何为终止操作
终端操作会从流的流水线生成结果。其结果可以是任何不是流的值。例如：List、Integer，甚至是void
查找与匹配
1.allMatch–检查是否匹配所有元素
@Test
public void test9(){
//allMatch--检查是否匹配所有元素
boolean b = employees.stream()
.allMatch((e) -> e.getStatus().equals(Employee.Status.FREE));
System.out.println(b);//false
}
2.anyMatch–检查是否至少匹配一个元素
@Test
public void test9(){
//anyMatch--检查是否至少匹配一个元素
boolean b1 = employees.stream()
.anyMatch((e) -> e.getStatus().equals(Employee.Status.BUSY));
System.out.println(b1);//true
}
3.noneMatch–检查是否没有匹配所有元素
@Test
public void test9(){
//noneMatch--检查是否没有匹配所有元素
boolean b2 = employees.stream()
.noneMatch((e) -> e.getStatus().equals(Employee.Status.BUSY));
System.out.println(b2);//false
}
4.findFirst–返回第一个元素
@Test
public void test9(){
//findFirst--返回第一个元素
Optional<Employee> op = employees.stream()
.sorted((e1, e2) -> -Double.compare(e1.getSalary(), e2.getSalary()))
.findFirst();
System.out.println(op.get());}
5.findAny–返回当前流中任意元素
@Test
public void test9(){
//findAny--返回当前流中任意元素
Optional<Employee> op2 = employees.parallelStream()
.filter((e) -> e.getStatus().equals(Employee.Status.FREE))
.findAny();
System.out.println(op2.get());
}
6.count–返回流中元素的总个数
@Test
public void test9(){
//count--返回流中元素的总个数
long count = employees.stream().count();
System.out.println(count);
}
7.max–返回流中最大值
@Test
public void test9(){
//max--返回流中最大值
Optional<Employee> op3 = employees.stream()
.max((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()));
System.out.println(op3.get());
}
8.min–返回流中最小值
@Test
public void test9(){
//min--返回流中最小值
Optional<Double> op4 = employees.stream()
.map(Employee::getSalary)
.min(Double::compareTo);
System.out.println(op4.get());
}
规约
reduce(T identity,BinaryOperator)/reduce(BinaryOPerator)–可以将流中元素反复结合起来，得到一个值
@org.junit.Test
public void test3(){
List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8,9,10);
Integer reduce = list.stream()
.reduce(0, (x, y) -> x + y);
System.out.println(reduce);
System.out.println("-------------------------------");
//计算所有工资
Optional<Double> reduce1 = employees.stream()
.map(Employee::getSalary)
.reduce(Double::sum);
System.out.println(reduce1.get());
System.out.println("-------------------------------");
Optional<Integer> reduce2 = employees.stream().map(Employee::getAge).reduce(Integer::max);
System.out.println(reduce2.get());
}
备注
map和reduce的连接通常称为map-reduce模式，因Goolge用它来进行网络搜索而出名
收集
collect：将流转换为其他形式，接受一个Collector接口的实现，用于给Stream中元素做汇总的方法
####Collector接口
Collector接口中的方法的实现决定了如何对流执行收集操作（如收集到List，Set，Map）。但是Collectors实用类提供了很多静态方法，可以方便地创建常见收集器实例。具体如下：
1.toList：返回类型List,把流中元素收集到List中
@Test
public void test9(){
//toList：返回类型List<T>,把流中元素收集到List中
List<String> collect = employees.stream()
.map(Employee::getName)
.collect(Collectors.toList());
System.out.println(collect);
}
2.toSet：返回类型Set,把流中元素收集到Set中
@Test
public void test9(){
//toSet：返回类型Set<T>,把流中元素收集到Set中
Set<String> collect1 = employees.stream()
.map(Employee::getName)
.collect(Collectors.toSet());
System.out.println(collect1);
}
3.toCollection: 返回类型Collection,把流中元素收集到创建的集合、
@Test
public void test9(){
//toCollection: 返回类型Collection<T>,把流中元素收集到创建的集合
ArrayList<Integer> collect2 = employees.stream()
.map(Employee::getAge)
.collect(Collectors.toCollection(ArrayList::new));
System.out.println(collect2);
}
