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feat(video): 新增视频评价功能及购买状态查询
- 移除TaskController上的@Deprecated注解 - 在VideoController中新增/checkBuyStatus接口用于查询视频购买状态 - 新增VideoReviewController控制器，提供评价管理功能 - 新增MapTypeHandler用于处理Map类型与JSON字段的转换 - 在VideoMapper中增加countBuyRecordByVideoId方法查询视频购买记录 - 新增视频评价相关实体类、DTO及Mapper接口 - 实现VideoReviewService服务类，支持评价新增、分页查询、统计分析和Excel导出 - 在VideoServiceImpl中实现checkVideoBuyStatus方法 - 修改VideoMapper.xml，关联task表并查询task_params字段 - 新增VideoReviewMapper.xml配置文件，实现评价相关SQL查询
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package com.ycwl.basic.service.impl;
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import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.github.pagehelper.PageHelper;
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import com.github.pagehelper.PageInfo;
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import com.ycwl.basic.constant.BaseContextHandler;
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import com.ycwl.basic.exception.BizException;
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import com.ycwl.basic.mapper.VideoMapper;
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import com.ycwl.basic.mapper.VideoReviewMapper;
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import com.ycwl.basic.model.pc.video.entity.VideoEntity;
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import com.ycwl.basic.model.pc.videoreview.dto.VideoReviewAddReqDTO;
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import com.ycwl.basic.model.pc.videoreview.dto.VideoReviewListReqDTO;
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import com.ycwl.basic.model.pc.videoreview.dto.VideoReviewRespDTO;
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import com.ycwl.basic.model.pc.videoreview.dto.VideoReviewStatisticsRespDTO;
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import com.ycwl.basic.model.pc.videoreview.entity.VideoReviewEntity;
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import com.ycwl.basic.service.VideoReviewService;
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import lombok.extern.slf4j.Slf4j;
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import org.apache.poi.ss.usermodel.*;
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import org.apache.poi.xssf.usermodel.XSSFWorkbook;
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import org.springframework.beans.BeanUtils;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import org.springframework.transaction.annotation.Transactional;
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import java.io.IOException;
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import java.io.OutputStream;
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import java.math.BigDecimal;
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import java.math.RoundingMode;
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import java.text.SimpleDateFormat;
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import java.util.*;
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import java.util.stream.Collectors;
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/**
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* 视频评价Service实现类
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*/
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@Slf4j
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@Service
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public class VideoReviewServiceImpl implements VideoReviewService {
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@Autowired
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private VideoReviewMapper videoReviewMapper;
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@Autowired
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private VideoMapper videoMapper;
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private final ObjectMapper objectMapper = new ObjectMapper();
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@Override
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@Transactional(rollbackFor = Exception.class)
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public Long addReview(VideoReviewAddReqDTO reqDTO) {
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// 1. 参数校验
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if (reqDTO.getVideoId() == null) {
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throw new BizException("视频ID不能为空");
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}
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if (reqDTO.getRating() == null || reqDTO.getRating() < 1 || reqDTO.getRating() > 5) {
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throw new BizException("评分必须在1-5之间");
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}
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// 2. 查询视频信息,获取景区ID
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VideoEntity video = videoMapper.selectById(reqDTO.getVideoId());
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if (video == null) {
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throw new BizException("视频不存在");
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}
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// 3. 获取当前登录用户(管理员)
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String userIdStr = BaseContextHandler.getUserId();
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if (userIdStr == null || userIdStr.isEmpty()) {
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throw new BizException("未登录或登录已过期");
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}
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Long creator = Long.valueOf(userIdStr);
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// 4. 构建评价实体
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VideoReviewEntity entity = new VideoReviewEntity();
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entity.setVideoId(reqDTO.getVideoId());
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entity.setScenicId(video.getScenicId());
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entity.setCreator(creator);
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entity.setRating(reqDTO.getRating());
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entity.setContent(reqDTO.getContent());
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entity.setCameraPositionRating(reqDTO.getCameraPositionRating());
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// 5. 插入数据库
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videoReviewMapper.insert(entity);
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log.info("管理员[{}]对视频[{}]添加评价成功,评价ID: {}", creator, reqDTO.getVideoId(), entity.getId());
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return entity.getId();
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}
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@Override
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public PageInfo<VideoReviewRespDTO> getReviewList(VideoReviewListReqDTO reqDTO) {
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// 设置分页参数
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PageHelper.startPage(reqDTO.getPageNum(), reqDTO.getPageSize());
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// 查询列表
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List<VideoReviewRespDTO> list = videoReviewMapper.selectReviewList(reqDTO);
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// 封装分页结果
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return new PageInfo<>(list);
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}
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@Override
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public VideoReviewStatisticsRespDTO getStatistics() {
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VideoReviewStatisticsRespDTO statistics = new VideoReviewStatisticsRespDTO();
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// 1. 总评价数
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Long totalCount = videoReviewMapper.countTotal();
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statistics.setTotalCount(totalCount);
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// 2. 平均评分
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Double avgRating = videoReviewMapper.calculateAverageRating();
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if (avgRating != null) {
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statistics.setAverageRating(BigDecimal.valueOf(avgRating).setScale(2, RoundingMode.HALF_UP));
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} else {
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statistics.setAverageRating(BigDecimal.ZERO);
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}
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// 3. 评分分布
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List<Map<String, Object>> ratingDistList = videoReviewMapper.countRatingDistribution();
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Map<Integer, Long> ratingDistribution = new HashMap<>();
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for (Map<String, Object> item : ratingDistList) {
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Integer rating = (Integer) item.get("ratingValue");
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Long count = (Long) item.get("count");
