iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/PredictModuleHandler.java

@@ -1,5 +1,6 @@
package com.iailab.module.model.mdk.predict;

import com.iailab.module.model.common.exception.ModelResultErrorException;
import com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity;
import com.iailab.module.model.mcs.pre.enums.ItemRunStatusEnum;
import com.iailab.module.model.mcs.pre.enums.ItemStatus;
@@ -49,7 +50,6 @@
     * @return
     */
    public void predict(List<ItemVO> predictItemList, Date predictTime, int intervalTime,Map<String, PredictResultVO> predictResultMap) {
        PredictResultVO predictResult;
        Map<String, double[]> predictValueMap = null;
        if (!CollectionUtils.isEmpty(predictResultMap)) {
            // 将predictResultMap处理成Map<outPutId, double[]>
@@ -61,6 +61,7 @@
            }
        }
        for (ItemVO predictItem : predictItemList) {
            PredictResultVO predictResult;
            if (!predictItem.getStatus().equals(ItemStatus.STATUS1.getCode())) {
                continue;
            }
@@ -72,33 +73,41 @@
                long start = System.currentTimeMillis();
                try {
                    // 预测项开始预测
                    predictResult = predictItemHandler.predict(predictTime, predictItem, predictValueMap,itemRunStatusEnum);
                    predictResult = predictItemHandler.predict(predictTime, predictItem, predictValueMap);
                } catch (ModelResultErrorException e) {
                    itemRunStatusEnum = ItemRunStatusEnum.MODELRESULTERROR;
                    continue;
                } catch (Exception e) {
                    itemRunStatusEnum = ItemRunStatusEnum.FAIL;
                    continue;
                }
                long end = System.currentTimeMillis();
                Long drtPre = end - start;
                log.info(MessageFormat.format("预测项：{0}，预测时间：{1}ms", predictItem.getItemName(), drtPre));
                totalDur = totalDur + drtPre;

                predictResult.setGranularity(predictItem.getGranularity());
                predictResult.setT(intervalTime);
                predictResult.setSaveIndex(predictItem.getSaveIndex());
                predictResult.setLt(1);
                predictResultMap.put(predictItem.getItemNo(), predictResult);

                // 保存预测结果
                predictResultHandler.savePredictResult(predictResult);
                long endSave = System.currentTimeMillis();
                Long drtSave = endSave - end;
                log.info(MessageFormat.format("预测项：{0}，保存时间：{1}ms", predictItem.getItemName(),
                        drtSave));
                totalDur = totalDur + drtSave;
                predictResultMap.put(predictItem.getItemNo(), predictResult);
                try {
                    predictResultHandler.savePredictResult(predictResult);
                } catch (Exception e) {
                    itemRunStatusEnum = ItemRunStatusEnum.MODELRESULTSAVEERROR;
                    throw new RuntimeException("模型结果保存异常，result：" + predictResult);
                }
                itemRunStatusEnum = ItemRunStatusEnum.SUCCESS;
//                long endSave = System.currentTimeMillis();
//                Long drtSave = endSave - end;
//                log.info(MessageFormat.format("预测项：{0}，保存时间：{1}ms", predictItem.getItemName(),
//                        drtSave));
//                totalDur = totalDur + drtSave;
            } catch (Exception e) {
                e.printStackTrace();
                log.error(MessageFormat.format("预测项编号：{0}，预测项名称：{1}，预测失败：{2} 预测时刻：{3}",
                        predictItem.getId(), predictItem.getItemName(), e.getMessage(), predictTime));
                itemRunStatusEnum = ItemRunStatusEnum.FAIL;
            } finally {
                mmItemStatusService.recordStatus(predictItem.getId(), itemRunStatusEnum, totalDur, predictTime);
            }