iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java

@@ -1,15 +1,13 @@
package com.iailab.module.model.api;

import com.alibaba.fastjson.JSON;
import com.iailab.framework.common.util.object.ConvertUtils;
import com.iailab.module.model.api.mdk.MdkApi;
import com.iailab.module.model.api.mdk.dto.*;
import com.iailab.module.model.mcs.pre.entity.DmModuleEntity;
import com.iailab.module.model.mcs.pre.service.DmModuleService;
import com.iailab.module.model.mcs.pre.service.MmPredictItemService;
import com.iailab.module.model.mdk.factory.ItemEntityFactory;
import com.iailab.module.model.mdk.factory.PredictItemFactory;
import com.iailab.module.model.mdk.predict.PredictItemHandler;
import com.iailab.module.model.mcs.sche.service.StScheduleRecordService;
import com.iailab.module.model.mcs.sche.service.StScheduleSchemeService;
import com.iailab.module.model.mdk.predict.PredictModuleHandler;
import com.iailab.module.model.mdk.predict.PredictResultHandler;
import com.iailab.module.model.mdk.schedule.ScheduleModelHandler;
@@ -25,9 +23,6 @@

import java.util.*;
import java.util.stream.Collectors;

import static com.iailab.framework.common.pojo.CommonResult.error;
import static com.iailab.framework.common.pojo.CommonResult.success;

/**
 * @author PanZhibao
@@ -49,16 +44,16 @@
    private PredictModuleHandler predictModuleHandler;

    @Autowired
    private ItemEntityFactory itemEntityFactory;

    @Autowired
    private PredictItemFactory predictItemFactory;

    @Autowired
    private PredictResultHandler predictResultHandler;

    @Autowired
    private ScheduleModelHandler scheduleModelHandler;

    @Autowired
    private StScheduleRecordService stScheduleRecordService;

    @Autowired
    private StScheduleSchemeService stScheduleSchemeService;

    /**
     * 按模块预测
@@ -101,10 +96,10 @@
                // 分组，先运行normal预测项，再将结果传递给merge预测项
                List<ItemVO> normalItems = predictItemList.stream().filter(e -> e.getItemType().equals("NormalItem")).collect(Collectors.toList());
                if (!CollectionUtils.isEmpty(normalItems)) {
                    predictModuleHandler.predict(normalItems, reqDTO.getPredictTime(), intervalTime,predictResultMap);
                    List<ItemVO> mergeItem = predictItemList.stream().filter(e -> e.getItemType().equals("MergeItem")).collect(Collectors.toList());
                    if (!CollectionUtils.isEmpty(mergeItem)) {
                        predictModuleHandler.predict(mergeItem, reqDTO.getPredictTime(), intervalTime,predictResultMap);
                    predictModuleHandler.predict(normalItems, reqDTO.getPredictTime(), intervalTime, predictResultMap);
                    List<ItemVO> mergeItems = predictItemList.stream().filter(e -> e.getItemType().equals("MergeItem")).collect(Collectors.toList());
                    if (!CollectionUtils.isEmpty(mergeItems)) {
                        predictModuleHandler.predict(mergeItems, reqDTO.getPredictTime(), intervalTime, predictResultMap);
                    }
                }
                // 更新Module时间
@@ -150,27 +145,31 @@
    @Override
    public MdkPredictItemRespDTO predictItem(MdkPredictReqDTO reqDTO) {
        MdkPredictItemRespDTO resp = new MdkPredictItemRespDTO();

        try {
            log.info("预测计算开始: " + System.currentTimeMillis());
            Map<String, List<MdkPredictDataDTO>> predictData = new HashMap<>();
            ItemVO predictItem = itemEntityFactory.getItemByItemNo(reqDTO.getItemNo());
            PredictItemHandler predictItemHandler = predictItemFactory.create(predictItem.getId());
            PredictResultVO predictResult = predictItemHandler.predict(reqDTO.getPredictTime(), predictItem,null,null);
            Map<String, List<DataValueVO>> resultMap = predictResultHandler.convertToPredictData(predictResult);
            if (!CollectionUtils.isEmpty(resultMap)) {
                for (Map.Entry<String, List<DataValueVO>> entry : resultMap.entrySet()) {
                    List<MdkPredictDataDTO>  data = ConvertUtils.sourceToTarget(entry.getValue(), MdkPredictDataDTO.class);
                    predictData.put(entry.getKey(), data);
                }

            ItemVO itemByItemNo = mmPredictItemService.getItemByItemNo(reqDTO.getItemNo());
            List<ItemVO> predictItemList = new ArrayList<>();
            predictItemList.add(itemByItemNo);
            Map<String, PredictResultVO> predictResultMap = new HashMap<>(predictItemList.size());
            predictModuleHandler.predict(predictItemList, reqDTO.getPredictTime(), 0, predictResultMap);

            Map<String, List<MdkPredictDataDTO>> itemPredictData = new HashMap<>();

            Map<String, List<DataValueVO>> predictLists = predictResultHandler.convertToPredictData2(predictResultMap.get(reqDTO.getItemNo()));
            for (Map.Entry<String, List<DataValueVO>> dataListEntry : predictLists.entrySet()) {
                List<MdkPredictDataDTO> predictData = dataListEntry.getValue().stream().map(t -> {
                    MdkPredictDataDTO dto1 = new MdkPredictDataDTO();
                    dto1.setDataTime(t.getDataTime());
                    dto1.setDataValue(t.getDataValue());
                    return dto1;
                }).collect(Collectors.toList());
                itemPredictData.put(dataListEntry.getKey(), predictData);
            }
            resp.setPredictData(predictData);
            resp.setItemId(predictItem.getId());
            resp.setItemId(reqDTO.getItemNo());
            resp.setPredictTime(reqDTO.getPredictTime());
            log.info("预测计算结束: " + System.currentTimeMillis());
        } catch (Exception ex) {
            log.info("预测计算异常: " + System.currentTimeMillis(), ex);
            return resp;
            resp.setPredictData(itemPredictData);
        } catch (Exception e) {
            throw new RuntimeException(e);
        }

        return resp;
@@ -204,10 +203,12 @@
            log.info("调度计算开始: " + System.currentTimeMillis());
            ScheduleResultVO scheduleResult = scheduleModelHandler.doSchedule(reqDTO.getScheduleCode(), reqDTO.getScheduleTime());
            resp.setResult(scheduleResult.getResult());
            stScheduleRecordService.create(scheduleResult);
            stScheduleSchemeService.updateTime(scheduleResult.getSchemeId(), scheduleResult.getScheduleTime());
            log.info("预测计算结束: " + System.currentTimeMillis());
        } catch (Exception ex) {
            log.info("调度计算异常: " + System.currentTimeMillis());
//            ex.printStackTrace();
            ex.printStackTrace();
            return resp;
        }
        return resp;