java根据百分百获取集合数据随机、有序等

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import java.util.stream.IntStream;  
public class DataDistributionExample {

    public static void main(String[] args) {
        // 假设这是原始数据集合，元素是任意类型
        List<String> dataList = new ArrayList<>();
        for (int i = 0; i < 100; i++) {
            dataList.add("User" + i);
        }

        // 按照小明（30%）、小红（40%）、小张（30%）的比例分配
        Map<String, Double> distributionMap = new HashMap<>();
        distributionMap.put("小明", 0.3);
        distributionMap.put("小红", 0.4);
        distributionMap.put("小张", 0.3);

        Collections.shuffle(dataList); // 首先对数据进行随机打乱

        int totalDataCount = dataList.size();
        int countForXiaoming = (int) Math.round(totalDataCount * distributionMap.get("小明"));
        int countForXiaohong = (int) Math.round(totalDataCount * distributionMap.get("小红"));

        List<String> resultForXiaoming = new ArrayList<>();
        List<String> resultForXiaohong = new ArrayList<>();
        List<String> resultForXiaozhang = new ArrayList<>();

        for (int i = 0; i < totalDataCount; i++) {
            if (i < countForXiaoming) {
                resultForXiaoming.add(dataList.remove(0));
            } else if (i < countForXiaoming + countForXiaohong) {
                resultForXiaohong.add(dataList.remove(0));
            } else {
                resultForXiaozhang.add(dataList.remove(0));
            }
        }

        System.out.println("小明的数据: " + resultForXiaoming);
        System.out.println("小红的数据: " + resultForXiaohong);
        System.out.println("小张的数据: " + resultForXiaozhang);
        
        
        System.out.println("================================");
        t001();
        
    }
    
    
    static void t001() {
    	// 原始数据列表，包含1到100的整数
        List<Integer> originalList = IntStream.rangeClosed(1, 100).boxed().collect(Collectors.toList());

        // 小明、张工对应的数字范围
        int xiaomingEnd = (int) (originalList.size() * 0.3);
        int zhanggongEnd = xiaomingEnd + (int) (originalList.size() * 0.3);

        // 使用HashSet存储已抽取的元素以避免重复
        Set<Integer> sampledSet = new HashSet<>();

        // 抽取小明的数据
        List<Integer> xiaomingData = originalList.subList(0, xiaomingEnd)
                .stream()
                .distinct()
                .filter(sampledSet::add)
                .collect(Collectors.toList());

        // 抽取张工的数据
        List<Integer> zhanggongData = originalList.subList(xiaomingEnd, zhanggongEnd)
                .stream()
                .distinct()
                .filter(sampledSet::add)
                .collect(Collectors.toList());

        // 抽取其他人的数据，由于这里每个人对应一个数字，所以直接从剩余部分中获取
        List<Integer> othersData = originalList.subList(zhanggongEnd, originalList.size())
                .stream()
                .distinct()
                .filter(sampledSet::add)
                .collect(Collectors.toList());
        
        
        System.out.println(xiaomingData+"\n"+zhanggongData+"\n"+othersData);

    }
}