feat(device): 便携式设备数据补召功能重构,补召数据拆分到13张基础数据表中
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@@ -10,8 +10,6 @@ import com.github.tocrhz.mqtt.publisher.MqttPublisher;
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import com.njcn.csdevice.api.CsLineFeignClient;
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import com.njcn.csdevice.api.CsLineTopologyFeignClient;
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import com.njcn.csdevice.api.DevCapacityFeignClient;
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import com.njcn.csdevice.api.fallback.CsLineTopologyClientFallbackFactory;
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import com.njcn.csdevice.pojo.po.CsLinePO;
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import com.njcn.csdevice.pojo.vo.AppTopologyDiagramVO;
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import com.njcn.csharmonic.param.CommonStatisticalQueryParam;
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import com.njcn.csharmonic.param.FrequencyStatisticalQueryParam;
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@@ -122,111 +120,6 @@ public class MqttMessageHandler {
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publisher.send("/zl/TemperData/" + pageId, gson.toJson(recallReplyDTO), 1, false);
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}
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/**
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* 实时数据应答
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*/
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// @MqttSubscribe(value = "/zl/askDevData/{devId}",qos = 1)
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// public void responseTopoData(String topic, @NamedValue("devId") String devId, MqttMessage message, @Payload String payload) {
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// String topoDataJson =redisUtil.getStringByKey (devId);
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// if(StringUtils.isEmpty(topoDataJson)){
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// List<ThdDataVO> result = new ArrayList<>();
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// List<ThdDataVO> tempList = new ArrayList<>();
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//
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// //1.查询拓扑图配置的指标:拓扑图扑图配置:7677f94c749dedaff30f911949cbd724
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// List<EleEpdPqd> data = csStatisticalSetFeignClient.queryStatisticalSelect("b934664f9592d1c5e92caa90695b7103").getData();
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// data.forEach(temp->{
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// if(Objects.nonNull(temp.getHarmStart())&&Objects.nonNull(temp.getHarmEnd())){
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// FrequencyStatisticalQueryParam frequencyStatisticalQueryParam = new FrequencyStatisticalQueryParam();
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// frequencyStatisticalQueryParam.setDevId(devId);
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// frequencyStatisticalQueryParam.setStatisticalId(temp.getId());
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// frequencyStatisticalQueryParam.setValueType("avg");
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// frequencyStatisticalQueryParam.setFrequencyStart(temp.getHarmStart());
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// frequencyStatisticalQueryParam.setFrequencyEnd(temp.getHarmEnd());
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// List<ThdDataVO> thdDataVOList = stableDataService.QuerySqlData(frequencyStatisticalQueryParam);
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// tempList.addAll(thdDataVOList);
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//
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// }else {
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// CommonStatisticalQueryParam commonStatisticalQueryParam = new CommonStatisticalQueryParam();
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// commonStatisticalQueryParam.setDevId(devId);
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// commonStatisticalQueryParam.setStatisticalId(temp.getId());
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// commonStatisticalQueryParam.setValueType("avg");
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// List<ThdDataVO> listFuture= stableDataService.queryFisrtCommonStatistical(commonStatisticalQueryParam);
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// tempList.addAll(listFuture);
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// }
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//
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// });
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// //过滤M相
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// List<ThdDataVO> m = tempList.stream().filter(temp -> Objects.equals(temp.getPhase(), "M")).collect(Collectors.toList());
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// m.stream().forEach(temp->{
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// Stream.of("A","B","C").forEach(phase->{
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// ThdDataVO thdDataVO = new ThdDataVO();
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// BeanUtils.copyProperties(temp,thdDataVO);
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// thdDataVO.setPhase(phase);
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// result.add(thdDataVO);
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// });
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// });
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// List<ThdDataVO> apfThdI = tempList.stream().filter(temp -> Objects.equals(temp.getStatisticalName(), "Apf_ThdA_Load(%)")).collect(Collectors.toList());
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// Map<String, List<ThdDataVO>> collect3 = apfThdI.stream().collect(Collectors.groupingBy(ThdDataVO::getLineId));
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// collect3.forEach((k,v)->{
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// if(!CollectionUtil.isEmpty(v)){
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// double asDouble = v.stream().mapToDouble(ThdDataVO::getStatisticalData).average().getAsDouble();
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// ThdDataVO thdDataVO = new ThdDataVO();
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// BeanUtils.copyProperties(v.get(0),thdDataVO);
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// thdDataVO.setStatisticalData(Double.valueOf(df.format(asDouble)));
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// thdDataVO.setPhase("avg");
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// result.add(thdDataVO);
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// }
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// });
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// List<ThdDataVO> apfRmsI = tempList.stream().filter(temp -> Objects.equals(temp.getStatisticalName(), "Apf_RmsI_TolOut(A)")).collect(Collectors.toList());
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// Map<String, List<ThdDataVO>> collect2 = apfRmsI.stream().collect(Collectors.groupingBy(ThdDataVO::getLineId));
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// collect2.forEach((k,v)->{
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// if(!CollectionUtil.isEmpty(v)){
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// double asDouble = v.stream().mapToDouble(ThdDataVO::getStatisticalData).average().getAsDouble();
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// ThdDataVO thdDataVO = new ThdDataVO();
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// BeanUtils.copyProperties(v.get(0),thdDataVO);
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// thdDataVO.setStatisticalData(Double.valueOf(df.format(asDouble)));
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// thdDataVO.setPhase("avg");
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// result.add(thdDataVO);
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// }
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// });
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// List<ThdDataVO> apfThdISys = tempList.stream().filter(temp -> Objects.equals(temp.getStatisticalName(), "Apf_ThdA_Sys(%)")).collect(Collectors.toList());
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// Map<String, List<ThdDataVO>> collect4 = apfThdISys.stream().collect(Collectors.groupingBy(ThdDataVO::getLineId));
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// collect4.forEach((k,v)->{
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// if(!CollectionUtil.isEmpty(v)){
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// double asDouble = v.stream().mapToDouble(ThdDataVO::getStatisticalData).average().getAsDouble();
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// ThdDataVO thdDataVO = new ThdDataVO();
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// BeanUtils.copyProperties(v.get(0),thdDataVO);
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// thdDataVO.setStatisticalData(Double.valueOf(df.format(asDouble)));
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// thdDataVO.setPhase("avg");
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// result.add(thdDataVO);
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//
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// }
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// });
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// Double capacity = devCapacityFeignClient.getDevCapacity(devId).getData();
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// apfRmsI.forEach(temp->{
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// ThdDataVO thdDataVO = new ThdDataVO();
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// BeanUtils.copyProperties(temp,thdDataVO);
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// thdDataVO.setUnit("%");
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// thdDataVO.setStatisticalName("load_Rate");
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// thdDataVO.setAnotherName("负载率");
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// if (capacity<=0){
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// thdDataVO.setStatisticalData(3.1415926);
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// }else {
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// double v = temp.getStatisticalData()*100 / capacity;
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// thdDataVO.setStatisticalData(Double.valueOf(df.format(v)));
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// }
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// result.add(thdDataVO);
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// });
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// List<ThdDataVO> notM = tempList.stream().filter(temp -> !Objects.equals(temp.getPhase(), "M")).collect(Collectors.toList());
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// result.addAll(notM);
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// Gson gson = new Gson();
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// topoDataJson = gson.toJson(result);
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// redisUtil.saveByKeyWithExpire(devId, (Object) topoDataJson, 30L);
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// }
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// publisher.send("/zl/devData/"+devId,topoDataJson,1,false);
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// }
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/**
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* 实时数据应答
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*/
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