day41 jdk8新特性Stream流 数据库安装

流（Stream）中保存了对集合或者数组数据的操作，和集合类似，但是集合中保存的是数据。Stream不能保存数据

一、创建流

• 通过Collection对象的stream()或者parallelStream()

• 通过Arrays类的stream(Array[])方法

• 通过Stream接口of() iterate() generate()方法

• 通过 IntStream, LongStream, DoubleStream接口中的of(), range(), rangeClosed()方法

 //1. 通过Collection对象的stream()或者parallelStream()
        List list = new ArrayList<>();

  Stream stringStream = list.parallelStream();

 //2.通过Arrays类的stream()方法
        String[] names = {"乔峰", "虚竹", "段誉", "阿朱", "段正淳", "萧远山"};
        Stream stream = Arrays.stream(names);

//3.通过Stream接口of()   iterate()   generate()方法
   //     System.out.println("-----------通过Stream接口的of()--------");
        Stream integerStream = Stream.of(10, 20, 30, 40, 50, 60); 

          Stream iterate = Stream.iterate(0, x -> x + 2);

        Stream generate = Stream.generate(() -> new Random().nextInt(100));

 //4.1.  通过 IntStream,  LongStream, DoubleStream接口中的of(), range(), rangeClosed()方法
        IntStream intStream = IntStream.of(10, 20, 30, 40, 50, 60, 70, 80); 

二、流的操作  

一个stream调用方法变成一个新的stream

• filter()： 对元素数据进行过滤

• limit(): 限制数据

• skip(): 跳过几个元素

• distinct(): 去重

• sorted() 排序

• map() 把流映射到另外一组数据

• parallel() (parallelStream) 获取一个并行流

• public class StreamDemo2 {
      public static void main(String[] args) {
          List list = new ArrayList<>();
          list.add(new Employee("张无忌", 12000.0));
          list.add(new Employee("小昭", 18000.0));
          list.add(new Employee("张三丰", 32000.0));
          list.add(new Employee("金花婆婆", 15000.0));
          list.add(new Employee("宋青书", 8000.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("谢逊", 27000.0));
          list.add(new Employee("成昆", 12800.0));
          list.add(new Employee("殷天正", 32000.0));
          list.add(new Employee("殷素素", 14500.0));
          list.add(new Employee("张翠山", 16900.0));
          list.add(new Employee("张松溪", 14200.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("灭绝师太", 13000.0));
  
  
  
          // 1. filter 过滤   过滤出工资大于15000的员工
          Stream employeeStream = list.stream().filter(e -> e.getSalary() > 15000);
        //  employeeStream.forEach(System.out::println);
  
          //2. limit  限制数据   取集合中的前两条数据
          Stream limit = list.stream().limit(2);
         // limit.forEach(System.out::println);
  
          //3. skip  跳过几条数据
          Stream skip = list.stream().skip(3);
         // skip.forEach(System.out::println);
  
          //4. distinct  去重 , 集合中的元素需要重写equals方法
          //list.stream().distinct().forEach(System.out::println);
  
  
  
          //5.sorted  排序
          //list.stream().distinct().sorted((o1,o2)-> Double.compare(o1.getSalary(),o2.getSalary())).forEach(System.out::println);
  
  
          //6. map 把流映射到另外一组数据, 提取集合中员工的名字
          list.stream().map(e->e.getName()).forEach(System.out::println);
  
          //parallel (parallelStream)    获取一个并行流    采用多线程提高效率
          list.stream().parallel().map(e->e.getName()).forEach(System.out::println);
  
  
  
  
          //练习： 找出所有姓张的，按照工资升序排序
         // list.stream().filter(e->e.getName().startsWith("张")).sorted((o1,o2)->Double.compare(o1.getSalary(),o2.getSalary()))
          //        .forEach(System.out::println);
  
          //练习2： 找出工资最低的张姓人员
  //        list.stream().filter(e->e.getName().startsWith("张"))
  //                .sorted((o1,o2)-> Double.compare(o1.getSalary(),o2.getSalary()))
  //                .limit(1).forEach(System.out::println);
  //
  
