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Stream流详解

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JDK8 Stream详解

概念

Stream是Java8 API的新成员,它允许以声明性方式处理数据集合 。

特点

(1)代码简洁:函数式编程写出的代码简洁且意图明确,使用stream接口让你从此告别for循环。

(2)多核友好:Java函数式编程使得编写并行程序从未如此简单,你需要的全部就是调用一下方法。

流程

1)第一步:把集合转换为流stream
2)第二步:操作stream流
stream流在管道中经过中间操作(intermediate operation)的处理,最后由最终操作(terminal operation)得到前面处理的结果

操作符

两种:中间操作符、终止操作符

中间操作符

流方法含义示例
filter用于通过设置的条件过滤出元素List strings = Arrays.asList(“abc”, “”, “bc”, “efg”, “abcd”,"", “jkl”);List filtered = strings.stream().filter(string -> !string.isEmpty()).collect(Collectors.toList());
distinct返回一个元素各异(根据流所生成元素的hashCode和equals方法实现)的流。List numbers = Arrays.asList(1, 2, 1, 3, 3, 2, 4);numbers.stream().filter(i -> i % 2 == 0).distinct().forEach(System.out::println);
limit会返回一个不超过给定长度的流。List strings = Arrays.asList(“abc”, “abc”, “bc”, “efg”, “abcd”,“jkl”, “jkl”);List limited = strings.stream().limit(3).collect(Collectors.toList());
skip返回一个扔掉了前n个元素的流。List strings = Arrays.asList(“abc”, “abc”, “bc”, “efg”, “abcd”,“jkl”, “jkl”);List skiped = strings.stream().skip(3).collect(Collectors.toList());
map接受一个函数作为参数。这个函数会被应用到每个元素上,并将其映射成一个新的元素(使用映射一词,是因为它和转换类似,但其中的细微差别在于它是“创建一个新版本”而不是去“修改”)。List strings = Arrays.asList(“abc”, “abc”, “bc”, “efg”, “abcd”,“jkl”, “jkl”);List mapped = strings.stream().map(str->str+"-itcast").collect(Collectors.toList());
flatMap使用flatMap方法的效果是,各个数组并不是分别映射成一个流,而是映射成流的内容。所有使用map(Arrays::stream)时生成的单个流都被合并起来,即扁平化为一个流。List strings = Arrays.asList(“abc”, “abc”, “bc”, “efg”, “abcd”,“jkl”, “jkl”);Stream flatMap = strings.stream().flatMap(Java8StreamTest::getCharacterByString);
sorted返回排序后的流List strings1 = Arrays.asList(“abc”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);List sorted1 = strings1.stream().sorted().collect(Collectors.toList());

示例代码:

1)filter

/**
 * 功能描述:根据条件过滤集合数据
 * @return : void
 */
@Test
public void filter(){
    List<String> strings = Arrays.asList("abc", "", "bc", "efg", "abcd","", "jkl");
    List<String> filtered = strings.stream().filter(string -> !string.isEmpty()).collect(Collectors.toList());
    out.println(filtered);
}

2)distinct

/**
 * 功能描述:去除集合中重复数据
 * @return : void
 */
@Test
public void distinct(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    List<String> distincted = strings.stream().distinct().collect(Collectors.toList());
    out.println(distincted);
}

3)limit

/**
 * 功能描述:指定获取集合前x条数据,重新构造一个新的集合
 * @return : void
 */
@Test
public void limit(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    List<String> limited = strings.stream().limit(3).collect(Collectors.toList());
    out.println(limited);
}

4)skip

/**
 * 功能描述:排除集合前x条数据,把后面的数据重新构造一个新的集合
 * @return : void
 */
@Test
    public void skip(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    List<String> skiped = strings.stream().skip(3).collect(Collectors.toList());
    out.println(skiped);
}

5)map

/**
 * 功能描述:对集合中所有元素统一处理
 * @return : void
 */
@Test
public void map(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    List<String> mapped = strings.stream().map(str->str+"-itcast").collect(Collectors.toList());
    out.println(mapped);
}

