修复每日业绩bug和优化赠送业绩计算方式

935090232@qq.com

2021-06-18 e423d56d730db1baed24f3f7dbbc4141038776b6

 zq-erp/src/main/java/com/matrix/system/hiveErp/action/DataAnalysisCustomer.java

@@ -1,5 +1,6 @@
package com.matrix.system.hiveErp.action;

import com.matrix.component.redis.RedisClient;
import com.matrix.core.constance.MatrixConstance;
import com.matrix.core.pojo.AjaxResult;
import com.matrix.core.tools.WebUtil;
@@ -7,9 +8,9 @@
import com.matrix.system.common.tools.DataAuthUtil;
import com.matrix.system.hive.bean.SysShopInfo;
import com.matrix.system.hive.dao.SysShopInfoDao;
import com.matrix.system.hive.service.imp.DataAnalysisCustomerServiceImpl;
import com.matrix.system.hiveErp.analysUtil.*;
import com.matrix.system.hiveErp.dao.TjVipSumDao;
import org.jetbrains.annotations.NotNull;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
@@ -31,7 +32,8 @@
    @Autowired
    SysShopInfoDao shopInfoDao;


    @Autowired
    DataAnalysisCustomerServiceImpl dataAnalysisCustomerService;

    /**
     * 会员人头数统计
@@ -43,9 +45,9 @@
     */
    @RequestMapping(value = "/customerHeadCompare")
    public @ResponseBody  AjaxResult customerHeadCompare(StatisticsParamVo statisticsParam) {
        return getAnalysisResult(statisticsParam, new Caculate() {
        return dataAnalysisCustomerService.getAnalysisResult(statisticsParam, new Caculate<Integer>() {
            @Override
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId) {
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId, Long companyId) {
                //从员工业绩统计表中，按时间段，门店的维度统计人头数
                return tjVipSumDao.customerHeadCompare(timeSpaceParam,shopId);
            }
@@ -61,9 +63,9 @@
     */
    @RequestMapping(value = "/customerEnterCountCompare")
    public @ResponseBody  AjaxResult customerEnterCountCompare(StatisticsParamVo statisticsParam) {
        return getAnalysisResult(statisticsParam, new Caculate() {
        return dataAnalysisCustomerService.getAnalysisResult(statisticsParam, new Caculate<Integer>() {
            @Override
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId) {
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId, Long companyId) {
                //从员工业绩统计表中，按时间段，门店的维度统计人次
                return tjVipSumDao.customerEnterCountCompare(timeSpaceParam,shopId);
            }
@@ -80,9 +82,9 @@
     */
    @RequestMapping(value = "/customerEnterRateCompare")
    public @ResponseBody  AjaxResult customerEnterRateCompare(StatisticsParamVo statisticsParam) {
        return getAnalysisResult(statisticsParam, new Caculate() {
        return dataAnalysisCustomerService.getAnalysisResult(statisticsParam, new Caculate<Integer>() {
            @Override
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId) {
            public Map<String, Integer> exec(List<StatisticsTimeDaoParam> timeSpaceParam, Long shopId, Long companyId) {
                //从员工业绩统计表中，按时间段，门店的维度统计人次
                return tjVipSumDao.customerEnterRateCompare(timeSpaceParam,shopId);
            }
@@ -93,64 +95,6 @@





    /**
     *  按店铺查询数据通用格式执行方法,支持时、日、月、年维度
     *  如：              A店铺    B店铺
     *     2020-01-01     12     13
     *     2020-02-02     10     11
     * @param statisticsParam 时间条件
     * @param caculate  循环调用caculate计算该店的数据
     *                  查询的数据需满足  只有一个门店只有一行 列名称为 t0,t1,t2
     * @return
     */
    private AjaxResult getAnalysisResult(StatisticsParamVo statisticsParam, Caculate caculate) {
        AjaxResult result = new AjaxResult();

        //根据计算横坐标
        List<Date> xAxis = StatisticsTimeUtil.getTimeSpace(statisticsParam.getBeginTime(), statisticsParam.getEndTime(), statisticsParam.getStatisticsUnit());

        //获取所有门店
        SysUsers user = WebUtil.getSessionAttribute(MatrixConstance.LOGIN_KEY);
        List<SysShopInfo> shops=null;
        if(DataAuthUtil.hasAllShopAuth()){
            shops    = shopInfoDao.selectShopInfo(user.getCompanyId());
        }else{
            shops=Arrays.asList(shopInfoDao.selectById(user.getShopId()));
        }
        //定义数据项内容
        List<SeriesVo> series=new ArrayList<>();

        //定义数据主体
        String[]  legendData=new String[shops.size()];

        int i=0;

        //按门店统计数据
        List<StatisticsTimeDaoParam> timeSpaceParam = StatisticsTimeUtil.buidParam(xAxis);
        for(SysShopInfo shop: shops){

            legendData[i++]=shop.getShopName();
            //数据项内容
            SeriesVo storeInfoSeries=new SeriesVo();
            storeInfoSeries.setName(shop.getShopName());
            //调用计算器获取数据库统计的结果
            Map<String, Integer> yAxisMap = caculate.exec(timeSpaceParam,shop.getId());
            //把统计结果转成数组格式
            storeInfoSeries.setData(StatisticsTimeUtil.getSeries(yAxisMap));
            series.add(storeInfoSeries);

        }
        //构造返回对象
        Map<Object,Object> data=new HashMap<>();
        data.put("legendData",legendData);
        data.put("series",series);
        data.put("xAxis", StatisticsTimeUtil.getFormartDateList(xAxis,statisticsParam));
        result.setMapInfo(data);
        result.setStatus(AjaxResult.STATUS_SUCCESS);
        return result;
    }