      }
  }

三、终止流

• forEach() 遍历

• min() 最小值

• max() 最大值

• count() 总数

• reduce() 规约

• collect() 收集

• public class StreamDemo4 {
      public static void main(String[] args) {
          List list = new ArrayList<>();
          list.add(new Employee("张无忌", 12000.0));
          list.add(new Employee("小昭", 18000.0));
          list.add(new Employee("张三丰", 32000.0));
          list.add(new Employee("金花婆婆", 15000.0));
          list.add(new Employee("宋青书", 8000.0));
          list.add(new Employee("灭绝师太", 13000.0));
          list.add(new Employee("谢逊", 27000.0));
          list.add(new Employee("成昆", 12800.0));
          list.add(new Employee("殷天正", 32000.0));
          list.add(new Employee("殷素素", 14500.0));
          list.add(new Employee("张翠山", 16900.0));
          list.add(new Employee("张松溪", 14200.0));
  
  
          //forEach()
          // list.stream().filter(e-> e.getName().startsWith("张")).forEach(System.out::println);
  
  
          // min()  max()
          //找出工资最低的张姓人员
          Optional min = list.stream().filter(e -> e.getName().startsWith("张"))
                  .min((o1, o2) -> Double.compare(o1.getSalary(), o2.getSalary()));
          System.out.println(min.get());
  
          //找出工资最高的员工
          Optional max = list.stream().max((o1, o2) -> Double.compare(o1.getSalary(), o2.getSalary()));
          System.out.println(max.get());
  
          //count()    求总数   输出员工总数
          long count = list.stream().count();
          System.out.println("员工总数：" + count);
          System.out.println(list.size());
  
          //reduce() 规约   输入数据后对数据产生某些影响 对数据进行深加工,在Stream中此方法主要用于数据的叠加
          //求公司员工工资总和
          Optional reduce = list.stream().map(e -> e.getSalary()).reduce((x, y) -> x + y);
          System.out.println(reduce.get());
  
          int[] array = {1,2,3,4,5,6,7,8,9,10};
          OptionalInt reduce1 = Arrays.stream(array).reduce((x, y) -> x + y);
          System.out.println(reduce1.getAsInt());
  
          String[] arr = {"a","b","c","d","e"};
          Optional reduce2 = Arrays.stream(arr).reduce((x, y) -> x + y);
          System.out.println(reduce2.get());
  
          //collect  收集
          // 收集所有员工的姓名，收集到一个集合中
          List collect = list.stream().map(e -> e.getName()).collect(Collectors.toList());
          //collect.forEach(System.out::println);
          Iterator iterator = collect.iterator();
          while(iterator.hasNext()){
              String str = iterator.next();
              System.out.println(str);
          }
  
      }
  }
  

  四、新时间API

• 之前的API存在的问题： 线程安全问题，设计混乱

• 本地化的日期对象

  • LocalDate

  • LocalTime

  • LocalDateTime

  • Instant 时间戳

  • ZXoneld 时区

  • DateTimeFormatter 日期格式转换

• SimpleDateFormat的线程安全问题

•  public static void main(String[] args) throws ExecutionException, InterruptedException {
          SimpleDateFormat simpleDateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
  
          ExecutorService executorService = Executors.newFixedThreadPool(10);
          Callable callable = new Callable() {
              @Override
              public Date call() throws Exception {
                  return simpleDateFormat.parse("2023-09-16 12:11:11");
              }
          };
  
          List> list =  new ArrayList<>();
          for (int i = 0; i < 10; i++) {
              Future submit = executorService.submit(callable);
              list.add(submit);
          }
          for (Future dateFuture : list) {
              System.out.println(dateFuture.get());
          }
  
  
          executorService.shutdown();
      }

  /**
   * SimpleDateFormat的线程安全问题
   */
  public class DateTimeFormatterDemo {
      public static void main(String[] args) throws ExecutionException, InterruptedException {
         //SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
          DateTimeFormatter sdf = DateTimeFormatter.ofPattern("yyyy-MM-dd");
  
          ExecutorService pool = Executors.newFixedThreadPool(10);
          Callable callable = new Callable() {
              @Override
              public LocalDate call() throws Exception {
  
                 return LocalDate.parse("2023-09-15");
  
              }
          };
  
          List> list = new ArrayList<>();
          for (int i = 0; i < 10; i++) {
              Future submit = pool.submit(callable);
              list.add(submit);
          }
  
          for (Future dateFuture : list) {
              System.out.println(dateFuture.get());
          }
  
          pool.shutdown();
  
      }
  }