异常事件时空分布(拥堵、失衡、溢出、空放)

signal-optimize-service/src/main/java/net/wanji/opt/service/impl/RunningEvaluateServiceImpl.java

@@ -294,8 +294,8 @@ public class RunningEvaluateServiceImpl implements RunningEvaluateService {
         Date startDate = bo.getStartDate();
         Date endDate = bo.getEndDate();
         endDate = DateUtil.offsetDay(endDate, 1); // 包含最后一天
-        int startStamp = (int) (startDate.getTime() / 1000); // 10位时间戳
-        int endStamp = (int) (endDate.getTime() / 1000);
+//        int startStamp = (int) (startDate.getTime() / 1000); // 10位时间戳
+//        int endStamp = (int) (endDate.getTime() / 1000);
 
         String startTime = DateUtil.format(startDate, "yyyy-MM-dd HH:mm:ss");
         String endTime = DateUtil.format(endDate, "yyyy-MM-dd HH:mm:ss");
@@ -315,8 +315,9 @@ public class RunningEvaluateServiceImpl implements RunningEvaluateService {
                 .filter(metricHistDTO -> metricHistDTO.getStatus() != null && metricHistDTO.getStatus().equals(status))
                 .collect(Collectors.toList());
 
-        //5. 整合数据
+        //5. 整合数据（按状态、时间区间重叠合并，并计算持续时间）
         runningEvaluateStatusVO.setProblemStatusList(buildProblemStatusList(filteredList));
+        //1天时间每5分钟一个时间点列表 ["00:15", "00:30" ... ]
         runningEvaluateStatusVO.setTimeList(TimeArrayUtil.getMinuteSectionArray(5));
 
         return runningEvaluateStatusVO;
@@ -604,14 +605,13 @@ public class RunningEvaluateServiceImpl implements RunningEvaluateService {
         }
     }
 
-    List<RunningEvaluateMetricsDetailVO.ProblemStatus> buildProblemStatusList(
-            List<MetricHistDTO> metricHistDTOList) {
+    List<RunningEvaluateMetricsDetailVO.ProblemStatus> buildProblemStatusList(List<MetricHistDTO> metricHistDTOList) {
         List<RunningEvaluateMetricsDetailVO.ProblemStatus> res = new ArrayList<>();
-        // 验证数据是否正确
+        //1. 验证数据是否正确
         if (!isDataValid(metricHistDTOList)) {
             return res;
         }
-        // 根据持续时长去重
+        //2. 分组，并找出最大持续时长，最终获取最大持续时长的数据DTO
         List<MetricHistDTO> uniqueList = metricHistDTOList.stream()
                 .collect(Collectors.groupingBy(
                         MetricHistDTO::getStartTime, // 按startTime分组
@@ -623,20 +623,23 @@ public class RunningEvaluateServiceImpl implements RunningEvaluateService {
                 ))
                 .values().stream().collect(Collectors.toList()); // 从Map中获取值并收集到新的列表中
 
+        //3. 循环最大持续时长的数据DTO集合
+        // 设置状态，开始时间，结束时间，持续时长
         for (MetricHistDTO metricHistDTO : uniqueList) {
-            RunningEvaluateMetricsDetailVO.ProblemStatus problemStatus =
-                    new RunningEvaluateMetricsDetailVO.ProblemStatus();
+            RunningEvaluateMetricsDetailVO.ProblemStatus problemStatus = new RunningEvaluateMetricsDetailVO.ProblemStatus();
             Integer status1 = metricHistDTO.getStatus();
-            problemStatus.setStatus(status1);
-            Date startTime1 = metricHistDTO.getStartTime();
-            problemStatus.setStartTime(startTime1);
             Integer duration1 = metricHistDTO.getDuration();
+            Date startTime1 = metricHistDTO.getStartTime();
             DateTime endTime = DateUtil.offsetMinute(startTime1, duration1);
-            problemStatus.setEndTime(endTime);
-            problemStatus.setDurationMinutes(duration1);
+
+            problemStatus.setStatus(status1);//状态
+            problemStatus.setStartTime(startTime1);//开始时间
+            problemStatus.setEndTime(endTime);//结束时间
+            problemStatus.setDurationMinutes(duration1);//持续时长
             res.add(problemStatus);
         }
 
+        //4. 按状态和开始时间排序
         // 合并时间区间
         // 先按 status 排序，status 相同再按 startTime 排序
         List<RunningEvaluateMetricsDetailVO.ProblemStatus> sortedList = res.stream()
@@ -647,14 +650,22 @@ public class RunningEvaluateServiceImpl implements RunningEvaluateService {
         List<RunningEvaluateMetricsDetailVO.ProblemStatus> mergedList = new ArrayList<>();
         RunningEvaluateMetricsDetailVO.ProblemStatus current = sortedList.get(0);
 
