Java8_Stream详解
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);
}
8)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
*/
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 |
| 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 = trings.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
<dependency>
<groupId>org.apache.commonsgroupId>
<artifactId>commons-collections4artifactId>
<version>4.4version>
dependency>