zxl
2025-06-05 29d3c47cc6c903c09b386649fabaebc81cbeca27
ycl-server/src/main/java/com/ycl/platform/service/impl/DataCenterServiceImpl.java
@@ -20,6 +20,7 @@
import com.ycl.platform.domain.vo.DynamicColumnVO;
import com.ycl.platform.mapper.DynamicColumnMapper;
import com.ycl.platform.mapper.ImageResourceSecurityDetailMapper;
import com.ycl.platform.mapper.TMonitorMapper;
import com.ycl.platform.mapper.YwPointMapper;
import com.ycl.platform.service.*;
import com.ycl.system.Result;
@@ -66,7 +67,6 @@
    private final MongoTemplate mongoTemplate;
    private final ImageResourceSecurityDetailMapper securityDetailMapper;
    private final YwPointMapper pointMapper;
    private final ICheckIndexVideoService checkIndexVideoService;
    private final ICheckIndexCarService checkIndexCarService;
    private final ICheckIndexFaceService checkIndexFaceService;
    private final DynamicColumnMapper dynamicColumnMapper;
@@ -77,14 +77,35 @@
    private static DecimalFormat DF = new DecimalFormat("#.####");
    public Map<String,List<DynamicColumnVO>> getDynamicByConditions(DataCenterQuery params,List<DynamicColumnVO> list){
        //获得到对应id,且包含传入字符串 动态列集合
        List<DynamicColumnVO> likeFieldDynamicColumnVOList = list.stream()
                .filter(dynamicColumnVO ->
                    dynamicColumnVO.getLabelId().equals(params.getDyId()) &&
                            dynamicColumnVO.getColumnValue().contains(params.getDyValue())
        ).collect(Collectors.toList());
        //获得满足条件的id集合
        List<String> ids = likeFieldDynamicColumnVOList.stream().map(DynamicColumnVO::getRefStringId).toList();
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = list.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        Set<String> removeSet = new HashSet<>(ids);
        //移除掉不符合条件的key
        groupByRefStringIdMap.keySet().retainAll(removeSet);
        return groupByRefStringIdMap;
    }
    @Override
    public void recordingAvailabilityExport(HttpServletResponse response,DataCenterQuery params) throws IOException {
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params, "createTime", likeFileds, null);
        //下拉框录像情况查询条件
        if (params.getOption() != null) {
            query.addCriteria(Criteria.where("recordStatus").is(params.getOption()));
        }
        MongoUtil.setNoPage(query, params, TIME_FIELD);
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);
        //翻译行政区域
        resultList.forEach(item -> {
@@ -92,8 +113,19 @@
            AreaDeptEnum areaDeptEnum = AreaDeptEnum.fromCode(areaCode);
            if (areaDeptEnum != null) item.setArealayername(areaDeptEnum.getName());
        });
        //获得动态列数据
        List<DynamicColumnVO> dynamicColumnVOList = dynamicColumnMapper.getDynamicColumnByTableName(TableNameConstants.COLUMN_NAME_VIDEO);
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        //判断是否有查询条件
        boolean conditions = false;
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = new HashMap<>();
        if (params.getDyId() != null && StringUtils.isNotEmpty(params.getDyValue())){
            conditions = true;
            //获得动态列集合中包含了的字符串值的集合 区分大小写
            groupByRefStringIdMap = getDynamicByConditions(params,dynamicColumnVOList);
        }else{
            groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        }
        //固定表头
        LinkedHashSet<String> headers = new LinkedHashSet<>();
        headers.add(RecordingAvailabilityHeaders.arealayername);
@@ -115,21 +147,28 @@
            headersList.addAll(dynamicsHeaders);
            headers.addAll(headersList);
        }
        SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd");
        SimpleDateFormat dateFormat2 = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
//        SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd");
        //查询到有动态列查询条件
        //获得对应动态列中ref的对象id 与 查询结果id过滤
        if (conditions){
            Map<String, List<DynamicColumnVO>> finalGroupByRefStringIdMap = groupByRefStringIdMap;
            resultList = resultList.stream()
                    .filter(obj -> finalGroupByRefStringIdMap.containsKey(obj.getId()))
                    .collect(Collectors.toList());
        }
        SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
        List<List<Object>> data = new ArrayList<>();
        for (RecordMetaDSumResult result : resultList){
            List<Object> row = new ArrayList<>();
            row.add(result.getArealayername());
            row.add(result.getArealayerno());
            row.add(dateFormat2.format(result.getCreateTime()));
            row.add(dateFormat.format(result.getCreateTime()));
            row.add(result.getDeviceId());
