public class TestStreamAPI2 {
 
 List<Employee> emps = Arrays.asList(
   new Employee(102, "李四", 59, 6666.66, Status.BUSY),
   new Employee(101, "張三", 18, 9999.99, Status.FREE),
   new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
   new Employee(104, "趙六", 8, 7777.77, Status.BUSY),
   new Employee(104, "趙六", 8, 7777.77, Status.FREE),
   new Employee(104, "趙六", 8, 7777.77, Status.FREE),
   new Employee(105, "田七", 38, 5555.55, Status.BUSY)
 );
 
 //3. 終止操作
 /*
  allMatch——檢查是否匹配所有元素
  anyMatch——檢查是否至少匹配一個元素
  noneMatch——檢查是否沒有匹配的元素
  findFirst——返回第一個元素
  findAny——返回當前流中的任意元素
  count——返回流中元素的總個數(shù)
  max——返回流中最大值
  min——返回流中最小值
  */
 @Test
 public void test1(){
   boolean bl = emps.stream()
    .allMatch((e) -> e.getStatus().equals(Status.BUSY));
   
   System.out.println(bl);
   
   boolean bl1 = emps.stream()
    .anyMatch((e) -> e.getStatus().equals(Status.BUSY));
   
   System.out.println(bl1);
   
   boolean bl2 = emps.stream()
    .noneMatch((e) -> e.getStatus().equals(Status.BUSY));
   
   System.out.println(bl2);
 }
 
 @Test
 public void test2(){
  Optional<Employee> op = emps.stream()
   .sorted((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()))
   .findFirst();
  
  System.out.println(op.get());
  
  System.out.println("--------------------------------");
  
  Optional<Employee> op2 = emps.parallelStream()
   .filter((e) -> e.getStatus().equals(Status.FREE))
   .findAny();
  
  System.out.println(op2.get());
 }
 
 @Test
 public void test3(){
  long count = emps.stream()
       .filter((e) -> e.getStatus().equals(Status.FREE))
       .count();
  
  System.out.println(count);
  
  Optional<Double> op = emps.stream()
   .map(Employee::getSalary)
   .max(Double::compare);
  
  System.out.println(op.get());
  
  Optional<Employee> op2 = emps.stream()
   .min((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()));
  
  System.out.println(op2.get());
 }
 
 //注意：流進行了終止操作后，不能再次使用
 @Test
 public void test4(){
  Stream<Employee> stream = emps.stream()
   .filter((e) -> e.getStatus().equals(Status.FREE));
  
  long count = stream.count();
  
  stream.map(Employee::getSalary)
   .max(Double::compare);
 }
}

public class TestStreamAPI3 {
 
 List<Employee> emps = Arrays.asList(
   new Employee(102, "李四", 79, 6666.66, Status.BUSY),
   new Employee(101, "張三", 18, 9999.99, Status.FREE),
   new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
   new Employee(104, "趙六", 8, 7777.77, Status.BUSY),
   new Employee(104, "趙六", 8, 7777.77, Status.FREE),
   new Employee(104, "趙六", 8, 7777.77, Status.FREE),
   new Employee(105, "田七", 38, 5555.55, Status.BUSY)
 );
 
 //3. 終止操作
 /*
  歸約
  reduce(T identity, BinaryOperator) / reduce(BinaryOperator) ——可以將流中元素反復(fù)結(jié)合起來，得到一個值。
  */
 @Test
 public void test1(){
  List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8,9,10);
  
  Integer sum = list.stream()
   .reduce(0, (x, y) -> x + y);
  
  System.out.println(sum);
  
  System.out.println("----------------------------------------");
  
  Optional<Double> op = emps.stream()
   .map(Employee::getSalary)
   .reduce(Double::sum);
  
  System.out.println(op.get());
 }
 
 //需求：搜索名字中 “六” 出現(xiàn)的次數(shù)
 @Test
 public void test2(){
  Optional<Integer> sum = emps.stream()
   .map(Employee::getName)
   .flatMap(TestStreamAPI1::filterCharacter)
   .map((ch) -> {
    if(ch.equals('六'))
     return 1;
    else
     return 0;
   }).reduce(Integer::sum);
  
  System.out.println(sum.get());
 }
 
 //collect——將流轉(zhuǎn)換為其他形式。接收一個 Collector接口的實現(xiàn)，用于給Stream中元素做匯總的方法
 @Test
 public void test3(){
  List<String> list = emps.stream()
   .map(Employee::getName)
   .collect(Collectors.toList());
  
  list.forEach(System.out::println);
  
  System.out.println("----------------------------------");
  
  Set<String> set = emps.stream()
   .map(Employee::getName)
   .collect(Collectors.toSet());
  
  set.forEach(System.out::println);

  System.out.println("----------------------------------");
  
  HashSet<String> hs = emps.stream()
   .map(Employee::getName)
   .collect(Collectors.toCollection(HashSet::new));
  
  hs.forEach(System.out::println);
 }
 
 @Test
 public void test4(){
  Optional<Double> max = emps.stream()
   .map(Employee::getSalary)
   .collect(Collectors.maxBy(Double::compare));
  
  System.out.println(max.get());
  
  Optional<Employee> op = emps.stream()
   .collect(Collectors.minBy((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary())));
  
  System.out.println(op.get());
  
  Double sum = emps.stream()
   .collect(Collectors.summingDouble(Employee::getSalary));
  
  System.out.println(sum);
  
  Double avg = emps.stream()
   .collect(Collectors.averagingDouble(Employee::getSalary));
  
  System.out.println(avg);
  
  Long count = emps.stream()
   .collect(Collectors.counting());
  
  System.out.println(count);
  
  System.out.println("--------------------------------------------");
  
  DoubleSummaryStatistics dss = emps.stream()
   .collect(Collectors.summarizingDouble(Employee::getSalary));
  
  System.out.println(dss.getMax());
 }
 
 //分組
 @Test
 public void test5(){
  Map<Status, List<Employee>> map = emps.stream()
   .collect(Collectors.groupingBy(Employee::getStatus));
  
  System.out.println(map);
 }
 
 //多級分組
 @Test
 public void test6(){
  Map<Status, Map<String, List<Employee>>> map = emps.stream()
   .collect(Collectors.groupingBy(Employee::getStatus, Collectors.groupingBy((e) -> {
    if(e.getAge() >= 60)
     return "老年";
    else if(e.getAge() >= 35)
     return "中年";
    else
     return "成年";
   })));
  
  System.out.println(map);
 }
 
 //分區(qū)
 @Test
 public void test7(){
  Map<Boolean, List<Employee>> map = emps.stream()
   .collect(Collectors.partitioningBy((e) -> e.getSalary() >= 5000));
  
  System.out.println(map);
 }
 
 //
 @Test
 public void test8(){
  String str = emps.stream()
   .map(Employee::getName)
   .collect(Collectors.joining("," , "----", "----"));
  
  System.out.println(str);
 }
 
 @Test
 public void test9(){
  Optional<Double> sum = emps.stream()
   .map(Employee::getSalary)
   .collect(Collectors.reducing(Double::sum));
  
  System.out.println(sum.get());
 }
}