From 3e15efd83d12f5e24bc56a3d66ddbe3633270f7f Mon Sep 17 00:00:00 2001
From: dengzedong <dengzedong@email>
Date: 星期五, 20 六月 2025 12:30:28 +0800
Subject: [PATCH] 绝对值累计
---
iailab-module-data/iailab-module-data-biz/src/main/java/com/iailab/module/data/point/collection/handler/CumulateHandle.java | 43 +++++++++++++++++++++++++++++++++++++------
1 files changed, 37 insertions(+), 6 deletions(-)
diff --git a/iailab-module-data/iailab-module-data-biz/src/main/java/com/iailab/module/data/point/collection/handler/CumulateHandle.java b/iailab-module-data/iailab-module-data-biz/src/main/java/com/iailab/module/data/point/collection/handler/CumulateHandle.java
index 58625db..ccb5ede 100644
--- a/iailab-module-data/iailab-module-data-biz/src/main/java/com/iailab/module/data/point/collection/handler/CumulateHandle.java
+++ b/iailab-module-data/iailab-module-data-biz/src/main/java/com/iailab/module/data/point/collection/handler/CumulateHandle.java
@@ -23,6 +23,7 @@
import javax.annotation.Resource;
import java.math.BigDecimal;
import java.util.*;
+import java.util.concurrent.TimeUnit;
/**
* 累计点处理
@@ -45,7 +46,7 @@
@Autowired
private RedisTemplate<String, Object> redisTemplate;
- public List<InfluxPointValuePOJO> handle(Date collectTime, List<DaPointDTO> dtos, List<String> listGood, List<String> listBad) {
+ public List<InfluxPointValuePOJO> handle(Date collectTime, List<DaPointDTO> dtos, Map<String, Object> dataMap, List<String> listGood, List<String> listBad) {
List<InfluxPointValuePOJO> result = new ArrayList<>();
try {
log.info("累计点处理开始");
@@ -54,9 +55,12 @@
}
dtos.forEach(dto -> {
try {
- Object value = singleCompute(dto, collectTime, listGood, listBad);
- InfluxPointValuePOJO pojo = GenInfluxPointValueUtils.getByPoint(dto, value);
+ Object rawValue = singleCompute(dto, collectTime, listGood, listBad);
+ BigDecimal coefficient = dto.getUnittransfactor() == null ? BigDecimal.ONE : dto.getUnittransfactor();
+ BigDecimal calValue = new BigDecimal(rawValue.toString()).multiply(coefficient);
+ InfluxPointValuePOJO pojo = GenInfluxPointValueUtils.getByPoint(dto, calValue);
pojo.setTimestamp(GenInfluxPointValueUtils.getByMin(collectTime, DataPointFreqEnum.getEumByCode(dto.getMinfreqid())));
+ dataMap.put(dto.getPointNo(), calValue);
result.add(pojo);
} catch (Exception ex) {
ex.printStackTrace();
@@ -85,7 +89,12 @@
if (redisTemplate.hasKey(PointCollector.PV + item.getPointNo())) {
value = redisTemplate.opsForValue().get(PointCollector.PV + item.getPointNo());
} else {
- value = singleCompute(item, calendar.getTime());
+ Object rawValue = singleCompute(item, calendar.getTime());
+ BigDecimal coefficient = item.getUnittransfactor() == null ? BigDecimal.ONE : item.getUnittransfactor();
+ value = new BigDecimal(rawValue.toString()).multiply(coefficient);
+ // 写入缓存
+ redisTemplate.opsForValue().set(PointCollector.PV + item.getPointNo(),
+ new BigDecimal(value.toString()).doubleValue(), PointCollector.offset, TimeUnit.SECONDS);
}
data.put(item.getPointNo(), value);
});
@@ -119,7 +128,29 @@
queryDto.setEnd(endTime);
queryDto.setPointNo(dto.getMomentPoint());
log.info("queryDto=" + JSONObject.toJSONString(queryDto));
- List<ApiPointValueDTO> dataList = dataPointApi.queryPointHistoryValue(queryDto);
+ List<ApiPointValueDTO> dataList = new ArrayList<>();
+ List<ApiPointValueDTO> dataListTemp = dataPointApi.queryPointHistoryValue(queryDto);
+ if (dto.getIsCumuNeg() != null) {
+ if (dto.getIsCumuNeg().equals(0)) {
+ // 不累计负值
+ for (ApiPointValueDTO item : dataListTemp) {
+ if (item.getV() > 0) {
+ dataList.add(item);
+ }
+ }
+ }else if (dto.getIsCumuNeg().equals(2)) {
+ // 绝对值累计
+ for (ApiPointValueDTO item : dataListTemp) {
+ item.setV(Math.abs(item.getV()));
+ dataList.add(item);
+ }
+ }else {
+ dataList = dataListTemp;
+ }
+ } else {
+ dataList = dataListTemp;
+ }
+
if (CollectionUtils.isEmpty(dataList)) {
log.info("dataList is empty");
if (listGood != null) {
@@ -148,7 +179,7 @@
long start = startTime.getTime();
long end = endTime.getTime();
long oneMin = 1000L * DataPointFreqEnum.getEumByCode(minfreqid).getValue();
- long mins = (end - start) / oneMin;
+ long mins = ((end - start) / oneMin) + 1;
//找出缺少项
Map<Long, Double> sourceDataMap = new HashMap<>(dataList.size());
--
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