            row.add(result.getMissDuration());
            row.add(result.getPlatId());
            row.add(result.getRecordDuration());
            row.add(result.getRecordStatusText());
            row.add(dateFormat2.format(result.getCreateTime()));
            row.add(dateFormat.format(result.getCreateTime()));
            //添加动态列数据
            for (String header : headersList){
                boolean flag = false;
@@ -201,8 +240,23 @@
                item.setOffLineTimeStr(offLineTime);
            }
        });
        List<DynamicColumnVO> dynamicColumnVOList = dynamicColumnMapper.getDynamicColumnByTableName(TableNameConstants.COLUMN_NAME_FACE_POINT);
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        //判断是否有查询条件
        boolean conditions = false;
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = new HashMap<>();
        if (params.getDyId() != null && StringUtils.isNotEmpty(params.getDyValue())){
            conditions = true;
            //获得动态列集合中包含了的字符串值的集合 区分大小写
            groupByRefStringIdMap = getDynamicByConditions(params,dynamicColumnVOList);
        }else{
            groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        }
        //固定表头
        LinkedHashSet<String> headers = new LinkedHashSet<>();
        headers.add(PointOnlineHeaders.no);
@@ -223,6 +277,13 @@
            //使用链表保证后续补充数据时获取数据顺序一致
            headersList.addAll(dynamicsHeaders);
            headers.addAll(headersList);
        }
        if (conditions){
            Map<String, List<DynamicColumnVO>> finalGroupByRefStringIdMap = groupByRefStringIdMap;
            resultList = resultList.stream()
                    .filter(obj -> finalGroupByRefStringIdMap.containsKey(obj.getNo()))
                    .collect(Collectors.toList());
        }
        List<List<Object>> data = new ArrayList<>();
@@ -313,7 +374,16 @@
            }
        });
        List<DynamicColumnVO> dynamicColumnVOList = dynamicColumnMapper.getDynamicColumnByTableName(TableNameConstants.COLUMN_NAME_VIDEO_POINT);
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        //判断是否有查询条件
        boolean conditions = false;
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = new HashMap<>();
        if (params.getDyId() != null && StringUtils.isNotEmpty(params.getDyValue())){
            conditions = true;
            //获得动态列集合中包含了的字符串值的集合 区分大小写
            groupByRefStringIdMap = getDynamicByConditions(params,dynamicColumnVOList);
        }else{
            groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        }
        //固定表头
        LinkedHashSet<String> headers = new LinkedHashSet<>();
        headers.add(PointOnlineHeaders.no);
@@ -334,6 +404,14 @@
            //使用链表保证后续补充数据时获取数据顺序一致
            headersList.addAll(dynamicsHeaders);
            headers.addAll(headersList);
        }
        if (conditions){
            Map<String, List<DynamicColumnVO>> finalGroupByRefStringIdMap = groupByRefStringIdMap;
            resultList = resultList.stream()
                    .filter(obj -> finalGroupByRefStringIdMap.containsKey(obj.getNo()))
                    .collect(Collectors.toList());
        }
        List<List<Object>> data = new ArrayList<>();
@@ -428,7 +506,16 @@
            }
        });
        List<DynamicColumnVO> dynamicColumnVOList = dynamicColumnMapper.getDynamicColumnByTableName(TableNameConstants.COLUMN_NAME_CAR_POINT);
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        //判断是否有查询条件
        boolean conditions = false;
        Map<String,List<DynamicColumnVO>> groupByRefStringIdMap = new HashMap<>();
        if (params.getDyId() != null && StringUtils.isNotEmpty(params.getDyValue())){
            conditions = true;
            //获得动态列集合中包含了的字符串值的集合 区分大小写
            groupByRefStringIdMap = getDynamicByConditions(params,dynamicColumnVOList);
        }else{
            groupByRefStringIdMap = dynamicColumnVOList.stream().collect(Collectors.groupingBy(DynamicColumnVO::getRefStringId));
        }
        //固定表头
        LinkedHashSet<String> headers = new LinkedHashSet<>();
        headers.add(PointOnlineHeaders.no);
@@ -449,6 +536,14 @@
            //使用链表保证后续补充数据时获取数据顺序一致
            headersList.addAll(dynamicsHeaders);
            headers.addAll(headersList);
        }
        if (conditions){
            Map<String, List<DynamicColumnVO>> finalGroupByRefStringIdMap = groupByRefStringIdMap;
            resultList = resultList.stream()
                    .filter(obj -> finalGroupByRefStringIdMap.containsKey(obj.getNo()))
                    .collect(Collectors.toList());
        }
        List<List<Object>> data = new ArrayList<>();
@@ -536,6 +631,8 @@
    }
    /**
     * 视频:点位在线率
@@ -1261,6 +1358,22 @@
