使用lambda表达式分别 根据 单个字段、多个字段,分组求和

 

示意图:

 

 

 

 1、根据 单个字段,分组求和:根据2019这个字段,计算一个list集合里,同属于2019的某个字段累加和

 

 2、根据 多个字段,分组求和:

  (1)先根据2019这个字段,再根据1这个字段,计算一个list集合里,同属于2019和1的某个字段累加和;

  (2)先根据2019这个字段,再根据2这个字段,计算一个list集合里,同属于2019和2的某个字段累加和;

 

代码如下:

import com.pojo.DataStatisticsResultMiddle;
import java.util.ArrayList;
import java.util.List;
import java.util.LongSummaryStatistics;
import java.util.Map;
import java.util.stream.Collectors;

public class Test {

    public static void main(String[] args) {

        List<DataStatisticsResultMiddle> li = new ArrayList<>();
        DataStatisticsResultMiddle middle1 = new DataStatisticsResultMiddle();
        middle1.setDatas("2019");
        middle1.setCarrierid("1");
        middle1.setEnusers(100L);
        DataStatisticsResultMiddle middle2 = new DataStatisticsResultMiddle();
        middle2.setDatas("2019");
        middle2.setCarrierid("1");
        middle2.setEnusers(150L);
        DataStatisticsResultMiddle middle3 = new DataStatisticsResultMiddle();
        middle3.setDatas("2019");
        middle3.setCarrierid("1");
        middle3.setEnusers(200L);

        DataStatisticsResultMiddle middle4 = new DataStatisticsResultMiddle();
        middle4.setDatas("2019");
        middle4.setCarrierid("2");
        middle4.setEnusers(400L);
        DataStatisticsResultMiddle middle5 = new DataStatisticsResultMiddle();
        middle5.setDatas("2019");
        middle5.setCarrierid("2");
        middle5.setEnusers(500L);
        DataStatisticsResultMiddle middle6 = new DataStatisticsResultMiddle();
        middle6.setDatas("2019");
        middle6.setCarrierid("2");
        middle6.setEnusers(600L);

        li.add(middle1);
        li.add(middle2);
        li.add(middle3);
        li.add(middle4);
        li.add(middle5);
        li.add(middle6);


        //单个字段,分组求和(datas)
        Map<String, LongSummaryStatistics> enusersCollect1 =
                li.stream().collect(Collectors.groupingBy(DataStatisticsResultMiddle:: getDatas, Collectors.summarizingLong(DataStatisticsResultMiddle :: getEnusers)));
        LongSummaryStatistics enusers = enusersCollect1.get("2019");
        System.out.println(enusers.getSum());

        System.out.println("分割线***********************************");

        //多个字段,分组求和(先按datas分组,再按Carrierid分组,求和)
        Map<String, Map<String, LongSummaryStatistics>> enusersCollect2 =
                li.stream().collect(Collectors.groupingBy(DataStatisticsResultMiddle:: getDatas,
                                        Collectors.groupingBy(DataStatisticsResultMiddle:: getCarrierid,
                                            Collectors.summarizingLong(DataStatisticsResultMiddle :: getEnusers))));
        Map<String, LongSummaryStatistics> map = enusersCollect2.get("2019");
        for(Map.Entry<String, LongSummaryStatistics> entry : map.entrySet()){
            System.out.println(entry.getKey());
            System.out.println(entry.getValue().getSum());
        }

    }

}

  

输出结果如下:

 

3、List的某个字段为String,对其求和:

防止精度丢失:用BigDecimal

//字段为String类型,数字带小数,防止精度丢失:用BigDecimal
String aaa  = list.stream().map(i -> new BigDecimal(i.getCurrentIncome())).reduce(BigDecimal.ZERO, BigDecimal::add).toString();
System.out.println("aaa:"+ aaa);
//会精度丢失
String bbb  = String.valueOf(list.stream().mapToDouble(i -> Double.parseDouble(i.getCurrentIncome())).sum());
System.out.println("bbb:"+ bbb);

 

 posted on 2019-11-17 14:06  布鲁布鲁sky  阅读(29584)  评论(0编辑  收藏  举报