From 13622b9e0d09945a7cad4e43d9cdf242d3b9b3f8 Mon Sep 17 00:00:00 2001
From: dengzedong <dengzedong@email>
Date: 星期四, 26 六月 2025 11:04:48 +0800
Subject: [PATCH] 动态长度
---
iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mcs/pre/service/impl/MmPredictAutoAdjustConfigServiceImpl.java | 289 ++++++++++++++++++++++++++++++++++-----------------------
1 files changed, 171 insertions(+), 118 deletions(-)
diff --git a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mcs/pre/service/impl/MmPredictAutoAdjustConfigServiceImpl.java b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mcs/pre/service/impl/MmPredictAutoAdjustConfigServiceImpl.java
index 8543f88..29fe746 100644
--- a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mcs/pre/service/impl/MmPredictAutoAdjustConfigServiceImpl.java
+++ b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mcs/pre/service/impl/MmPredictAutoAdjustConfigServiceImpl.java
@@ -4,6 +4,7 @@
import com.iailab.framework.common.pojo.PageResult;
import com.iailab.framework.common.service.impl.BaseServiceImpl;
import com.iailab.module.data.api.point.DataPointApi;
+import com.iailab.module.data.api.point.dto.ApiPointDTO;
import com.iailab.module.data.api.point.dto.ApiPointValueDTO;
import com.iailab.module.data.api.point.dto.ApiPointValueQueryDTO;
import com.iailab.module.model.common.enums.DataTypeEnum;
@@ -27,6 +28,7 @@
import java.math.BigDecimal;
import java.util.*;
+import java.util.function.Predicate;
import java.util.stream.Collectors;
/**
@@ -58,13 +60,14 @@
}
@Override
- public MmPredictAutoAdjustConfigEntity getByCode(String code) {
- return baseDao.selectOne("config_code",code,"is_enable",1);
+ public List<MmPredictAutoAdjustConfigEntity> getByCode(String code) {
+ return baseDao.selectList(MmPredictAutoAdjustConfigEntity::getConfigCode,code,MmPredictAutoAdjustConfigEntity::getIsEnable,1);
}
@Override
public void create(MmPredictAutoAdjustConfigEntity entity) {
entity.setId(UUID.randomUUID().toString());
+ entity.setCreateTime(new Date());
baseDao.insert(entity);
}
@@ -80,137 +83,187 @@
@Override
public boolean autoAdjustByCode(String configCode,long adjustStartTime) {
+ log.info("开始自动调整：configCode：" + configCode + ",adjustStartTime:" + new Date(adjustStartTime));
// 查询调整配置
- MmPredictAutoAdjustConfigEntity configEntity = getByCode(configCode);
- if (configEntity == null) {
- log.info("自动调整失败原因：configEntity为null");
+ List<MmPredictAutoAdjustConfigEntity> configEntityList = getByCode(configCode);
+ if (CollectionUtils.isEmpty(configEntityList)) {
+ log.info("自动调整失败原因：configEntityList为空");
return false;
}
- Double adjustValue = 0.0;
- ApiPointValueQueryDTO queryDTO;
- Calendar calendar = Calendar.getInstance();
- calendar.setTimeInMillis(adjustStartTime);
- Date endTime;
- Date startTime;
- List<ApiPointValueDTO> apiPointValueDTOS;
- // 判断是否调整
- AutoAdjustTriggerRuleEnum triggerRuleEnum = AutoAdjustTriggerRuleEnum.fromCode(configEntity.getTriggerRule());
- switch (triggerRuleEnum) {
- case SLOPE:
- queryDTO = new ApiPointValueQueryDTO();
- queryDTO.setPointNo(dataPointApi.getInfoById(configEntity.getPointId()).getPointNo());
- endTime = calendar.getTime();
+ // 根据outputId分组