    }
    private final ISysConfigService configService;
    public double getSySMinTime(){
        //获取系统参数
        String dictLabel =  configService.selectConfigByKey("recording_min_time");
        double recordingMinTime;
        try {
            recordingMinTime = Double.parseDouble(dictLabel) / 60; // 如果 dictLabel 是以小时为单位,则无需除以 60
        } catch (Exception e) {
            log.error("配置的删除时间范围格式不正确: {}", dictLabel, e);
            return  12.0; // 默认 12 小时(以小时为单位)
        }
        return recordingMinTime;
    }
    private final TMonitorMapper tMonitorMapper;
    /**
     * 视频:录像可用率
     *
@@ -1268,27 +1381,21 @@
     * @return
     */
    @Override
    public Result videoAvailabilityRate(DataCenterQuery params) {
        //获取系统参数
        String dictLabel =  configService.selectConfigByKey("recording_min_time");
        double recordingMinTime;
        try {
            recordingMinTime = Double.parseDouble(dictLabel) / 60; // 如果 dictLabel 是以小时为单位,则无需除以 60
        } catch (Exception e) {
            log.error("配置的删除时间范围格式不正确: {}", dictLabel, e);
            recordingMinTime = 12.0; // 默认 12 小时(以小时为单位)
        }
        List<String> noString = tMonitorMapper.getIdListVideo();
        List<String> likeFileds = Arrays.asList("deviceId", "deviceName");
        Query query = MongoUtil.getQuery(params, "createTime", likeFileds, null);
        if (CollectionUtils.isNotEmpty(noString)) { // 防止空集合异常
            query.addCriteria(Criteria.where("no").in(noString));
        }
        //下拉框录像情况查询条件
        if (params.getOption() != null) {
            query.addCriteria(Criteria.where("recordStatus").is(params.getOption()));
        }
        long total = mongoTemplate.count(query, RecordMetaDSumResult.class);
        MongoUtil.setPage(query, params, "createTime");
        List<RecordMetaDSumResult> resultList = mongoTemplate.find(query, RecordMetaDSumResult.class);
        //查询动态列数据
        //查询动态列数据更具id查询
@@ -1304,12 +1411,15 @@
        });
        // 统计数量
        MongoDatabase database = mongoTemplate.getDb();
        MongoCollection<Document> collection = database.getCollection("uy_record_meta_d_sum");
        List<Integer> status = Arrays.asList(1, 0, -1);
        List<String> resultCount = status.stream().map(item -> {
            List<Document> dList = new ArrayList<>(2);
            dList.add(new Document("recordStatus", new Document("$eq", item)));
            dList.add(new Document("no", new Document("$in", noString)));
            setTag(params, dList);
            Document filter = new Document("$and", dList);
            // 构建聚合管道
@@ -1333,12 +1443,14 @@
        MongoDatabase databaes2 = mongoTemplate.getDb();
        MongoCollection<Document> collection2 = databaes2.getCollection("uy_record_meta_d_sum");
        double finalRecordingMinTime = recordingMinTime;
        double finalRecordingMinTime = getSySMinTime();
        List<Document> documentList = new ArrayList<>(3);
        List<Document> documentList = new ArrayList<>(2);
        documentList.add(new Document("no", new Document("$in", noString)));
        setTag(params, documentList);
        Document recording = new Document("recordDuration",new Document("$gte", finalRecordingMinTime));
        Document recording = new Document("missDuration",new Document("$lte", finalRecordingMinTime));
        documentList.add(recording);
        Document filter = new Document("$and", documentList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
@@ -1348,25 +1460,14 @@
                new Document("$count", "uniqueDeviceIds")
        );
        AggregateIterable<Document> result = collection2.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历,因为 $count 只会产生一个结果
        }
        log.error("打印:{}",uniqueDeviceIdCount);
//        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
//                .select(CheckIndexVideo::getVideoAvailable)
//                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
//                .eq(params.getDataType().equals(2), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Dept)
//                .between(CheckIndexVideo::getCreateTime, DateUtils.getDayStart(params.getStartTime()), DateUtils.getDayEnd(params.getEndTime()))
//                .list();
//        BigDecimal onlineRate = BigDecimal.ZERO;
//        if (CollectionUtils.isNotEmpty(videoList)) {
//            BigDecimal sum = videoList.stream().map(CheckIndexVideo::getVideoAvailable).reduce(BigDecimal.ZERO, BigDecimal::add);
//            BigDecimal count = BigDecimal.valueOf(videoList.size());
//            onlineRate = sum.divide(count, 4, RoundingMode.HALF_UP).multiply(BigDecimal.valueOf(100));
//        }
        //加一个总数
