Java 8 API添加了一个新的抽象称为流Stream，可以让你以一种声明的方式处理数据。
Stream 使用一种类似用 SQL 语句从数据库查询数据的直观方式来提供一种对 Java 集合运算和表达的高阶抽象。
Stream API可以极大提高Java程序员的生产力，让程序员写出高效率、干净、简洁的代码。
这种风格将要处理的元素集合看作一种流， 流在管道中传输， 并且可以在管道的节点上进行处理， 比如筛选， 排序，聚合等。
元素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。
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。
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。
主要方法
/*filter过滤(T-> boolean)*/
public static void filter(){
List<User> list = users();
List<User> newlist = list.stream().filter(user -> user.getAge() > 20)
.collect(Collectors.toList());
for (User user : newlist) {
System.out.println(user.getName()+" --> "+ user.getAge());
}
}
---结果---
袁天罡 --> 99
陆佑劫 --> 45
张天师 --> 48
/*distinct 去重*/
数据源中复制new User("李星云", 18, 0, "渝州",new BigDecimal(1000)) 并粘贴两个
public static void distinct(){
List<User> list = users();
List<User> newlist = list.stream().distinct().collect(Collectors.toList());
for (User user : newlist) {
System.out.println(user.getName()+" --> "+ user.getAge());
}
}
---结果---
李星云 --> 18
陆林轩 --> 16
姬如雪 --> 17
袁天罡 --> 99
张子凡 --> 19
陆佑劫 --> 45
张天师 --> 48
蚩梦 --> 18
/*sorted排序*/
public static void sorted(){
List<User> list = users();
List<User> newlist = list.stream()
.sorted(Comparator.comparingInt(User::getAge))
.collect(Collectors.toList());
for (User user : newlist) {
System.out.println(user.getName()+" --> "+ user.getAge());
}
}
---结果---
陆林轩 --> 16
姬如雪 --> 17
李星云 --> 18
蚩梦 --> 18
张子凡 --> 19
陆佑劫 --> 45
张天师 --> 48
袁天罡 --> 99
/*limit返回前n个元素*/
public static void limit(){
List<User> list = users();
List<User> newlist = list.stream()
.sorted(Comparator.comparingInt(User::getAge))
.limit(2)
.collect(Collectors.toList());
for (User user : newlist) {
System.out.println(user.getName()+" --> "+ user.getAge());
}
}
---结果---
陆林轩 --> 16
姬如雪 --> 17
/*skip去除前n个元素*/
public static void skip(){
List<User> list = users();
List<User> newlist = list.stream()
.sorted(Comparator.comparingInt(User::getAge))
.skip(2)
.collect(Collectors.toList());
for (User user : newlist) {
System.out.println(user.getName()+" --> "+ user.getAge());
}
}
---结果---
李星云 --> 18
蚩梦 --> 18
张子凡 --> 19
陆佑劫 --> 45
张天师 --> 48
袁天罡 --> 99
/*map(T->R)*/
public static void map(){
List<User> list = users();
List<String> newlist = list.stream()
.map(User::getName).distinct().collect(Collectors.toList());
for (String add : newlist) {
System.out.println(add);
}
}
---结果---
李星云
陆林轩
姬如雪
袁天罡
张子凡
陆佑劫
张天师
蚩梦
/*flatMap(T -> Stream<R>)*/
public static void flatmap(){
List<String> flatmap = new ArrayList<>();
flatmap.add("常宣灵,常昊灵");
flatmap.add("孟婆,判官红,判官蓝");
/*
这里原集合中的数据由逗号分割，使用split进行拆分后，得到的是Stream<String[]>，
字符串数组组成的流，要使用flatMap的Arrays::stream
将Stream<String[]>转为Stream<String>,然后把流相连接
*/
flatmap = flatmap.stream()
.map(s -> s.split(","))
.flatMap(Arrays::stream)
.collect(Collectors.toList());
for (String name : flatmap) {
System.out.println(name);
}
}
---结果---
常宣灵
常昊灵
孟婆
判官红
判官蓝
/*allMatch（T->boolean）检测是否全部满足参数行为*/
public static void allMatch(){
List<User> list = users();
boolean flag = list.stream()
.allMatch(user -> user.getAge() >= 17);
System.out.println(flag);
}
---结果---
false
/*anyMatch（T->boolean）检测是否有任意元素满足给定的条件*/
public static void anyMatch(){
List<User> list = users();
boolean flag = list.stream()
.anyMatch(user -> user.getSex() == 1);
System.out.println(flag);
}
---结果---
true
/*noneMatchT->boolean）流中是否有元素匹配给定的 T -> boolean条件*/
public static void noneMatch(){
List<User> list = users();
boolean flag = list.stream()
.noneMatch(user -> user.getAddress().contains("郑州"));
System.out.println(flag);
}
---结果---
true
/*findFirst( ):找到第一个元素*/
public static void findfirst(){
List<User> list = users();
Optional<User> optionalUser = list.stream()
.sorted(Comparator.comparingInt(User::getAge))
.findFirst();
System.out.println(optionalUser.toString());
}
---结果---
Optional[User{name='陆林轩', age=16, sex=1, money=500, address='渝州'}]
/*findAny( ):找到任意一个元素*/
public static void findAny(){
List<User> list = users();
// Optional<User> optionalUser = list.stream()
.findAny();
Optional<User> optionalUser = list.stream()
.findAny();
System.out.println(optionalUser.toString());
}
---结果---
Optional[User{name='李星云', age=18, sex=0, money=1000, address='渝州'}]
/*计算总数*/
public static void count(){
List<User> list = users();