+ Map<String, List<MmPredictAutoAdjustConfigEntity>> outputIdMap = configEntityList.stream().collect(Collectors.groupingBy(MmPredictAutoAdjustConfigEntity::getOutputId));
+ for (Map.Entry<String, List<MmPredictAutoAdjustConfigEntity>> entry : outputIdMap.entrySet()) {
+ String outputId = entry.getKey();
+ // 查询调整用户adjustStartTime 至 adjustStartTime - 预测长度 * 预测粒度 范围的值
+ Calendar calendar = Calendar.getInstance();
+ calendar.setTimeInMillis(adjustStartTime);
+ Date endTime = calendar.getTime();
+ ItemVO item = mmPredictItemService.getItemByOutPutId(outputId);
+ if (item == null) {
+ log.info("自动调整失败原因：getItemByOutPutId为null，outputId：" + outputId);
+ continue;
+ }
+ calendar.add(Calendar.SECOND,item.getPredictLength() * item.getGranularity() * -1);
+ Date startTime = calendar.getTime();
+
+ // 获取预测历史结果
+ InfluxModelResultPOJO pojo = new InfluxModelResultPOJO();
+ pojo.setType(DataTypeEnum.FLOAT_LAST_BAK.getCode());
+ pojo.setOutPutId(outputId);
+ List<InfluxModelResultVO> influxModelResult = influxDBService.queryModelResults(pojo, new Date(adjustStartTime), new Date(adjustStartTime));
+ if (CollectionUtils.isEmpty(influxModelResult)) {
+ log.info("自动调整失败原因：预测历史结果为空。itemNo：" + item.getItemNo() + "，itemName:" + item.getItemName() + "，outputId:" + outputId + "，time:" + adjustStartTime);
+ continue;
+ }
+
+ // 计算所有影响用户的最终调整值
+ Double finalAdjustValue = 0.0;
+ for (MmPredictAutoAdjustConfigEntity configEntity : entry.getValue()) {
+ Double adjustValue = null;
+ // 查询影响用户历史值
+ ApiPointValueQueryDTO queryDTO = new ApiPointValueQueryDTO();
+ ApiPointDTO pointInfo = dataPointApi.getInfoById(configEntity.getPointId());
+ if (pointInfo == null) {
+ log.info("自动调整失败原因：影响用户pointInfo为空。pointId：" + configEntity.getPointId() + "configCode：" + configEntity.getConfigCode() + "configName：" + configEntity.getConfigName());
+ continue;
+ }
+ log.info("自动调整开始处理：configName：" + configEntity.getConfigName() + "影响用户：" + pointInfo.getPointName());
+ queryDTO.setPointNo(pointInfo.getPointNo());
queryDTO.setEnd(endTime);
- calendar.add(Calendar.MINUTE,-1 * configEntity.getT());
- startTime = calendar.getTime();
queryDTO.setStart(startTime);
- apiPointValueDTOS = dataPointApi.queryPointHistoryValue(queryDTO);
+ List<ApiPointValueDTO> apiPointValueDTOS = dataPointApi.queryPointHistoryValue(queryDTO);
if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
- log.info("自动调整失败原因：测点数据长度为0");
- return false;
+ log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：测点数据长度为0。queryDTO：" + queryDTO);
+ continue;
}
- apiPointValueDTOS = apiPointValueDTOS.stream().filter(e -> e.getV() != -2).collect(Collectors.toList());
+ // 过滤掉-2
+ apiPointValueDTOS = apiPointValueDTOS.stream().filter(e -> !Double.valueOf(e.getV()).equals(-2.0)).collect(Collectors.toList());
if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
- log.info("自动调整失败原因：测点数据长度为0");
- return false;
+ log.info("影响用户调整失败原因：过滤掉-2之后测点数据长度为0。queryDTO：" + queryDTO);
+ continue;
}
- Optional<ApiPointValueDTO> startOptional = apiPointValueDTOS.stream().filter(e -> e.getT().equals(startTime)).findFirst();
- if (!startOptional.isPresent()) {
- log.info("自动调整失败原因：计算斜率startTime时间点测点值为null，startTime：" + startTime);
- return false;
- }
- Optional<ApiPointValueDTO> endOptional = apiPointValueDTOS.stream().filter(e -> e.getT().equals(endTime)).findFirst();
