java8 Stream大数据量List分批处理切割方式

//按每3个一组分割
private static final Integer MAX_NUMBER = 3;


private static Integer countStep(Integer size) {
    return (size + MAX_NUMBER - 1) / MAX_NUMBER;
}

public static void main(String[] args) {
      List<Integer> list = Arrays.asList(1, 2, 3, 4, 5, 6, 7);
      int limit = countStep(list.size());
      //方法一：使用流遍历操作
      List<List<Integer>> mglist = new ArrayList<>();
      Stream.iterate(0, n -> n + 1).limit(limit).forEach(i -> {
          mglist.add(list.stream().skip(i * MAX_NUMBER).limit(MAX_NUMBER).collect(Collectors.toList()));
      });

      System.out.println(mglist);

      //方法二：获取分割后的集合
      List<List<Integer>> splitList = Stream.iterate(0, n -> n + 1).limit(limit).parallel().map(a -> list.stream().skip(a * MAX_NUMBER).limit(MAX_NUMBER).parallel().collect(Collectors.toList())).collect(Collectors.toList());
      
      System.out.println(splitList);
}

//使用guava对list进行分割
List<User> users = userService.findAll();
//按每50个一组分割
List<List<User>> parts = Lists.partition(users, 50);
parts.stream().forEach(list -> {
    process(list);
});

List<Integer> intList = Lists.newArrayList(1, 2, 3, 4, 5, 6, 7, 8);
List<List<Integer>> subs = ListUtils.partition(intList, 3);

public static <T> List<List<T>> averageAssign(List<T> source, int n) {
    List<List<T>> result = new ArrayList<>();
    //(先计算出余数)
    int remainder = source.size() % n;  
    //然后是商
    int number = source.size() / n;  
    //偏移量
    int offset = 0;
    for (int i = 0; i < n; i++) {
        List<T> value;
        if (remainder > 0) {
            value = source.subList(i * number + offset, (i + 1) * number + offset + 1);
            remainder--;
            offset++;
        } else {
            value = source.subList(i * number + offset, (i + 1) * number + offset);
        }
        result.add(value);
    }
    return result;
}

List<String> list = Arrays.asList("官僚","买办","资产阶级");

Runnable run = new Runnable() {
    @Override
    public void run() {
        // TODO
    }
}

@FunctionalInterface
public interface MyFun {
    void fun();
}

//也可以使用泛型
@FunctionalInterface
public interface MyFun1<T> {
    void fun(T t);
}

public static void domething(MyFun myfun) {
    myfun.fun();
}

public static void domething(MyFun1<User> myFun) {
    User user = new User();
    user.setName("我是泛型");
    myFun.fun(user);
}

public static void main(String[] args) {
    domething(() -> {System.out.println("通过lambda表达式执行了函数式接口");});
    domething1((item) -> {
        item.setId(100);
        item.setAge(20);
        System.out.println("这是MyFun1函数式接口真正的执行逻辑，最终的结果是：" + JSONObject.tojsonString(item);)
    });
}

List<String> arrList = Arrays.asList("买办", "资产阶级", "官僚");


List<String> list = new ArrayList<>();
list.add("买办");
list.add("官僚");
list.add("资产阶级");
// 注意：大小必须和list保持一致，若小于3，则需要重新分配内存地址，并返回新数组地址；
// 若数组元素大于所需，则下标为[list.size()]的元素置为null，其他元素为原值
// 所以最好将数组大小跟集合大小保持一致,可以验证new String[1],new String[5]的输出值
String[] arr = new String[list.size()];
arr = list.toArray(arr);
System.out.println("arr ：" + Arrays.toString(arr));

// list 初始化（guava）
List<String> initList = Lists.newArrayList("Java", "python", "javascript");

List<User> students = new ArrayList<>();
User st1 = new User();
st1.setId(123);
st1.setAge(10);

User st2 = new User();
st2.setId(123);
st2.setAge(20);

User st3 = new User();
st3.setId(456);
st3.setAge(20);
students.add(st1);
students.add(st2);
students.add(st3);

// list 分割(guava)
List<List<User>> splits = Lists.partition(students, 2);
System.out.println("list分割：" + JsonUtil.toJSONString(splits));

// list分组
Map<Integer, List<User>> groupStu = students.stream().collect(
        Collectors.groupingBy(User::getAge));
System.out.println("list分组：" + JsonUtil.toJSONString(groupStu));

// list转map, (k,v)，若集合中有重复的key，会抛异常：Duplicate key……
// 通过(k1, k2)->k1来处理重复情况，保留k1，舍弃k2
Map<Integer, Integer> studentIdMap = students.stream().collect(
        Collectors.toMap(User::getId, User::getAge, (k1, k2) -> k1));
System.out.println("list转map, (k,v) :" + studentIdMap);

// list转map, (k,t)
Map<Integer, User> studenteMap = students.stream().collect(
        Collectors.toMap(User::getId, Function.identity(), (k1, k2) -> k1));
System.out.println("list转map, (k,t) :" + studenteMap);

// list过滤
List<User> oldStu = students.stream().filter(
        student -> student.getAge() > 10).collect(Collectors.toList());
System.out.println("list过滤filter :" + JsonUtil.toJSONString(oldStu));

// list对象转换
List<Teacher> teachers = students.stream().map(
        student -> {
            Teacher teacher = new Teacher();
            BeanUtils.copyProperties(student, teacher);
            teacher.setTitle("教师");
            return teacher;
        }).collect(Collectors.toList());
System.out.println("list对象转化:" + JsonUtil.toJSONString(teachers));

// list转set
Set<Integer> ages = students.stream().map(User::getAge).collect(Collectors.toSet());
System.out.println("list转set：" + ages);

// 过滤掉空元素后再map
    public static void main(String[] args) {

        List<Customer> customerList = new ArrayList<>();
        customerList.add(new Customer(1L, "Ryu"));
        customerList.add(new Customer(2L, "Ken"));
        customerList.add(new Customer(3L, null));
        customerList.add(null);
        customerList.add(new Customer(5L, null));
        customerList.add(new Customer(6L, "Zangief"));
        
        
        List<String> nameList1 = customerList.stream()
                .filter(Objects::nonNull) // 過濾掉Customer為null的元素
                .map(e -> e.getName())    
                .filter(Objects::nonNull) // 過濾掉Customer.getName()為null的元素
                .collect(Collectors.toList());
        
        
        System.out.println(nameList1); // [Ryu, Ken, Zangief]
        
    }