+        //5. 合并时间区间（同一个状态，时间区间重叠的要合并，并计算新的持续时长）
+        /*
+            初始化current为排序后列表的第一个元素。
+            遍历剩余元素，逐一与current比较：
+            如果current和next的状态相同且时间区间重叠（即current.getEndTime()不早于next.getStartTime()），则合并两者：
+            更新current的结束时间为两者结束时间的较大值。
+            重新计算current的持续时长。
+            如果不重叠，则将current添加到mergedList中，并将current更新为next。
+            最后，将最后一个current添加到mergedList中。
+         */
         for (int i = 1; i < sortedList.size(); i++) {
             RunningEvaluateMetricsDetailVO.ProblemStatus next = sortedList.get(i);
-            if (Objects.equals(current.getStatus(), next.getStatus())
-                    && !current.getEndTime().before(next.getStartTime())) {
-                // 如果有交叉，则合并记录
+            if (Objects.equals(current.getStatus(), next.getStatus()) && !current.getEndTime().before(next.getStartTime())) {
+                // 如果时间有交叉，则合并记录
                 current.setEndTime(new Date(Math.max(current.getEndTime().getTime(), next.getEndTime().getTime())));
-                current.setDurationMinutes(
-                        (int) ((current.getEndTime().getTime() - current.getStartTime().getTime()) / (60 * 1000)));
+                current.setDurationMinutes((int) ((current.getEndTime().getTime() - current.getStartTime().getTime()) / (60 * 1000)));
             } else {
                 // 否则，将当前记录添加到结果列表中，并更新当前记录
                 mergedList.add(current);

signal-optimize-service/src/main/java/net/wanji/opt/service/impl/SceneEvaluateServiceImpl.java

@@ -76,9 +76,8 @@ public class SceneEvaluateServiceImpl implements SceneEvaluateService {
 
         SceneEvaluateAbnormalDistributeVO vo = new SceneEvaluateAbnormalDistributeVO();
 
-        //日期，状态分布（路口状态：0正常；1失衡；2拥堵；3溢出；4死锁；5空放）
-        List<SceneEvaluateAbnormalDistributeVO.TimeDistribution> timeDistributionList =
-                buildTimeDistributionList(crossId, startDate, endDate);
+        //每一天对应的状态列表          （路口状态：0正常；1失衡；2拥堵；3溢出；4死锁；5空放）
+        List<SceneEvaluateAbnormalDistributeVO.TimeDistribution> timeDistributionList = buildTimeDistributionList(crossId, startDate, endDate);
 
         vo.setTimeDateDistributionList(buildTimeDateDistributionList(timeDistributionList));
 
@@ -1336,34 +1335,42 @@ public class SceneEvaluateServiceImpl implements SceneEvaluateService {
         vo.setEmptyReleaseDuration(emptyReleaseDuration/60);
     }
 
-    private List<SceneEvaluateAbnormalDistributeVO.TimeDistribution> buildTimeDistributionList(
-            String crossId, Date startDate, Date endDate) {
+    private List<SceneEvaluateAbnormalDistributeVO.TimeDistribution> buildTimeDistributionList(String crossId, Date startDate, Date endDate) {
+        //返回结果
         List<SceneEvaluateAbnormalDistributeVO.TimeDistribution> res = new ArrayList<>();
+
+        //1. 参数初始化
         Calendar start = Calendar.getInstance();
         Calendar end = Calendar.getInstance();
         start.setTime(startDate);
         end.setTime(endDate);
-        // 使 endDate 包含在内
+
+        // 设置开始和结束日期，并将结束日期加一天以包含整个时间段
         end.add(Calendar.DATE, 1);
 
+        //2. 遍历从开始日期到结束日期的每一天。
         for (Date date = start.getTime(); start.before(end); start.add(Calendar.DATE, 1), date = start.getTime()) {
-            SceneEvaluateAbnormalDistributeVO.TimeDistribution timeDistribution =
-                    new SceneEvaluateAbnormalDistributeVO.TimeDistribution();
+            SceneEvaluateAbnormalDistributeVO.TimeDistribution timeDistribution = new SceneEvaluateAbnormalDistributeVO.TimeDistribution();
+            // 每一天
             timeDistribution.setProblemDate(date);
             // 获取问题列表
             // 路口级别全量数据
             Calendar partEnd = (Calendar) start.clone();
             partEnd.add(Calendar.DAY_OF_MONTH, 1);
+
+            //2.1 查询路口级数据，条件时间范围和路口ID
 //            int startStamp = (int)(start.getTimeInMillis() / 1000);
 //            int endStamp = (int)(partEnd.getTimeInMillis() / 1000);
             String startTime = DateUtil.format(startDate, "yyyy-MM-dd HH:mm:ss");
             String endTime = DateUtil.format(endDate, "yyyy-MM-dd HH:mm:ss");
             List<MetricHistDTO> crossDTOList = crossDataHistMapper.selectMetricHistDTO2(crossId, startTime, endTime);
-            // 过滤有问题的记录
+
+            //2.2 过滤有问题的记录
             List<MetricHistDTO> filteredList = crossDTOList.stream()
                     .filter(metricHistDTO -> metricHistDTO.getStatus() != null && !metricHistDTO.getStatus().equals(0))
                     .collect(Collectors.toList());
 
+            //2.3 整合数据 (路口状态（如拥堵、溢出等），开始时间HH:mm，结束时间HH:mm，持续时间)
             timeDistribution.setProblemStatusList(runningEvaluateService.buildProblemStatusList(filteredList));
             res.add(timeDistribution);
         }