stream 方法过滤条件的使用

迈不过友情╰ 2022-12-03 02:26 235阅读 0赞

@Data
    
    @AllArgsConstructor   
    
    public class User {
    
        private Long id;      // id
    
        private Integer age;  // 年龄
    
        private Byte gentle;  // 性别
    
        private String name;  // 名字
    
        private Integer rank; // 排名
    
    }
    
    User user0 = new User(1L, 18, (byte) 0, "张三", 1);
    
    User user1 = new User(2L, 20, (byte) 1, "李四", 4);
    
    User user2 = new User(3L, 35, (byte) 0, "王五", 2);
    
    User user3 = new User(4L, 29, (byte) 1, "赵六", 3);

下面以List为例，实际上只要是Collection的子类，玩法都类似

1、生成stream

List<User> list = Arrays.asList(user0, user1, user2, user3);
    Stream<User> stream = null;
    stream = list.stream(); // 需要预判NPE
    stream = Optional.of(list).orElseGet(Collections::emptyList).stream(); // 需要预判NPE
    stream = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream();
    stream = Optional.ofNullable(list).orElseGet(Collections::emptyList).parallelStream(); // 并行处理流
    stream = Stream.of(user0, user1, user2, user3).parallel(); // 直接构造
    stream = Stream.of(Arrays.asList(user0, user1), Arrays.asList(user2, user3)).flatMap(Collection::stream); // flatMap合并

2、stream操作

// 过滤出性别为0的user
    List<User> userList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().filter(user -> (byte) 0 == user.getGentle()).collect(Collectors.toList());
     
    // 获取排名大于1的用户年龄set
    Set<Integer> ageList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().filter(user -> 1 < user.getRank()).map(User::getAge).collect(Collectors.toSet());
     
    // 合计性别为0的user的年龄
    Integer totalAge = Optional.ofNullable(userList).orElseGet(Collections::emptyList).stream().map(User::getAge).reduce(0, Integer::sum);
     
    // 按排名倒序排列
    List<User> sortedUserList = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().sorted(Comparator.comparing(User::getRank, Comparator.reverseOrder())).collect(Collectors.toList());
     
    // 获取排名第2高的user
    User rankUser = Optional.ofNullable(sortedUserList).orElseGet(Collections::emptyList).stream().skip(1).findFirst().get();
     
    // 排名最高的user
    User highestRankUser = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().max(Comparator.comparing(User::getRank)).get();
     
    // 是否存在排名大于1的user
    boolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().anyMatch(user -> user.getRank() > 1);
     
    // 是否所有user排名都大于1
    boolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().allMatch(user -> user.getRank() > 1);
     
    // 是否所有user排名都不大于5
    boolean flag = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().noneMatch(user -> user.getRank() > 5);
     
    // 按唯一id分组
    Map<Long, User> idUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getId, Function.identity()));
     
    // 按唯一id,名字分组
    Map<Long, String> idNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getId, User::getName));
     
    // 按年龄,名字分组，相同年龄的后出现的被覆盖
    Map<Integer, String> ageNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.toMap(User::getAge, User::getName, (a, b) -> a));
     
    // 按性别分组
    Map<Byte, List<User>> gentleUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle));
     
    // 按排名是否大于3分组
    Map<Boolean, List<User>> partitionUserMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.partitioningBy(user -> user.getRank() > 3));
     
    // 按性别名字分组
    Map<Byte, List<String>> gentleNameMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle, Collectors.mapping(User::getName, Collectors.toList())));
     
    // 按性别年龄总和分组
    Map<Byte, Integer> gentleTotalAgeMap = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().collect(Collectors.groupingBy(User::getGentle, Collectors.reducing(0, User::getAge, Integer::sum)));
     
    // 迭代操作
    Stream.iterate(0, i -> i + 1).limit(list.size()).forEach(i -> {
        System.out.println(list.get(i).getName());
    });
     
    // guava table转换
    Table<Long, String, Integer> idNameRankTable = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream().map(user -> ImmutableTable.of(user.getId(), user.getName(), user.getRank())).collect(HashBasedTable::create, HashBasedTable::putAll, HashBasedTable::putAll);

// stream只能被terminal一次，下面是错误示范
    Stream<User> stream = Optional.ofNullable(list).orElseGet(Collections::emptyList).stream();
    stream.collect(Collectors.toMap(User::getId, Function.identity()));
    stream.collect(Collectors.toMap(User::getId, User::getName)); // java.lang.IllegalStateException: stream has already been operated upon or closed
     
     
    // ssc-common的com.meicloud.mcu.common.util.StreamUtil简单封装了一些流操作，欢迎试用
     
    // 参考资料：https://www.ibm.com/developerworks/cn/java/j-lo-java8streamapi/index.html