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java8Stream

Stream

介绍

java8添加了一个抽象流Stream,可以让我们像写sql一样操作集合元素。Stream将要处理的元素看做是一种流, 在管道中传输,并进行处理,最后由终止操作得到处理的结果。

什么是Stream?

Stream是一个来自特定元素队列并支持聚合操作

  • 元素是具体类型的对象,形成一个队列。
  • 数据源是流的来源。
  • 聚合操作是类似sql一样的操作,比如filter, map, reduce, find, match, sorted等。
  • Stream自己不会存储元素。
  • Stream不会改变源对象。
  • Stream操作是延迟执行的。

创建流

串行流

stream():即单线程的方式去操作流

并行流

parallelStream():即多线程方式去操作流

@Test
	public void test() {
		//1通过Collection提供的stream()和parallelStream()方法
		List<String> list = Arrays.asList("a","b","c");
		Stream<String> stream1 = list.stream();
		Stream<String> stream2 = list.parallelStream();
		
		//2通过Arrays的静态方法stream()
		String[] strs= {"a","b","c"};
		Stream<String> stream3 = Arrays.stream(strs);
		
		//3通过Stream类中的静态方法of()
		Stream<String> stream4 = Stream.of("a","b","c");
		
		//4通过Stream类的iterate方法生成无限流
		Stream<Integer> stream5 = Stream.iterate(0, (x)->x+1);
		
		//5通过Stream的generate方法生成无限流
		Stream.generate(()->Math.random());
		
	}

中间操作

过滤

使用 filter(Predicate<? super T> predicate)来按照一定规则对流中元素进行过滤

@Test
	public void test() {
		List<Integer> list = Arrays.asList(1,2,3,4,5);
		Stream<Integer> stream = list.stream();
		stream = stream.filter((x)->x.compareTo(2)>0);
		
		stream.forEach(System.out::println);
	}
输出:
3
4
5

@Test
	public void test2() {
		List<Integer> list = Arrays.asList(1,2,3,4,5);
		Stream<Integer> stream = list.stream();
		stream = stream.filter(
				(x)->{
			System.out.println(x);
			return x.compareTo(2)>0;}
			);
	}
结果:没有任何输出,这也就是前面说的Stream操作是延迟执行的,只有当终止操作这些中间操作才会依次执行

截断

使元素的个数不超过指定的数目

@Test
	public void test() {
		List<Integer> list = Arrays.asList(1,2,3,4,5);
		Stream<Integer> stream = list.stream();
		stream=stream.limit(3);
		stream.forEach(System.out::println);
	}
输出:
1
2
3
可以看到只输出了给定个元素

跳过元素

跳过流中前几个元素

@Test
	public void test4() {
		List<Integer> list = Arrays.asList(1,2,3,4,5);
		Stream<Integer> stream = list.stream();
		stream=stream.skip(2);
		stream.forEach(System.out::println);
	}
输出:
3
4
5
跳过了前两个元素

唯一筛选

两个元素通过hashCode()判断两个元素是否相同

@Test
	public void test5() {
		List<Integer> list = Arrays.asList(1,2,3,4,5,5);
		Stream<Integer> stream = list.stream();
		stream.distinct().forEach(System.out::println);
	}
输出:
1
2
3
4
5

映射

map(method)接受一个方法,把流中的元素按照方法进行转换

@Test
	public void test() {
		List<String> list = Arrays.asList("a","b","c");
		Stream<String> stream = list.stream();
		stream=stream.map((x)->x.toUpperCase());
		stream.forEach(System.out::println);
	}
输出:
A
B
C

flatMap(method)也是接受一个函数作为参数,但是与map,不同的是如果这个函数生成的本来就是流,它会把函数生成流中的元素加到流中

//这个函数本身就生成流
public static Stream<Character> toStream(String s){
  List<Character> list=new ArrayList<Character>();
  char[] chs = s.toCharArray();
  for (char c : chs) {
    list.add(c);
  }
  Stream<Character> stream = list.stream();
  return stream;
}
@Test
public void test() {
  List<String> list = Arrays.asList("aaa","bbb","ccc");
  Stream<Stream<Character>> stream = 
  //由于函数本身就生成流,所以流中加入的还是流
  list.stream().map(StreamTest::toStream);
  //遍历的时候需要先从流中取出流,在遍历
  stream.forEach((s)->s.forEach(System.out::println));
}

//然而我们可以使用flatMap进行改进
@Test
public void test() {
  List<String> list = Arrays.asList("aaa","bbb","ccc");
  list.stream().flatMap(StreamTest::toStream).forEach(System.out::println);
}
输出:
a
a
a
b
b
b
c
c
c

终止操作

所有匹配

当所有元素都匹配时,allMatch(Predicate<? super T> predicate)才会返回true

@Test
public void test() {
  List<String> list = Arrays.asList("aaa","bbb","ccc");
  boolean allMatch = list.stream().allMatch((s)->s.length()>2);
  System.out.println(allMatch);
}
输出:
true

任一匹配

当Stream中任一一个元素匹配时,anyMatch(Predicate<? super T> predicate)返回true

@Test
public void test() {
  List<String> list = Arrays.asList("aaa","bbb","ccc");
  boolean anyMatch = list.stream().anyMatch((s)->s.equals("bbb"));
  System.out.println(anyMatch);
}
输出:
true

所有不匹配

当Stream中所有的元素都不匹配时,noneMatch(Predicate<? super T> predicate)返回true

@Test
public void test() {
  List<String> list = Arrays.asList("aaa","bbb","ccc");
  boolean noneMatch = list.stream().noneMatch((s)->s.equals("ddd"));
  System.out.println(noneMatch);
}
输出:
true