        log.error("录像可用率打印:{}",uniqueDeviceIdCount);
        int totalCount = 0;
        for (String s : resultCount) {
            totalCount += Integer.parseInt(s);
@@ -1374,10 +1475,9 @@
        resultCount.add(0, totalCount + "");
        BigDecimal onlineRate = BigDecimal.ZERO;
//        1:完整 0:间歇 -1:异常 |
        if (!StringUtils.isEmpty(resultCount.get(0)) && !"0".equals(resultCount.get(0))) {
            //resultCount.get(0)是总数 uniqueDeviceIdCount是更具系统参数查询到mongodb中大于等于 recordDuration字段的总数
            onlineRate = new BigDecimal(uniqueDeviceIdCount).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100"));
        }
        resultCount.add(this.remove0(onlineRate));
@@ -1438,6 +1538,35 @@
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());
        //计算部级录像可用率
        MongoDatabase database2 = mongoTemplate.getDb();
        MongoCollection<Document> collection2 = database2.getCollection("uy_record_meta_d_sum");
        double finalRecordingMinTime = getSySMinTime();
        List<Document> documentList = new ArrayList<>(4);
        documentList.add(new Document("deptTag", new Document("$eq", Boolean.TRUE)));
        setTag(params, documentList);
        Document recording = new Document("missDuration",new Document("$lte", finalRecordingMinTime));
        documentList.add(recording);
        Document filter = new Document("$and", documentList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
                new Document("$match", filter),
                // $group 去重
                new Document("$group", new Document("_id", "$deviceId")),
                new Document("$count", "uniqueDeviceIds")
        );
        AggregateIterable<Document> result = collection2.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历,因为 $count 只会产生一个结果
        }
        log.error("部级录像可用率{}:",uniqueDeviceIdCount);
//        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
//                .select(CheckIndexVideo::getMinistryVideoAvailable)
//                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
@@ -1458,7 +1587,7 @@
        resultCount.add(0, totalCount + "");
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (!StringUtils.isEmpty(resultCount.get(0)) && !"0".equals(resultCount.get(0))) {
            onlineRate = new BigDecimal(resultCount.get(1)).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100"));
            onlineRate = new BigDecimal(uniqueDeviceIdCount).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100"));
        }
        resultCount.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();
@@ -1517,6 +1646,32 @@
            return uniqueDeviceIdCount + "";
        }).collect(Collectors.toList());
        //计算重点点位录像可用率
        MongoDatabase database2 = mongoTemplate.getDb();
        MongoCollection<Document> collection2 = database2.getCollection("uy_record_meta_d_sum");
        double finalRecordingMinTime = getSySMinTime();
        List<Document> documentList = new ArrayList<>(4);
        documentList.add(new Document("importantTag", new Document("$eq", Boolean.TRUE)));
        setTag(params, documentList);
        Document recording = new Document("missDuration",new Document("$lte", finalRecordingMinTime));
        documentList.add(recording);
        Document filter = new Document("$and", documentList);
        // 构建聚合管道
        List<Document> pipeline = Arrays.asList(
                new Document("$match", filter),
                // $group 去重
                new Document("$group", new Document("_id", "$deviceId")),
                new Document("$count", "uniqueDeviceIds")
        );
        AggregateIterable<Document> result = collection2.aggregate(pipeline);
        Integer uniqueDeviceIdCount = 0;
        for (Document doc : result) {
            uniqueDeviceIdCount = doc.getInteger("uniqueDeviceIds");
            break; // 不需要继续遍历,因为 $count 只会产生一个结果
        }
        log.error("重点点位录像可用率{}:",uniqueDeviceIdCount);
//        List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper())
//                .select(CheckIndexVideo::getKeyVideoAvailable)
//                .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province)
@@ -1537,7 +1692,7 @@
        resultCount.add(0, totalCount + "");
        BigDecimal onlineRate = BigDecimal.ZERO;
        if (!StringUtils.isEmpty(resultCount.get(0)) && !"0".equals(resultCount.get(0))) {
            onlineRate = new BigDecimal(resultCount.get(1)).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100"));
            onlineRate = new BigDecimal(uniqueDeviceIdCount).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100"));
        }
        resultCount.add(this.remove0(onlineRate));
        HashMap<String, Object> map = new HashMap<>();