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ratingDistribution.put(rating, count);
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}
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statistics.setRatingDistribution(ratingDistribution);
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// 4. 最近7天趋势
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List<Map<String, Object>> trendList = videoReviewMapper.countRecentTrend(7);
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Map<String, Long> recentTrend = new LinkedHashMap<>();
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for (Map<String, Object> item : trendList) {
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String date = (String) item.get("dateStr");
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Long count = (Long) item.get("count");
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recentTrend.put(date, count);
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}
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statistics.setRecentTrend(recentTrend);
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// 5. 景区排行(前10)
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List<VideoReviewStatisticsRespDTO.ScenicReviewRank> scenicRankList = videoReviewMapper.countScenicRank(10);
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statistics.setScenicRankList(scenicRankList);
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// 6. 机位评价维度平均值
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Map<String, BigDecimal> cameraPositionAverage = calculateCameraPositionAverage();
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statistics.setCameraPositionAverage(cameraPositionAverage);
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return statistics;
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}
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@Override
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public void exportReviews(VideoReviewListReqDTO reqDTO, OutputStream outputStream) throws IOException {
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// 1. 查询所有数据(不分页)
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reqDTO.setPageNum(1);
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reqDTO.setPageSize(Integer.MAX_VALUE);
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List<VideoReviewRespDTO> list = videoReviewMapper.selectReviewList(reqDTO);
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// 2. 创建Excel工作簿
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Workbook workbook = new XSSFWorkbook();
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Sheet sheet = workbook.createSheet("视频评价数据");
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// 3. 创建标题行样式
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CellStyle headerStyle = workbook.createCellStyle();
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Font headerFont = workbook.createFont();
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headerFont.setBold(true);
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headerStyle.setFont(headerFont);
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headerStyle.setFillForegroundColor(IndexedColors.GREY_25_PERCENT.getIndex());
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headerStyle.setFillPattern(FillPatternType.SOLID_FOREGROUND);
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// 4. 创建标题行
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Row headerRow = sheet.createRow(0);
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String[] headers = {"评价ID", "视频ID", "景区ID", "景区名称", "评价人ID", "评价人名称",
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"评分", "文字评价", "机位评价", "创建时间", "更新时间"};
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for (int i = 0; i < headers.length; i++) {
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Cell cell = headerRow.createCell(i);
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cell.setCellValue(headers[i]);
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cell.setCellStyle(headerStyle);
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}
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// 5. 填充数据
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SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
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int rowNum = 1;
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for (VideoReviewRespDTO review : list) {
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Row row = sheet.createRow(rowNum++);
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row.createCell(0).setCellValue(review.getId());
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row.createCell(1).setCellValue(review.getVideoId());
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row.createCell(2).setCellValue(review.getScenicId());
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row.createCell(3).setCellValue(review.getScenicName());
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row.createCell(4).setCellValue(review.getCreator());
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row.createCell(5).setCellValue(review.getCreatorName());
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row.createCell(6).setCellValue(review.getRating());
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row.createCell(7).setCellValue(review.getContent());
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// 机位评价JSON转字符串
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try {
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String cameraRatingJson = review.getCameraPositionRating() != null ?
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objectMapper.writeValueAsString(review.getCameraPositionRating()) : "";
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row.createCell(8).setCellValue(cameraRatingJson);
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} catch (Exception e) {
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row.createCell(8).setCellValue("");
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}
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row.createCell(9).setCellValue(review.getCreateTime() != null ? sdf.format(review.getCreateTime()) : "");
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row.createCell(10).setCellValue(review.getUpdateTime() != null ? sdf.format(review.getUpdateTime()) : "");
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}
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// 6. 自动调整列宽
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for (int i = 0; i < headers.length; i++) {
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sheet.autoSizeColumn(i);
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}
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// 7. 写入输出流
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workbook.write(outputStream);
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workbook.close();
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log.info("导出视频评价数据成功,共{}条", list.size());
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}
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/**
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* 计算机位评价各维度的平均值
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*/
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private Map<String, BigDecimal> calculateCameraPositionAverage() {
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List<Map<String, Integer>> allRatings = videoReviewMapper.selectAllCameraPositionRatings();
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if (allRatings == null || allRatings.isEmpty()) {
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return new HashMap<>();
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}
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// 统计各维度的总分和次数
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Map<String, List<Integer>> dimensionScores = new HashMap<>();
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for (Map<String, Integer> rating : allRatings) {
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if (rating == null) continue;
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for (Map.Entry<String, Integer> entry : rating.entrySet()) {
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dimensionScores.computeIfAbsent(entry.getKey(), k -> new ArrayList<>()).add(entry.getValue());
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}
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}
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// 计算平均值
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Map<String, BigDecimal> result = new HashMap<>();
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for (Map.Entry<String, List<Integer>> entry : dimensionScores.entrySet()) {
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double avg = entry.getValue().stream().mapToInt(Integer::intValue).average().orElse(0.0);
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result.put(entry.getKey(), BigDecimal.valueOf(avg).setScale(2, RoundingMode.HALF_UP));
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}
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return result;
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}
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}
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