فهرست منبع

推荐模型自动化更新-check auc

Joe 9 ماه پیش
والد
کامیت
dd55f88a9e
1فایلهای تغییر یافته به همراه78 افزوده شده و 0 حذف شده
  1. 78 0
      qiaojialiang/check_auc.sh

+ 78 - 0
qiaojialiang/check_auc.sh

@@ -0,0 +1,78 @@
+#!/bin/sh
+set -ex
+
+source /root/anaconda3/bin/activate py37
+
+#  nohup sh handle_rov.sh > "$(date +%Y%m%d_%H%M%S)_handle_rov.log" 2>&1 &
+
+# 原始数据table name
+table='alg_recsys_sample_all'
+today="$(date +%Y%m%d)"
+today_early_3="$(date -d '3 days ago' +%Y%m%d)"
+#table='alg_recsys_sample_all_test'
+# 处理分区配置 推荐数据间隔一天生产,所以5日0点使用3日0-23点数据生产new模型数据
+begin_early_2_Str="$(date -d '2 days ago' +%Y%m%d)"
+end_early_2_Str="$(date -d '2 days ago' +%Y%m%d)"
+beginHhStr=00
+endHhStr=23
+max_hour=05
+max_minute=00
+# 各节点产出hdfs文件绝对路径
+# 源数据文件
+originDataPath=/dw/recommend/model/13_sample_data/
+# 特征值
+valueDataPath=/dw/recommend/model/14_feature_data/
+# 特征分桶
+bucketDataPath=/dw/recommend/model/16_train_data/
+# 模型数据路径
+MODEL_PATH=/root/joe/recommend-emr-dataprocess/model
+# 预测路径
+PREDICT_PATH=/root/joe/recommend-emr-dataprocess/predict
+# 历史线上正在使用的模型数据路径
+LAST_MODEL_HOME=/root/joe/model_online
+# 模型数据文件前缀
+model_name=akaqjl8
+# fm模型
+FM_HOME=/root/sunmingze/alphaFM/bin
+# hadoop
+HADOOP=/opt/apps/HADOOP-COMMON/hadoop-common-current/bin/hadoop
+
+
+
+ 0 对比AUC 前置对比2日模型数据 与 线上模型数据效果对比,如果2日模型优于线上,更新线上模型
+echo "$(date +%Y-%m-%d_%H-%M-%S)----------step0------------开始对比,新:${MODEL_PATH}/${model_name}_${today_early_3}.txt,与线上online模型数据auc效果"
+#$HADOOP fs -text ${bucketDataPath}/${begin_early_2_Str}/* | ${FM_HOME}/bin/fm_predict -m ${LAST_MODEL_HOME}/model_online.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_${today}_online.txt
+#$HADOOP fs -text ${bucketDataPath}/${begin_early_2_Str}/* | ${FM_HOME}/bin/fm_predict -m ${MODEL_PATH}/${model_name}_${today_early_3}.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_${today}_new.txt
+
+$HADOOP fs -text ${bucketDataPath}/20240703/* | ${FM_HOME}/bin/fm_predict -m ${LAST_MODEL_HOME}/model_online.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_${today}_online.txt
+$HADOOP fs -text ${bucketDataPath}/20240703/* | ${FM_HOME}/bin/fm_predict -m ${MODEL_PATH}/${model_name}_20240703.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_${today}_new.txt
+
+
+online_auc=`cat ${PREDICT_PATH}/${model_name}_${today}_online.txt | /root/sunmingze/AUC/AUC`
+if [ $? -ne 0 ]; then
+   echo "推荐线上模型AUC计算失败"
+#   /root/anaconda3/bin/python ad/ad_monitor_util.py "线上模型AUC计算失败"
+   exit 1
+fi
+
+new_auc=`${PREDICT_PATH}/${model_name}_${today}_new.txt | /root/sunmingze/AUC/AUC`
+if [ $? -ne 0 ]; then
+   echo "推荐新模型AUC计算失败"
+#   /root/anaconda3/bin/python ad/ad_monitor_util.py "新模型AUC计算失败"
+   exit 1
+fi
+
+
+# 1 对比auc数据判断是否更新线上模型
+if [ "$online_auc" \< "$new_auc" ]; then
+    echo "新模型优于线上模型: 线上模型AUC: ${online_auc}, 新模型AUC: ${new_auc}"
+    # todo 模型格式转换
+
+    # todo 模型文件上传OSS
+
+    # todo 本地保存最新的线上使用的模型,用于下一次的AUC验证
+#    /root/anaconda3/bin/python ad/ad_monitor_util.py "新模型优于线上模型: 线上模型AUC: ${online_auc}, 新模型AUC: ${new_auc}"
+else
+    echo "新模型不如线上模型: 线上模型AUC: ${online_auc}, 新模型AUC: ${new_auc}"
+#    /root/anaconda3/bin/python ad/ad_monitor_util.py "新模型不如线上模型: 线上模型AUC: ${online_auc}, 新模型AUC: ${new_auc}"
+fi