添加 部分 支持其他监测因素 代码

adaptors/知物云es主题特征to中交华联.go

@@ -35,7 +35,7 @@ func (the Adaptor_ZWYES_ZJHL) Transform(structId int64, factorId int, rawMsg str
 	}
 
 	Payload := the.EsAggTopToHBJCAS(structId, factorId, esAggDateHistogram)
-	if len(Payload) >= 0 {
+	if len(Payload) == 0 {
 		return needPush
 	}
 
@@ -72,7 +72,7 @@ func (the Adaptor_ZWYES_ZJHL) EsAggTopToHBJCAS(structId int64, factorId int, esA
 			}
 			monitorCode := the.getPointCodeFromLabel(station.Labels)
 			if monitorCode == 0 {
-				log.Printf("redis 获取[s:%d,f:%d]测点[%d]标签[%s],信息转换int64异常,跳过", structId, factorId, sensorId, station.Labels)
+				log.Printf("redis 获取[s:%d,f:%d]测点[%d],标签信息[%s]转换int64异常,跳过", structId, factorId, sensorId, station.Labels)
 				continue
 			}
 
@@ -169,7 +169,7 @@ func (the Adaptor_ZWYES_ZJHL) EsAgg2StatisticData(factorId int, monitorCode int6
 		dataDefinitionStatisticData.StatisticData.DataBody = &protoFiles_zjhl_v3.StatisticData_Hsd{Hsd: &protoFiles_zjhl_v3.HSDStatistic{
 			TrafficFlow:   int32(dateBucket.X.Count),
 			MaxTotalLoad:  int32(maxAbsoluteValueX),
-			//MaxAxleLoad:   0, //目前无法支持统计 字符串类型,先不上传
+			MaxAxleLoad:   0, //目前无法支持统计 字符串类型, 和李晓敏确认 按0上报
 			OverLoadCount: int32(dateBucket.Y.Sum),
 			AvgLoad:       float32(avgValueX),
 		}}
@@ -212,6 +212,17 @@ func (the Adaptor_ZWYES_ZJHL) EsAgg2StatisticData(factorId int, monitorCode int6
 			MaxAbsoluteValue: float32(maxAbsoluteValueX),
 			RootMeanSquare:   float32(rootMeanSquareY),
 		}}
+	case 883: //湿度 ->最终拼接为 温湿度
+		dataDefinitionStatisticData.StatisticData.DataBody = &protoFiles_zjhl_v3.StatisticData_Rhs{Rhs: &protoFiles_zjhl_v3.RHSStatistic{
+			//MaxTemperature:           float32(dateBucket.X.Max),
+			//MinTemperature:           float32(dateBucket.X.Min),
+			//AvgTemperature:           float32(avgValueX),
+			//MaxTemperatureDifference: float32(dateBucket.X.Max - dateBucket.X.Min),
+			MaxHumidity:            float32(dateBucket.X.Max),
+			MinHumidity:            float32(dateBucket.X.Min),
+			AvgHumidity:            float32(avgValueX),
+			HumidityExceedDuration: 0,
+		}}
 	case 935: //gnss
 		dataDefinitionStatisticData.StatisticData.DataBody = &protoFiles_zjhl_v3.StatisticData_Gnss{Gnss: &protoFiles_zjhl_v3.GNSSStatistic{
 			// 统计时间范围内的空间变形X绝对最大值

consumers/consumerGZG2ZJHL.go

@@ -129,9 +129,13 @@ func (the *consumerGZG2ZJHL) getStructIds() []int64 {
 	return structIds
 }
 func (the *consumerGZG2ZJHL) getEs1HourAggData() {
-	start, end := utils.GetTimeRangeByHour(-1)
+	start, end := utils.GetTimeRangeByHour(-5)
 	log.Printf("查询数据时间范围 %s - %s", start, end)
-	hourFactorIds := []int{7, 935, 4, 6, 11} //Gnss 935 ,4(温度),6索力, 15, 18, 20
+	//hourFactorIds := []int{883, 2, 7, 935, 4, 6, 11}
+	hourFactorIds := []int{935}
+	//湿度883  -> 要当作温湿度处理，合并温度监测中的3个有相同label的测点数据，组合成虚拟温湿度数据
+	//温湿度2(要温度和湿度数据拼接), 源于温度测点和湿度测点 特殊的3个label测点算温湿度  6500030003，6500030004，6500030005
+	//Gnss 935 ,4(温度),6索力, 15, 18, 20
 	structIds := the.getStructIds()
 	for _, structId := range structIds {
 		for _, factorId := range hourFactorIds {
@@ -414,6 +418,15 @@ func getEsAggSubSqlByZwyFactorId(factorId int) string {
 			"field": "data.trms"
 		}
 	}
+}`
+	case 883: //湿度 (后期需要合并3个温度 拼成 温湿度)
+		subAggSQl = `
+{
+    "x": {
+        "extended_stats": {
+            "field": "data.humidity"
+        }
+    }
 }`
 	case 935:
 		subAggSQl = `