4.counting:返回类型Long,计算流中总元素
@Test
public void test9(){
//counting:返回类型Long,计算流中总元素
Long collect3 = employees.stream()
//.map(Employee::getAge)
.collect(Collectors.counting());
System.out.println(collect3);
}
5.averagingDouble:计算流中平均值
@Test
public void test9(){
//averagingDouble:计算流中平均值
Double aDouble = employees.stream()
.collect(Collectors.averagingDouble(Employee::getSalary));
System.out.println(aDouble);
}
6.summingDouble:计算流中总和
@Test
public void test9(){
//summingDouble:计算流中总和
Integer collect4 = employees.stream()
.collect(Collectors.summingInt(Employee::getAge));
System.out.println(collect4);
}
7.maxBy:返回类型Optional:根据比较器选择最大值
@Test
public void test9(){
//maxBy:返回类型Optional<T>:根据比较器选择最大值
Optional<Employee> op = employees.stream()
.collect(Collectors.maxBy((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary())));
System.out.println(op.get());
}
8.minBy:返回类型Optional:根据比较器选择最小值
@Test
public void test9(){
//minBy:返回类型Optional<T>:根据比较器选择最小值
Optional<Integer> op2 = employees.stream()
.map(Employee::getAge)
.collect(Collectors.minBy(Integer::compare));
System.out.println(op2.get());
}
8.groupingBy:范会类型Map>根据属型值对流分组
@Test
public void test9(){
//groupingBy:范会类型Map<k,List<t>>根据属型值对流分组
Map<Employee.Status, List<Employee>> collect5 = employees.stream()
.collect(Collectors.groupingBy(Employee::getStatus));
System.out.println(collect5);
//{BUSY=[Employee{name='李四', age=58, salary=5555.55, status=BUSY}, Employee{name='田七', age=23, salary=8888.88, status=BUSY}], FREE=[Employee{name='张三', age=18, salary=9999.99, status=FREE}, Employee{name='赵六', age=36, salary=6666.66, status=FREE}], VOCATION=[Employee{name='王五', age=26, salary=3333.33, status=VOCATION}]}
}
9.多级分组
@Test
public void test9(){
//多级分组
Map<Employee.Status, Map<String, List<Employee>>> collect6 = employees.stream()
.collect(Collectors.groupingBy(Employee::getStatus, Collectors.groupingBy((Employee e) -> {
if (e.getAge() <= 35) {
return "青年";
} else if (e.getAge() <= 50) {
return "中年";
} else {
return "老年";
}
})));
System.out.println(collect6);
//{BUSY={青年=[Employee{name='田七', age=23, salary=8888.88, status=BUSY}], 老年=[Employee{name='李四', age=58, salary=5555.55, status=BUSY}]}, FREE={青年=[Employee{name='张三', age=18, salary=9999.99, status=FREE}], 中年=[Employee{name='赵六', age=36, salary=6666.66, status=FREE}]}, VOCATION={青年=[Employee{name='王五', age=26, salary=3333.33, status=VOCATION}]}}
}
10.//partitioningBy:返回类型Map>,根据true或者false进行分组
@Test
public void test9(){
//partitioningBy:返回类型Map<Boolean,List<T>>,根据true或者false进行分组
Map<Boolean, List<Employee>> collect7 = employees.stream()
.collect(Collectors.partitioningBy((e) -> e.getSalary() > 8000));
System.out.println(collect7);
}
11.sumarizingDouble:返回类型DoubleSummaryStatistics,收集流中Double属性的统计值
@Test
public void test9(){
//sumarizingDouble:返回类
DoubleSummaryStatistics,收集流中Double属性的统计值
DoubleSummaryStatistics statistics = employees.stream()
.collect(Collectors.summarizingDouble(Employee::getSalary));
System.out.println(statistics.getCount());
System.out.println(statistics.getSum());
}
12.joining:返回类型String,连接流中每个字符串
@Test
public void test9(){
//joining:返回类型String,连接流中每个字符串
String s = employees.stream()
.map(Employee::getName)
.collect(Collectors.joining(",", "---", "---"));
System.out.println(s);
}