long count = list.stream().count();
System.out.println(count);
}
---结果---
8
/*最大值最小值*/
public static void max_min(){
List<User> list = users();
Optional<User> max = list.stream()
.collect(
Collectors.maxBy(
Comparator.comparing(User::getAge)
)
);
Optional<User> min = list.stream()
.collect(
Collectors.minBy(
Comparator.comparing(User::getAge)
)
);
System.out.println("max--> " + max+" min--> "+ min);
}
---结果---
max--> Optional[User{name='袁天罡', age=99, sex=0, money=100000, address='藏兵谷'}] min--> Optional[User{name='陆林轩', age=16, sex=1, money=500, address='渝州'}]
/*求和_平均值*/
public static void sum_avg(){
List<User>list = users();
int totalAge = list.stream()
.collect(Collectors.summingInt(User::getAge));
System.out.println("totalAge--> "+ totalAge);
/*获得列表对象金额， 使用reduce聚合函数,实现累加器*/
BigDecimal totalMpney = list.stream()
.map(User::getMoney)
.reduce(BigDecimal.ZERO, BigDecimal::add);
System.out.println("totalMpney--> " + totalMpney);
double avgAge = list.stream()
.collect(Collectors.averagingInt(User::getAge));
System.out.println("avgAge--> " + avgAge);
}
---结果---
totalAge--> 280
totalMpney--> 105700
avgAge--> 35.0
/*一次性得到元素的个数、总和、最大值、最小值*/
public static void allVlaue(){
List<User> list = users();
IntSummaryStatistics statistics = list.stream()
.collect(Collectors.summarizingInt(User::getAge));
System.out.println(statistics);
}
---结果---
IntSummaryStatistics{count=8, sum=280, min=16, average=35.000000, max=99}
/*拼接*/
public static void join(){
List<User> list = users();
String names = list.stream()
.map(User::getName)
.collect(Collectors.joining(", "));
System.out.println(names);
}
---结果---
李星云, 陆林轩, 姬如雪, 袁天罡, 张子凡, 陆佑劫, 张天师, 蚩梦
/*分组*/
public static void group(){
Map<Integer, List<User>> map = users().stream()
.collect(Collectors.groupingBy(User::getSex));
System.out.println(new Gson().toJson(map));
System.out.println();
Map<Integer, Map<Integer,List<User>>> map2 = users().stream()
.collect(Collectors.groupingBy(User::getSex,
Collectors.groupingBy(User::getAge)));
System.out.println(new Gson().toJson(map2));
}
---结果---
{"0":[{"name":"李星云","age":18,"sex":0,"address":"渝州","money":1000},{"name":"袁天罡","age":99,"sex":0,"address":"藏兵谷","money":100000},{"name":"张子凡","age":19,"sex":0,"address":"天师府","money":900},{"name":"陆佑劫","age":45,"sex":0,"address":"不良人","money":600},{"name":"张天师","age":48,"sex":0,"address":"天师府","money":1100}],"1":[{"name":"陆林轩","age":16,"sex":1,"address":"渝州","money":500},{"name":"姬如雪","age":17,"sex":1,"address":"幻音坊","money":800},{"name":"蚩梦","age":18,"sex":1,"address":"万毒窟","money":800}]}
{"0":{"48":[{"name":"张天师","age":48,"sex":0,"address":"天师府","money":1100}],"18":[{"name":"李星云","age":18,"sex":0,"address":"渝州","money":1000}],"19":[{"name":"张子凡","age":19,"sex":0,"address":"天师府","money":900}],"99":[{"name":"袁天罡","age":99,"sex":0,"address":"藏兵谷","money":100000}],"45":[{"name":"陆佑劫","age":45,"sex":0,"address":"不良人","money":600}]},"1":{"16":[{"name":"陆林轩","age":16,"sex":1,"address":"渝州","money":500}],"17":[{"name":"姬如雪","age":17,"sex":1,"address":"幻音坊","money":800}],"18":[{"name":"蚩梦","age":18,"sex":1,"address":"万毒窟","money":800}]}}
/*分组合计*/
public static void groupCount(){
Map<Integer, Long> num = users().stream()
.collect(Collectors.groupingBy(User::getSex, Collectors.counting()));
System.out.println(num);
Map<Integer, Long> num2 = users().stream()
.filter(user -> user.getAge()>=18)
.collect(Collectors.groupingBy(User::getSex, Collectors.counting()));
System.out.println(num2);
}
---结果---
{0=5, 1=3}
{0=5, 1=1}
/*分区*/
public static void partitioningBy(){
List<User> list = users();
Map<Boolean, List<User>> part = list.stream()
.collect(Collectors.partitioningBy(user -> user.getAge() <= 30));
System.out.println(new Gson().toJson(part));
}
---结果---
{"false":[{"name":"袁天罡","age":99,"sex":0,"address":"藏兵谷","money":100000},{"name":"陆佑劫","age":45,"sex":0,"address":"不良人","money":600},{"name":"张天师","age":48,"sex":0,"address":"天师府","money":1100}],"true":[{"name":"李星云","age":18,"sex":0,"address":"渝州","money":1000},{"name":"陆林轩","age":16,"sex":1,"address":"渝州","money":500},{"name":"姬如雪","age":17,"sex":1,"address":"幻音坊","money":800},{"name":"张子凡","age":19,"sex":0,"address":"天师府","money":900},{"name":"蚩梦","age":18,"sex":1,"address":"万毒窟","money":800}]}