- if (!endOptional.isPresent()) {
- log.info("自动调整失败原因：计算斜率endTime时间点测点值为null，endTime：" + endTime);
- return false;
- }
- ApiPointValueDTO startPointValue = startOptional.get();
- ApiPointValueDTO endPointValue = endOptional.get();
- // 计算斜率，有正负之分，代表上升或下降
- double slope = BigDecimal.valueOf(endPointValue.getV() - startPointValue.getV()).divide(BigDecimal.valueOf(configEntity.getT())).doubleValue();
- //斜率绝对值大于等于触发值则进行调整
- if (Double.valueOf(Math.abs(slope)).compareTo(configEntity.getTriggerValue()) >= 0) {
- //计算调整值
- HashMap<String,Object> map = new HashMap<>();
- map.put("startValue",startPointValue.getV());
- map.put("endValue",endPointValue.getV());
- adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), map);
- } else {
- log.info("自动调整失败原因：斜率小于调整值，斜率:" + slope);
- return false;
+ // 触发规则
+ AutoAdjustTriggerRuleEnum triggerRuleEnum = AutoAdjustTriggerRuleEnum.fromCode(configEntity.getTriggerRule());
+ // 判断是否符合触发条件 并计算调整值
+ switch (triggerRuleEnum) {
+ case SLOPE:
+ // 计算每个△t的斜率，任意一个大于触发值则认为该区间有调整
+ Calendar slopeCalendar = Calendar.getInstance();
+ slopeCalendar.setTime(startTime);
+ Date slopeStartTime = slopeCalendar.getTime();
+ slopeCalendar.add(Calendar.MINUTE,configEntity.getT());
+ Date slopeEndTime = slopeCalendar.getTime();
+ if (slopeEndTime.after(endTime)) {
+ log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：△t设置过大，大于模型预测长度 * 预测粒度。△t：" + configEntity.getT());
+ continue;
+ }
+ while (!slopeEndTime.after(endTime)) {
+ //计算斜率
+ //△t开始时间测点值
+ Date finalSlopeStartTime = slopeStartTime;
+ Optional<ApiPointValueDTO> startOptional = apiPointValueDTOS.stream().filter(apiPointValueDTO -> apiPointValueDTO.getT().equals(finalSlopeStartTime)).findFirst();
+ //△t结束时间测点值
+ Date finalSlopeEndTime = slopeEndTime;
+ Optional<ApiPointValueDTO> endOptional = apiPointValueDTOS.stream().filter(e -> e.getT().equals(finalSlopeEndTime)).findFirst();
+ if (startOptional.isPresent() && endOptional.isPresent()) {
+ ApiPointValueDTO startPointValue = startOptional.get();
+ ApiPointValueDTO endPointValue = endOptional.get();
+ // 计算斜率
+ double slope = BigDecimal.valueOf(endPointValue.getV() - startPointValue.getV()).divide(BigDecimal.valueOf(configEntity.getT())).doubleValue();
+ // 斜率大于等于触发值则进行调整
+ if (Double.valueOf(Math.abs(slope)).compareTo(configEntity.getTriggerValue()) >= 0) {
+ // 计算调整值 并跳出循环
+ adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), apiPointValueDTOS);
+ log.info("计算调整值：" + adjustValue + "，斜率：" + slope + "，pointNo：" + pointInfo.getPointNo() + "，pointName：" + pointInfo.getPointName() + "，slopeStartTime：" + slopeStartTime + "，slopeEndTime：" + slopeEndTime);
+ break;
+ }
+ log.info("斜率不满足条件，斜率：" + slope);
+ }
+ // 下一个△t
+ slopeStartTime = slopeCalendar.getTime();
+ slopeCalendar.add(Calendar.MINUTE,configEntity.getT());
+ slopeEndTime = slopeCalendar.getTime();
+ }
+ break;
+ case AVERAGE_GAP:
+ // 计算每两个△t的平均差，任意一个大于触发值则认为该区间有调整
+ Calendar averageCalendar = Calendar.getInstance();
+ averageCalendar.setTime(startTime);
+ Date averageStartTime = averageCalendar.getTime();
+ averageCalendar.add(Calendar.MINUTE,configEntity.getT());
+ Date averageMiddleTime = averageCalendar.getTime();
+ averageCalendar.add(Calendar.MINUTE,configEntity.getT());
