修复bug。算法内部使用新线程导致LiteFlow层面的process()方法瞬间返回，但实际计算还在进行，会影响有上下层关系的算法计算

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/service/line/IDataLimitRateAsync.java

@@ -4,26 +4,29 @@ import com.njcn.device.biz.pojo.po.Overlimit;
 
 import java.util.List;
 import java.util.Map;
+import java.util.concurrent.CompletableFuture;
 
 public interface IDataLimitRateAsync {
 
     /**
      * limit_rate多线程算法
+     *
      * @param dataDate
      * @param list
      * @param phase
      * @param overLimitMap
      * @param size
      * @param i
-     * @param type 系统类型
+     * @param type         系统类型
+     * @return
      * @Author: wr
      * @Date: 2025/12/17 12:16
      */
-    void lineDataRate(String dataDate,
-                      List<String> list,
-                      List<String> phase,
-                      Map<String, Overlimit> overLimitMap,
-                      int size,
-                      int i,
-                      int type);
+    CompletableFuture<Void> lineDataRate(String dataDate,
+                                         List<String> list,
+                                         List<String> phase,
+                                         Map<String, Overlimit> overLimitMap,
+                                         int size,
+                                         int i,
+                                         int type);
 }

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/serviceimpl/line/IDataCrossingServiceImpl.java

@@ -46,6 +46,7 @@ import java.util.ArrayList;
 import java.util.List;
 import java.util.Map;
 import java.util.Objects;
+import java.util.concurrent.CompletableFuture;
 import java.util.function.Function;
 import java.util.stream.Collectors;
 
@@ -108,11 +109,26 @@ public class IDataCrossingServiceImpl implements IDataCrossingService {
         List<List<String>> pendingIds = ListUtils.partition(lineIds, 1);
         ArrayList<String> phase = ListUtil.toList(PhaseType.PHASE_A, PhaseType.PHASE_B, PhaseType.PHASE_C);
         MemorySizeUtil.getNowMemory();
+
+        List<CompletableFuture<Void>> futures = new ArrayList<>();
         for (int i = 0; i < pendingIds.size(); i++) {
             logger.info(calculatedParam.getDataDate()+" 总分区数据：" + pendingIds.size() + "=====》当前第"+(i + 1)+"小分区");
             List<String> list = pendingIds.get(i);
-            dataLimitRateAsync.lineDataRate(calculatedParam.getDataDate(), list, phase, overLimitMap, pendingIds.size(), (i + 1), lineParam.getType());
+            // 获取Future
+            CompletableFuture<Void> future = dataLimitRateAsync.lineDataRate(
+                    calculatedParam.getDataDate(),
+                    list,
+                    phase,
+                    overLimitMap,
+                    pendingIds.size(),
+                    (i + 1),
+                    lineParam.getType()
+            );
+
+            futures.add(future);
         }
+        // 等待所有任务完成
+        CompletableFuture.allOf(futures.toArray(new CompletableFuture[0])).join();
         System.gc();
     }
 

algorithm/algorithm-boot/src/main/java/com/njcn/algorithm/serviceimpl/line/IDataLimitRateAsyncImpl.java

@@ -25,6 +25,7 @@ import org.springframework.util.CollectionUtils;
 import javax.annotation.Resource;
 import java.lang.reflect.Method;
 import java.util.*;
+import java.util.concurrent.CompletableFuture;
 import java.util.stream.Collectors;
 
 /**
@@ -56,13 +57,13 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
 
     @Override
     @Async("asyncExecutor")
-    public void lineDataRate(String dataDate,
-                             List<String> list,
-                             List<String> phase,
-                             Map<String, Overlimit> overLimitMap,
-                             int size,
-                             int i,
-                             int type) {
+    public CompletableFuture<Void> lineDataRate(String dataDate,
+                                                List<String> list,
+                                                List<String> phase,
+                                                Map<String, Overlimit> overLimitMap,
+                                                int size,
+                                                int i,
+                                                int type) {
         List<DataLimitDetailDto> result = new ArrayList<>();
         LineCountEvaluateParam lineParam = new LineCountEvaluateParam();
         lineParam.setStartTime(TimeUtils.getBeginOfDay(dataDate));
@@ -123,7 +124,7 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
          */
         Map<String, List<DataHarmDto>> harmRateV = dataVHarmList.stream()
                 .filter(x -> phase.contains(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataHarmDto::getLineId));
 
         /**
@@ -131,7 +132,7 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
          */
         Map<String, List<DataIDto>> dataI = dataIList.stream()
                 .filter(x -> phase.contains(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataIDto::getLineId));
 
 
@@ -140,7 +141,7 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
          */
         Map<String, List<DataHarmDto>> inHarmV = dataVInHarmList.stream()
                 .filter(x -> phase.contains(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataHarmDto::getLineId));
 
         /**
@@ -148,49 +149,57 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
          */
         Map<String, List<DataVDto>> dataVThd = dataVAllTime.stream()
                 .filter(x -> phase.contains(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataVDto::getLineId));
 
         /**
          * 功能描述:获取influxDB -> data_v -> 负序电压不平衡度 -> 最大值 && 日95%概率值
          */
         Map<String, List<DataVDto>> dataVUnbalance = dataVAllTime.stream()
-                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equals(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()) ||
-                        InfluxDBTableConstant.MAX.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equalsIgnoreCase(x.getPhasicType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()) ||
+                        InfluxDBTableConstant.MAX.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataVDto::getLineId));
 