第一个元素

返回当前流中的第一个元素

@Test
public void test() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  Optional<Integer> findFirst = list.stream().findFirst();
  System.out.println(findFirst.get());
}
输出:
1

任一一个元素

返回当前流中的任一一个元素

@Test
public void test() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  Optional<Integer> findAny = list.stream().findAny();
  System.out.println(findAny.get());
}
输出:
1

//使用并行流试试
@Test
public void test13() {
	List<Integer> list = Arrays.asList(1,2,3,4,5);
	Optional<Integer> findAny =   		list.parallelStream().findAny();
	System.out.println(findAny.get());
}
输出:
3

流中元素个数

返回流中的元素个数

@Test
public void test14() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  long count = list.stream().count();
  System.out.println(count);
}
输出:
5

流中的最大值

返回流中元素的最大值

@Test
public void test15() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  Optional<Integer> max = list.stream().max(Integer::compare);
  System.out.println(max.get());
}
输出:
5

流中的最小值

返回流中的最小值

@Test
public void test16() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  Optional<Integer> min = list.stream().min(Integer::compare);
  System.out.println(min.get());
}
输出:
1

规约

将流中的元素反复结合得到一个最终值

@Test
public void test() {
  List<Integer> list = Arrays.asList(1,2,3,4,5);
  Optional<Integer> reduce = list.stream().reduce(Integer::sum);
  System.out.println(reduce.get());

  Integer reduce2 = list.stream().reduce(0, (x,y)->{
    System.out.println(x+"->"+y);
    return x+y;
  });
  System.out.println(reduce2);
}
输出:
15
0->1
1->2
3->3
6->4
10->5
15

可以看到当使用(T identity, BinaryOperator accumulator)时,identity即为最初和流中元素进行运算的,所以值不能为空,所以返回的不是Optional

收集

将流转换成其他形式

@Test
public void test() {
  List<Integer> list = Arrays.asList(1,2,3,4,5,5);
  Set<Integer> collect = list.stream().collect(Collectors.toSet());
  System.out.println(collect);
}
输出:
[1, 2, 3, 4, 5]

@Test
public void test() {
		List<Integer> list = Arrays.asList(1,2,3,4,5,5);
		Optional<Integer> collect = list.stream().collect(Collectors.maxBy(Integer::compareTo));
		System.out.println(collect.get());
}
输出:
5

class Stu{
	String name;
	Integer age;
	String gender;
	public Stu(String name, Integer age, String gender) {
		super();
		this.name = name;
		this.age = age;
		this.gender = gender;
	}
	public String getName() {
		return name;
	}
	public void setName(String name) {
		this.name = name;
	}
	public Integer getAge() {
		return age;
	}
	public void setAge(Integer age) {
		this.age = age;
	}
	public String getGender() {
		return gender;
	}
	public void setGender(String gender) {
		this.gender = gender;
	}
	@Override
	public String toString() {
		return "Stu [name=" + name + ", age=" + age + ", gender=" + gender + "]";
	}
	
}
//一级分组
@Test
	public void test() {
		List<Stu> list = Arrays.asList(
				new Stu("张三",20,"男"),
				new Stu("李四",22,"女"),
				new Stu("王五",18,"男"),
				new Stu("赵六",20,"女"),
				new Stu("田七",22,"女")
				);
		Map<String, List<Stu>> collect = 				list.stream().collect(Collectors.groupingBy(Stu::getGender));
		System.out.println(collect);
	}
输出:
{女=[Stu [name=李四, age=22, gender=女], Stu [name=赵六, age=20, gender=女], Stu [name=田七, age=22, gender=女]], 男=[Stu [name=张三, age=20, gender=男], Stu [name=王五, age=18, gender=男]]}

//二级分组
@Test
public void test21() {
  List<Stu> list = Arrays.asList(
    new Stu("张三",20,"男"),
    new Stu("李四",22,"女"),
    new Stu("王五",18,"男"),
    new Stu("赵六",20,"女"),
    new Stu("田七",22,"女")
  );
  Map<Integer, Map<String, List<Stu>>> collect = list.stream()
    .collect(Collectors.groupingBy(Stu::getAge, Collectors.groupingBy(Stu::getGender)));
  System.out.println(collect);
}
输出:
{18={男=[Stu [name=王五, age=18, gender=男]]}, 20={女=[Stu [name=赵六, age=20, gender=女]], 男=[Stu [name=张三, age=20, gender=男]]}, 22={女=[Stu [name=李四, age=22, gender=女], Stu [name=田七, age=22, gender=女]]}}

//分区
@Test
public void test22() {
  List<Stu> list = Arrays.asList(
    new Stu("张三",20,"男"),
    new Stu("李四",22,"女"),
    new Stu("王五",18,"男"),
    new Stu("赵六",20,"女"),
    new Stu("田七",22,"女")
  );
  Map<Boolean, List<Stu>> collect = list.stream()
    .collect(Collectors.partitioningBy((e)->((Stu)e).getAge()>20));
  System.out.println(collect);
}
输出:
{false=[Stu [name=张三, age=20, gender=男], Stu [name=王五, age=18, gender=男], Stu [name=赵六, age=20, gender=女]], true=[Stu [name=李四, age=22, gender=女], Stu [name=田七, age=22, gender=女]]}
原文  http://www.cnblogs.com/moyuduo/p/12616827.html
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