+ Date averageEndTime = averageCalendar.getTime();
+
+ if (averageEndTime.after(endTime)) {
+ log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：△t设置过大，△t*2大于模型预测长度 * 预测粒度。△t：" + configEntity.getT());
+ continue;
+ }
+ while (!averageEndTime.after(endTime)) {
+ //计算均值差
+ //前△t测点平均值
+ Date finalAverageStartTime = averageStartTime;
+ Date finalAverageMiddleTime = averageMiddleTime;
+ OptionalDouble startAverage = apiPointValueDTOS.stream().filter(e -> e.getT().after(finalAverageStartTime) && !e.getT().after(finalAverageMiddleTime)).mapToDouble(ApiPointValueDTO::getV).average();
+ //后△t测点平均值
+ Date finalAverageEndTime = averageEndTime;
+ OptionalDouble endAverage = apiPointValueDTOS.stream().filter(e -> e.getT().after(finalAverageMiddleTime) && !e.getT().after(finalAverageEndTime)).mapToDouble(ApiPointValueDTO::getV).average();
+ if (startAverage.isPresent() && endAverage.isPresent()) {
+ double averageGapValue = startAverage.getAsDouble() - endAverage.getAsDouble();
+ // 均值差，大于等于触发值则进行调整
+ if (Double.valueOf(Math.abs(averageGapValue)).compareTo(configEntity.getTriggerValue()) >= 0) {
+ // 计算调整值 并跳出循环
+ adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), apiPointValueDTOS);
+ log.info("计算调整值：" + adjustValue + "，均值差：" + averageGapValue + "，pointNo：" + pointInfo.getPointNo() + "，pointName：" + pointInfo.getPointName() + "，averageStartTime：" + averageStartTime + "，averageMiddleTime：" + averageMiddleTime + "，averageEndTime：" + averageEndTime);
+ break;
+ }
+ log.info("均值差不满足条件，均值差：" + averageGapValue);
+ }
+
+ // 下一个△t
+ averageStartTime = averageMiddleTime;
+ averageMiddleTime = averageEndTime;
+ averageCalendar.add(Calendar.MINUTE,configEntity.getT());
+ averageEndTime = averageCalendar.getTime();
+ }
+ break;
+ default:
+ log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：未知触发规则,triggerRule" + configEntity.getTriggerRule());
+ continue;
}
- break;
- case AVERAGE_GAP:
- queryDTO = new ApiPointValueQueryDTO();
- queryDTO.setPointNo(dataPointApi.getInfoById(configEntity.getPointId()).getPointNo());
- endTime = calendar.getTime();
- queryDTO.setEnd(endTime);
- calendar.add(Calendar.MINUTE,-1 * configEntity.getT() * 2 + 1);
- startTime = calendar.getTime();
- queryDTO.setStart(startTime);
- apiPointValueDTOS = dataPointApi.queryPointHistoryValue(queryDTO);
- if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
- log.info("自动调整失败原因：测点数据长度为0");
- return false;
+ if (adjustValue == null) {
+ log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：未达到触发条件");
+ continue;
}
- apiPointValueDTOS = apiPointValueDTOS.stream().filter(e -> e.getV() != -2).collect(Collectors.toList());
- if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
- log.info("自动调整失败原因：测点数据长度为0");
- return false;
- }
- calendar.add(Calendar.MINUTE,configEntity.getT());
- double startAverage = apiPointValueDTOS.stream().filter(e -> e.getT().before(calendar.getTime())).collect(Collectors.summarizingDouble(ApiPointValueDTO::getV)).getAverage();
- double endAverage = apiPointValueDTOS.stream().filter(e -> e.getT().compareTo(calendar.getTime()) >= 0).collect(Collectors.summarizingDouble(ApiPointValueDTO::getV)).getAverage();
- // 计算均值差，大于等于触发值则进行调整