6)flatMap

/**
 * 功能描述:对集合中所有元素统一处理
 * @return : void
 */
@Test
public void flatMap(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    Stream<String> stringStream = strings.stream().map(x -> x);
    Stream<String> stringStream1 = strings.stream().flatMap(x -> Arrays.asList(x.split(" ")).stream());
}

7)sorted

/**
 * 功能描述 : 对集合进行排序
 * @return : void
 */
@Test
public void sorted(){
    List<String> strings1 = Arrays.asList("abc", "abd", "aba", "efg", "abcd","jkl", "jkl");
    List<String> strings2 = Arrays.asList("张三", "李四", "王五", "赵柳", "张哥","李哥", "王哥");
    List<Integer> strings3 = Arrays.asList(10, 2, 30, 22, 1,0, -9);
    List<String> sorted1 = strings1.stream().sorted().collect(Collectors.toList());
    List<String> sorted2 = strings2.stream().sorted(Collections.reverseOrder(Collator.getInstance(Locale.CHINA))).collect(Collectors.toList());
    List<Integer> sorted3 = strings3.stream().sorted().collect(Collectors.toList());
    out.println(sorted1);
    out.println(sorted2);
    out.println(sorted3);
}

Map、flatMap区别

map:对流中每一个元素进行处理
flatMap:流扁平化,让你把一个流中的“每个值”都换成另一个流,然后把所有的流连接起来成为一个流 
总结:map是对一级元素进行操作,flatmap是对二级元素操作。

本质区别:map返回一个值;flatmap返回一个流,多个值。

应用场景:map对集合中每个元素加工,返回加工后结果;flatmap对集合中每个元素加工后,做扁平化处理后(拆分层级,放到同一层)然后返回


/**
 * 方法一
 * 功能描述:  通过使用map、flatMap把字符串转换为字符输出对比区别
 * @return : void
 */
@Test
public void flatMap2Map(){
    List<String> strings = Arrays.asList("abc", "abc", "bc", "efg", "abcd","jkl", "jkl");
    final Stream<Character> flatMap = strings.stream().flatMap(Java8StreamTest::getCharacterByString);
    flatMap.forEach(System.out::println);
    //----------------------------------------------
    final Stream<Stream<Character>> mapStream = strings.stream().map(Java8StreamTest::getCharacterByString);
    //mapStream.forEach(System.out::println);
    out.println("------------------------------------------------");
    mapStream.forEach(stream-> {stream.forEach(character->{System.out.println(character);});});

}

公共方法(字符串转换为字符流)

/**
* 功能描述:字符串转换为字符流
* @param str
* @return : java.util.stream.Stream<java.lang.Character>
*/
public static Stream<Character> getCharacterByString(String str) {
    List<Character> characterList = new ArrayList<>();
    for (Character character : str.toCharArray()) {
    	characterList.add(character);
    }
    return characterList.stream();
}

终止操作符

流方法含义示例
anyMatch检查是否至少匹配一个元素,返回boolean。List strings = Arrays.asList(“abc”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);boolean b = strings.stream().anyMatch(s -> s == “abc”);
allMatch检查是否匹配所有元素,返回boolean。List strings = Arrays.asList(“abc”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);boolean b = strings.stream().allMatch(s -> s == “abc”);
noneMatch检查是否没有匹配所有元素,返回boolean。List strings = Arrays.asList(“abc”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);boolean b = strings.stream().noneMatch(s -> s == “abc”);
findAny将返回当前流中的任意元素。List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);Optional any = strings.stream().findAny();
findFirst返回第一个元素List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);Optional first = strings.stream().findFirst();
forEach遍历流List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);strings.stream().forEach(s -> out.println(s));
collect收集器,将流转换为其他形式。List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);Set set = strings.stream().collect(Collectors.toSet());List list = strings.stream().collect(Collectors.toList());Map<String, String> map = strings.stream().collect(Collectors.toMap(v ->v.concat("_name"), v1 -> v1, (v1, v2) -> v1));
reduce可以将流中元素反复结合起来,得到一个值。List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);Optional reduce = strings.stream().reduce((acc,item) -> {return acc+item;});if(reduce.isPresent())out.println(reduce.get());
count返回流中元素总数。List strings = Arrays.asList(“cv”, “abd”, “aba”, “efg”, “abcd”,“jkl”, “jkl”);long count = strings.stream().count();

