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+#!/bin/sh
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+set -x
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+
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+source /root/anaconda3/bin/activate py37
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+
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+export SPARK_HOME=/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8
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+export PATH=$SPARK_HOME/bin:$PATH
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+export HADOOP_CONF_DIR=/etc/taihao-apps/hadoop-conf
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+export JAVA_HOME=/usr/lib/jvm/java-1.8.0
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+
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+# nohup sh handle_rov.sh > "$(date +%Y%m%d_%H%M%S)_handle_rov.log" 2>&1 &
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+
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+# 原始数据table name
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+table='alg_recsys_sample_all'
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+today="$(date +%Y%m%d)"
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+today_early_3="$(date -d '3 days ago' +%Y%m%d)"
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+#table='alg_recsys_sample_all_test'
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+# 处理分区配置 推荐数据间隔一天生产，所以5日0点使用3日0-23点数据生产new模型数据
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+begin_early_2_Str="$(date -d '2 days ago' +%Y%m%d)"
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+end_early_2_Str="$(date -d '2 days ago' +%Y%m%d)"
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+beginHhStr=00
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+endHhStr=23
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+max_hour=05
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+max_minute=00
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+# 各节点产出hdfs文件绝对路径
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+# 源数据文件
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+originDataPath=/dw/recommend/model/41_recsys_sample_data/
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+# 特征值
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+valueDataPath=/dw/recommend/model/14_feature_data/
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+# 特征分桶
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+bucketDataPath=/dw/recommend/model/43_recsys_train_data/
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+# 模型数据路径
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+MODEL_PATH=/root/joe/recommend-emr-dataprocess/model
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+# 预测路径
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+PREDICT_PATH=/root/joe/recommend-emr-dataprocess/predict
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+# 历史线上正在使用的模型数据路径
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+LAST_MODEL_HOME=/root/joe/model_online
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+# 模型数据文件前缀
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+model_name=model_nba8
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+# fm模型
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+FM_HOME=/root/sunmingze/alphaFM/bin
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+# hadoop
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+HADOOP=/opt/apps/HADOOP-COMMON/hadoop-common-current/bin/hadoop
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+OSS_PATH=oss://art-recommend.oss-cn-hangzhou.aliyuncs.com/zhangbo/
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+
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+
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+cat /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new.txt |
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+ awk -F " " '{
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+ if (NR == 1) {
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+ print $1"\t"$2
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+ } else {
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+ split($0, fields, " ");
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+ OFS="\t";
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+ line=""
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+ for (i = 1; i <= 10 && i <= length(fields); i++) {
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+ line = (line ? line "\t" : "") fields[i];
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+ }
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+ print line
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+ }
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+ }' > /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt
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+if [ $? -ne 0 ]; then
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+ echo "新模型文件格式转换失败"
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+fi
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+# 4.1.2 模型文件上传OSS
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+online_model_path=${OSS_PATH}/${model_name}.txt
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+$HADOOP fs -test -e ${online_model_path}
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+if [ $? -eq 0 ]; then
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+ echo "数据存在, 先删除。"
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+ $HADOOP fs -rm -r -skipTrash ${online_model_path}
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+else
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+ echo "数据不存在"
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+fi
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+$HADOOP fs -put /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt ${online_model_path}
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+if [ $? -eq 0 ]; then
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+ echo "推荐模型文件至OSS成功"
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+ # 4.1.3 本地保存最新的线上使用的模型，用于下一次的AUC验证
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+ cp -f ${LAST_MODEL_HOME}/model_online.txt ${LAST_MODEL_HOME}/model_online_$(date +\%Y\%m\%d).txt
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+ cp -f /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new.txt ${LAST_MODEL_HOME}/model_online.txt
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+ if [ $? -ne 0 ]; then
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+ echo "模型备份失败"
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+ fi
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+ /root/anaconda3/bin/python monitor_util.py --level info --msg "荐模型数据更新 \n【任务名称】:step模型更新\n【是否成功】:success\n【信息】:已更新/root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt模型}"
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+else
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+ echo "推荐模型文件至OSS失败"
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+ /root/anaconda3/bin/python monitor_util.py --level error --msg "荐模型数据更新 \n【任务名称】:step模型推送oss\n【是否成功】:error\n【信息】:推荐模型文件至OSS失败/root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt --- ${online_model_path}"
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+fi
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Joe