| | |
| | | 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; |
| | |
| | | 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; |
| | |
| | | |
| | | 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 -> { |
| | |
| | | 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); |
| | |
| | | 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; |
| | |
| | | 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); |
| | |
| | | //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<>(); |
| | |
| | | } |
| | | }); |
| | | 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); |
| | |
| | | //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<>(); |
| | |
| | | } |
| | | }); |
| | | 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); |
| | |
| | | //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<>(); |
| | |
| | | |
| | | |
| | | } |
| | | |
| | | |
| | | |
| | | /** |
| | | * 视频:点位在线率 |
| | |
| | | } |
| | | |
| | | 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 |
| | | * |
| | |
| | | * @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 |
| | |
| | | |
| | | }); |
| | | // 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("$and", dList); |
| | | // 构建聚合管道 |
| | |
| | | MongoDatabase databaes2 = mongoTemplate.getDb(); |
| | | MongoCollection<Document> collection2 = databaes2.getCollection("uy_record_meta_d_sum"); |
| | | |
| | | double finalRecordingMinTime = recordingMinTime; |
| | | double finalRecordingMinTime = getSySMinTime(); |
| | | |
| | | List<Document> documentList = new ArrayList<>(3); |
| | | List<Document> documentList = new ArrayList<>(2); |
| | | documentList.add(new Document("no", new Document("$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("$and", documentList); |
| | | // 构建聚合管道 |
| | | List<Document> pipeline = Arrays.asList( |
| | |
| | | new Document("$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); |
| | |
| | | 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)); |
| | |
| | | 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 $count 只会产生一个结果 |
| | | } |
| | | log.error("部级录像可用率{}:",uniqueDeviceIdCount); |
| | | |
| | | |
| | | |
| | | // List<CheckIndexVideo> videoList = new LambdaQueryChainWrapper<>(checkIndexVideoService.getBaseMapper()) |
| | | // .select(CheckIndexVideo::getMinistryVideoAvailable) |
| | | // .eq(params.getDataType().equals(1), CheckIndexVideo::getExamineTag, CheckConstants.Examine_Tag_Province) |
| | |
| | | resultCount.add(0, totalCount + ""); |
| | | BigDecimal onlineRate = BigDecimal.ZERO; |
| | | if (!StringUtils.isEmpty(resultCount.get(0)) && !"0".equals(resultCount.get(0))) { |
| | | onlineRate = new BigDecimal(resultCount.get(1)).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100")); |
| | | onlineRate = new BigDecimal(uniqueDeviceIdCount).divide(new BigDecimal(resultCount.get(0)), 3,RoundingMode.DOWN).multiply(new BigDecimal("100")); |
| | | } |
| | | resultCount.add(this.remove0(onlineRate)); |
| | | HashMap<String, Object> map = new HashMap<>(); |
| | |
| | | return uniqueDeviceIdCount + ""; |
| | | }).collect(Collectors.toList()); |
| | | |
| | | //计算重点点位录像可用率 |
| | | MongoDatabase database2 = mongoTemplate.getDb(); |
| | | MongoCollection<Document> collection2 = database2.getCollection("uy_record_meta_d_sum"); |
| | | double finalRecordingMinTime = getSySMinTime(); |
| | | |
| | | List<Document> documentList = new ArrayList<>(4); |
| | | documentList.add(new Document("importantTag", new Document("$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) |
| | |
| | | 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<>(); |