- if (Double.valueOf(Math.abs(startAverage - endAverage)).compareTo(configEntity.getTriggerValue()) >= 0) {
- //计算调整值
- HashMap<String,Object> map = new HashMap<>();
- map.put("startValue",startAverage);
- map.put("endValue",endAverage);
- adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), map);
- } else {
- log.info("自动调整失败原因：均值差小于调整值，均值差:" + (startAverage - endAverage));
- return false;
- }
- break;
- default:
- log.info("自动调整失败原因：未知触发规则,triggerRule" + configEntity.getTriggerRule());
- return false;
+
+ // 调整系数
+ adjustValue = adjustValue * configEntity.getAdjustCoefficient();
+ // 调整方向
+ adjustValue = adjustValue * configEntity.getAdjustDirection();
+ // 累加到最终调整值
+ finalAdjustValue += adjustValue;
+ }
+ // 执行调整
+ if (finalAdjustValue.equals(0.0)) {
+ log.info("自动调整失败原因：finalAdjustValue为0，outputId：" + outputId + "，configCode:" + configCode);
+ continue;
+ }
+ List<InfluxModelResultPOJO> lastList = new ArrayList<>();
+ for (InfluxModelResultVO resultVO : influxModelResult) {
+ InfluxModelResultLastSimPOJO adjustPojo = new InfluxModelResultLastSimPOJO();
+ // 设置新的调整值
+ adjustPojo.setValue(Double.parseDouble(resultVO.getValue().toString()) + finalAdjustValue);
+ adjustPojo.setTimestamp(resultVO.getTimestamp());
+ adjustPojo.setOutPutId(outputId);
+ lastList.add(adjustPojo);
+ }
+ // 相同时间直接覆盖旧值
+ influxDBService.asyncWriteModelResults(lastList);
+ log.info("t+l自动调整。configCode:" + configCode + ",adjustValue:" + finalAdjustValue + "，itemNo：" + item.getItemNo() + "，itemName：" + item.getItemName() + "，outputId：" + outputId + ",adjustTime：" + adjustStartTime);
}
- // 调整方向
- adjustValue = adjustValue * configEntity.getAdjustDirection();
-
- // 获取历史结果
- ItemVO item = mmPredictItemService.getItemByOutPutId(configEntity.getOutputId());
- if (item == null) {
- log.info("自动调整失败原因：getItemByOutPutId为null，outputId：" + configEntity.getOutputId());
- return false;
- }
- Calendar resultCalendar = Calendar.getInstance();
- resultCalendar.setTimeInMillis(adjustStartTime);
- Date resultStartTime = resultCalendar.getTime();
- resultCalendar.add(Calendar.SECOND,configEntity.getAdjustLength() * item.getGranularity());
- Date resultEndTime = resultCalendar.getTime();
- InfluxModelResultPOJO pojo = new InfluxModelResultPOJO();
- pojo.setType(DataTypeEnum.FLOAT_LAST_BAK.getCode());
- pojo.setOutPutId(configEntity.getOutputId());
- List<InfluxModelResultVO> influxModelResult = influxDBService.queryModelResults(pojo, resultStartTime, resultEndTime);
-
- List<InfluxModelResultPOJO> lastList = new ArrayList<>();
- for (InfluxModelResultVO resultVO : influxModelResult) {
- InfluxModelResultLastSimPOJO adjustPojo = new InfluxModelResultLastSimPOJO();
- // 设置新的调整值
- adjustPojo.setValue(Double.parseDouble(resultVO.getValue().toString()) + adjustValue);
- adjustPojo.setTimestamp(resultVO.getTimestamp());
- adjustPojo.setOutPutId(configEntity.getOutputId());
- lastList.add(adjustPojo);
- }
- // 相同时间直接覆盖旧值
- influxDBService.asyncWriteModelResults(lastList);
- log.info("t+l自动调整。configCode:" + configCode + ",adjustValue:" + adjustValue + ",resultStartTime：" + resultStartTime + ",resultEndTime：" + resultEndTime + "调整长度：" + lastList.size());
return true;
}
}
\ No newline at end of file
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