Files
pqs-influx/src/main/java/com/njcn/influx/service/impl/DataFlickerServiceImpl.java

96 lines
3.8 KiB
Java

package com.njcn.influx.service.impl;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.njcn.influx.imapper.DataFlickerMapper;
import com.njcn.influx.pojo.dto.DataFlickerDTO;
import com.njcn.influx.pojo.po.DataFlicker;
import com.njcn.influx.query.InfluxQueryWrapper;
import com.njcn.influx.service.DataFlickerService;
import org.springframework.stereotype.Service;
import javax.annotation.Resource;
import java.util.ArrayList;
import java.util.List;
/**
* @author hongawen
* @version 1.0.0
* @date 2023年05月05日 09:05
*/
@Service
public class DataFlickerServiceImpl implements DataFlickerService {
@Resource
private DataFlickerMapper dataFlickerMapper;
@Override
public List<DataFlickerDTO> getDataFlicker(String lineIndex, String startTime, String endTime) {
//最小值
List<DataFlickerDTO> result1 ;
InfluxQueryWrapper influxQueryWrapper = new InfluxQueryWrapper(DataFlicker.class, DataFlickerDTO.class);
influxQueryWrapper.eq(DataFlicker::getLineId, lineIndex)
.min(DataFlicker::getFluc)
.min(DataFlicker::getPlt)
.min(DataFlicker::getPst)
.groupBy(DataFlicker::getLineId,DataFlicker::getPhaseType,DataFlicker::getQualityFlag)
.between(DataFlicker::getTime, startTime, endTime);
result1 = dataFlickerMapper.getStatisticsByWraper(influxQueryWrapper);
result1.forEach(item -> {
item.setValueType("MIN");
});
//最大值
List<DataFlickerDTO> result2 ;
influxQueryWrapper.initSql();
influxQueryWrapper.eq(DataFlicker::getLineId, lineIndex)
.max(DataFlicker::getFluc)
.max(DataFlicker::getPlt)
.max(DataFlicker::getPst)
.groupBy(DataFlicker::getLineId,DataFlicker::getPhaseType,DataFlicker::getQualityFlag)
.between(DataFlicker::getTime, startTime, endTime);
result2 = dataFlickerMapper.getStatisticsByWraper(influxQueryWrapper);
result2.forEach(item -> {
item.setValueType("MAX");
});
//平均值
List<DataFlickerDTO> result3 ;
influxQueryWrapper.initSql();
influxQueryWrapper.eq(DataFlicker::getLineId, lineIndex)
.mean(DataFlicker::getFluc)
.mean(DataFlicker::getPlt)
.mean(DataFlicker::getPst)
.groupBy(DataFlicker::getLineId,DataFlicker::getPhaseType,DataFlicker::getQualityFlag)
.between(DataFlicker::getTime, startTime, endTime);
result3 = dataFlickerMapper.getStatisticsByWraper(influxQueryWrapper);
result3.forEach(item -> {
item.setValueType("AVG");
});
List<DataFlickerDTO> result4 ;
influxQueryWrapper.initSql();
influxQueryWrapper.eq(DataFlicker::getLineId, lineIndex)
.percentile(DataFlicker::getFluc, 95)
.percentile(DataFlicker::getPlt, 95)
.percentile(DataFlicker::getPst, 95)
.groupBy(DataFlicker::getLineId,DataFlicker::getPhaseType,DataFlicker::getQualityFlag)
.between(DataFlicker::getTime, startTime, endTime);
//CP95值
result4 = dataFlickerMapper.getStatisticsByWraper(influxQueryWrapper);
result4.forEach(item -> {
item.setValueType("CP95");
});
List<DataFlickerDTO> result = new ArrayList<>();
result.addAll(result1);
result.addAll(result2);
result.addAll(result3);
result.addAll(result4);
ObjectMapper objectMapper = new ObjectMapper();
try {
System.out.println(objectMapper.writeValueAsString(result));
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
return result;
}
}