package com.dingzhuo.energy.project.plannedOutput.service.impl;
|
|
import java.util.ArrayList;
|
import java.util.Collections;
|
import java.util.Date;
|
import java.util.List;
|
|
import com.dingzhuo.energy.common.utils.time.TimeManager;
|
import com.dingzhuo.energy.common.utils.time.TimeType;
|
import com.dingzhuo.energy.dataservice.domain.DataItem;
|
import com.dingzhuo.energy.dataservice.service.impl.PeriodDataServiceImpl;
|
import org.apache.logging.log4j.LogManager;
|
import org.apache.logging.log4j.Logger;
|
import org.springframework.beans.factory.annotation.Autowired;
|
import org.springframework.stereotype.Service;
|
import com.dingzhuo.energy.project.plannedOutput.mapper.PlannedOutputMapper;
|
import com.dingzhuo.energy.project.plannedOutput.domain.PlannedOutput;
|
import com.dingzhuo.energy.project.plannedOutput.service.IPlannedOutputService;
|
|
/**
|
* plannedOutputService业务层处理
|
*
|
* @author sys
|
* @date 2020-12-16
|
*/
|
@Service
|
public class PlannedOutputServiceImpl implements IPlannedOutputService
|
{
|
private Logger logger = LogManager.getLogger(PlannedOutputServiceImpl.class);
|
@Autowired
|
private PlannedOutputMapper plannedOutputMapper;
|
|
/**
|
* 查询plannedOutput列表
|
*
|
* @param
|
* @return plannedOutput
|
*/
|
@Override
|
public List<PlannedOutput> selectPlannedOutputList(List<Integer> indexIds, TimeType timeType,Date dataTime,String palnType)
|
{
|
if (indexIds.size() !=0) {
|
String timeCode = TimeManager.getTimeCode(dataTime, timeType);
|
return plannedOutputMapper.selectPlannedOutputList(indexIds, timeCode,palnType);
|
}
|
return Collections.emptyList();
|
}
|
public List<PlannedOutput> selectPlanList(List<Integer> indexIds){
|
if (indexIds.size() !=0) {
|
return plannedOutputMapper.selectPlanList(indexIds);
|
}
|
return Collections.emptyList();
|
}
|
/**
|
* 新增plannedOutput
|
*
|
* @return 结果
|
*/
|
/*@Override
|
public int insertPlannedOutput(PlannedOutput plannedOutput)
|
{
|
return plannedOutputMapper.insertPlannedOutput(plannedOutput);
|
}*/
|
@Override
|
public void insertPlannedOutput(List<PlannedOutput> datas) {
|
List<List<PlannedOutput>> splitDatas = splitList(datas, 100);
|
if (splitDatas != null) {
|
splitDatas.parallelStream().forEach(dataPart -> {
|
/*try {
|
plannedOutputMapper.saveDataList(dataPart);
|
} catch (Exception ex) {
|
logger.error("批量保存数据失败", ex);*/
|
dataPart.parallelStream().forEach(dataItem -> {
|
try {
|
plannedOutputMapper.save(dataItem);
|
} catch (Exception singleEx) {
|
logger.error("单个指标数据保存失败！【" + dataItem + "】", singleEx);
|
}
|
});
|
/* }*/
|
});
|
}
|
}
|
/**
|
* 修改plannedOutput
|
*
|
* @param plannedOutput plannedOutput
|
* @return 结果
|
*/
|
@Override
|
public int updatePlannedOutput(PlannedOutput plannedOutput)
|
{
|
return plannedOutputMapper.updatePlannedOutput(plannedOutput);
|
}
|
public static <E> List<List<E>> splitList(List<E> targetList, Integer splitSize) {
|
if (targetList == null) {
|
return Collections.emptyList();
|
}
|
|
int size = targetList.size();
|
List<List<E>> resultList = new ArrayList<>();
|
if (size <= splitSize) {
|
resultList.add(targetList);
|
} else {
|
for (int i = 0; i < size; i += splitSize) {
|
//用于限制最后一部分size小于splitSize的list
|
int limit = i + splitSize;
|
if (limit > size) {
|
limit = size;
|
}
|
resultList.add(targetList.subList(i, limit));
|
}
|
}
|
return resultList;
|
}
|
}
|
