Stream流详解
作者:互联网
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