示例代码

1)anyMatch

/**
 * 功能描述 : 判断集合中是否至少存在一个元素满足条件
 * @return : void
 */
@Test
public void anyMatch(){
    List<String> strings = Arrays.asList("abc", "abd", "aba", "efg", "abcd","jkl", "jkl");
    boolean b = strings.stream().anyMatch(s -> s == "abc");
    out.println(b);
}

2)allMatch

/**
 * 功能描述 : 判断集合中是否所有元素都满足条件
 * @return : void
 */
@Test
public void allMatch(){
    List<String> strings = Arrays.asList("abc", "abd", "aba", "efg", "abcd","jkl", "jkl");
    boolean b = strings.stream().allMatch(s -> s == "abc");
    out.println(b);
}

3)noneMatch

/**
 * 功能描述 : 判断集合中是否所有元素都不满足条件
 * @return : void
 */
@Test
public void noneMatch(){
    List<String> strings = Arrays.asList("abc", "abd", "aba", "efg", "abcd","jkl", "jkl");
    boolean b = strings.stream().noneMatch(s -> s == "abc");
    out.println(b);
}

4)findAny

/**
 * 功能描述 : 返回当前流中任意元素
 * @return : void
 */
@Test
public void findAny(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    Optional<String> any = strings.stream().findAny();
    if(any.isPresent()) out.println(any.get());
}

5)findFirst

/**
 * 功能描述 : 返回当前流中第一个元素
 * @return : void
 */
@Test
public void findFirst(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    Optional<String> first = strings.stream().findFirst();
    if(first.isPresent()) out.println(first.get());
}

6)forEach java

/**
 * 功能描述 : 遍历流
 * @return : void
 */
@Test
public void foreach(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    strings.stream().forEach(s -> out.println(s));
}

7)collect

/**
 * 功能描述 : 流转换为其他形式
 * @return : void
 */
@Test
public void collect(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    Set<String> set = strings.stream().collect(Collectors.toSet());
    List<String> list = strings.stream().collect(Collectors.toList());
    Map<String, String> map = strings.stream().collect(Collectors.toMap(v ->v.concat("_name"), v1 -> v1, (v1, v2) -> v1));
    out.println(set);
    out.println(list);
    out.println(map);
}

8)reduce

/**
 * 功能描述 : 将流中元素反复结合起来,得到一个值
 * @return : void
 */
@Test
public void reduce(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    //reduce方法一
    Optional<String> reduce1 = strings.stream().reduce((acc,item) -> {return acc+item;});
    //reduce方法二
    String reduce2 = strings.stream().reduce("itcast", (acc, item) -> {
    	return acc + item;
    });
    //reduce方法三
    ArrayList<String> reduce3 = strings.stream().reduce(
        new ArrayList<String>(),
   		new BiFunction<ArrayList<String>, String, ArrayList<String>>() {
    		@Override
    		public ArrayList<String> apply(ArrayList<String> acc, String item) {
    			acc.add(item);
    			return acc;
    		}
    	}, 
        new BinaryOperator<ArrayList<String>>() {
   			@Override
    		public ArrayList<String> apply(ArrayList<String> acc, ArrayList<String> item) {
    		return acc;
    		}
    	}
    );
    if(reduce1.isPresent())out.println(reduce1.get());
    out.println(reduce2);
    out.println(reduce3);
}

9)count

/**
* 功能描述 : 返回流中元素总数
* @return : void
*/
@Test
public void count(){
    List<String> strings = Arrays.asList("cv", "abd", "aba", "efg", "abcd","jkl", "jkl");
    long count = strings.stream().count();
    out.println(count);
}

注意:文章中因排序部分用到外部比较器,需要导入外部jar包

<!--apache集合操作工具包-->
<dependency>
    <groupId>org.apache.commons</groupId>
    <artifactId>commons-collections4</artifactId>
    <version>4.4</version>
</dependency>

标签:Stream,stream,Arrays,List,jkl,详解,strings,asList
来源: https://blog.csdn.net/DarzenWong/article/details/122513057