps.stream()
         .map(Employee::getName)
         .collect(Collectors.joining("," , "----", "----"));
      
      System.out.println(str);
   }
   
   @Test
   public void test9(){
      Optional<Double> sum = emps.stream()
         .map(Employee::getSalary)
         .collect(Collectors.reducing(Double::sum));
      
      System.out.println(sum.get());
   }
}

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