         /**
          * 功能描述:获取influxDB -> data_i -> 负序电流 -> 最大值 && 日95%概率值
          */
         Map<String, List<DataIDto>> dataINeg = dataIList.stream()
-                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equals(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.CP95.equals(x.getValueType()) ||
-                        InfluxDBTableConstant.MAX.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equalsIgnoreCase(x.getPhasicType()))
+                .filter(x -> InfluxDBTableConstant.CP95.equalsIgnoreCase(x.getValueType()) ||
+                        InfluxDBTableConstant.MAX.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataIDto::getLineId));
 
         /**
          * 功能描述:获取influxDB -> data_v -> 频率偏差 -> 最大值 && 最小值
          */
         Map<String, List<DataVDto>> dataVFreq = dataVAllTime.stream()
-                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equals(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.MIN.equals(x.getValueType()) ||
-                        InfluxDBTableConstant.MAX.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.PHASE_TYPE_T.equalsIgnoreCase(x.getPhasicType()))
+                .filter(x -> InfluxDBTableConstant.MIN.equalsIgnoreCase(x.getValueType()) ||
+                        InfluxDBTableConstant.MAX.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataVDto::getLineId));
         /**
          * 功能描述:获取influxDB -> data_v -> 电压偏差 -> 最大值
          */
         Map<String, List<DataVDto>> dataVDev = dataVAllTime.stream()
                 .filter(x -> phase.contains(x.getPhasicType()))
-                .filter(x -> InfluxDBTableConstant.MAX.equals(x.getValueType()))
+                .filter(x -> InfluxDBTableConstant.MAX.equalsIgnoreCase(x.getValueType()))
                 .collect(Collectors.groupingBy(DataVDto::getLineId));
 
         /**
          * 功能描述:获取influxDB -> data_plt -> 长时间闪变 -> 注(取最大值原始算法去掉了，现没有根据最大值比较)
          */
-        Map<String, List<DataPltDto>> dataPlt = dataPltAllTime.stream()
-                .filter(x -> phase.contains(x.getPhasicType()))
-                .collect(Collectors.groupingBy(DataPltDto::getLineId));
+        Map<String, List<DataPltDto>> dataPlt;
+        if (type == 2) {
+            dataPlt = dataPltAllTime.stream()
+                    .filter(x -> phase.contains(x.getPhasicType()))
+                    .filter(x -> InfluxDBTableConstant.MAX.equalsIgnoreCase(x.getValueType()))
+                    .collect(Collectors.groupingBy(DataPltDto::getLineId));
+        } else {
+            dataPlt = dataPltAllTime.stream()
+                    .filter(x -> PhaseType.PHASE_A.equals(x.getPhasicType()))
+                    .collect(Collectors.groupingBy(DataPltDto::getLineId));
+        }
 
         for (String item : list) {
             if (ObjectUtil.isNotNull(overLimitMap.get(item))) {
@@ -229,6 +238,8 @@ public class IDataLimitRateAsyncImpl implements IDataLimitRateAsync {
             MemorySizeUtil.getNowMemory();
         }
         System.gc();
+
+        return CompletableFuture.completedFuture(null);
     }
 
     /**

data-processing/data-processing-api/src/main/java/com/njcn/dataProcess/pojo/dto/PqsCommunicateDto.java

@@ -18,6 +18,8 @@ public class PqsCommunicateDto {
     private String description;
 
     private Integer type;
+    //是否更新updateTime标志；数据上送更新1，状态翻转不更新0
+    private Integer flag=0;
 
 
 }

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/LnDataDealServiceImpl.java

@@ -97,7 +97,7 @@ public class LnDataDealServiceImpl implements LnDataDealService {
                 pqsCommunicateDto.setTime(LocalDateTimeUtil.format(dataVDTO.getTimeid(), DatePattern.NORM_DATETIME_PATTERN));
                 pqsCommunicateDto.setDevId(temp);
                 pqsCommunicateDto.setType(1);
-
+                pqsCommunicateDto.setFlag(1);
 
                 iPqsCommunicate.insertion(pqsCommunicateDto);
             });

data-processing/data-processing-boot/src/main/java/com/njcn/dataProcess/service/impl/influxdb/InfluxdbPqsCommunicateImpl.java

@@ -129,7 +129,9 @@ public class InfluxdbPqsCommunicateImpl implements IPqsCommunicate {
         //更新mysql数据
         DevComFlagDTO devComFlagDTO = new DevComFlagDTO();
         devComFlagDTO.setId(pqsCommunicateDto.getDevId());
-        devComFlagDTO.setDate(LocalDateTime.parse(pqsCommunicateDto.getTime(), DATE_TIME_FORMATTER));
+        if(Objects.equals(pqsCommunicateDto.getFlag(),1)){
+            devComFlagDTO.setDate(LocalDateTime.parse(pqsCommunicateDto.getTime(), DATE_TIME_FORMATTER));
+        }
         devComFlagDTO.setStatus(pqsCommunicateDto.getType());
 
         deviceFeignClient.updateDevComFlag(devComFlagDTO);