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- #!/bin/sh
- set -x
- source /root/anaconda3/bin/activate py37
- export SPARK_HOME=/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8
- export PATH=$SPARK_HOME/bin:$PATH
- export HADOOP_CONF_DIR=/etc/taihao-apps/hadoop-conf
- export JAVA_HOME=/usr/lib/jvm/java-1.8.0
- # 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/41_recsys_sample_data/
- # 特征值
- valueDataPath=/dw/recommend/model/14_feature_data/
- # 特征分桶
- bucketDataPath=/dw/recommend/model/43_recsys_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=model_nba8
- # fm模型
- FM_HOME=/root/sunmingze/alphaFM/bin
- # hadoop
- HADOOP=/opt/apps/HADOOP-COMMON/hadoop-common-current/bin/hadoop
- OSS_PATH=oss://art-recommend.oss-cn-hangzhou.aliyuncs.com/zhangbo/
- $HADOOP fs -text ${bucketDataPath}/20240713/* | ${FM_HOME}/fm_train -m ${MODEL_PATH}/${model_name}_0709_0713.txt -dim 1,1,8 -im /root/joe/recommend-emr-dataprocess/model/model_nba8_0709_0712.txt -core 8
- $HADOOP fs -text ${bucketDataPath}/20240714/* | ${FM_HOME}/fm_predict -m ${MODEL_PATH}/${model_name}_0709_0713.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_0709_0713_new.txt
- new_auc=`cat ${PREDICT_PATH}/${model_name}_0709_0713_new.txt | /root/sunmingze/AUC/AUC`
- echo "0709-0713 auc：${new_auc}"
|
