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@@ -1,5 +1,5 @@
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#!/bin/sh
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-set -ex
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+set -x
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# 0 全局变量/参数
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originDataSavePath=/dw/recommend/model/31_ad_sample_data_auto/
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@@ -35,7 +35,7 @@ while true; do
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if (( current_hour > max_hour || (current_hour == max_hour && current_minute >= max_minute) )); then
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echo "最长等待时间已到，失败:${current_hour}-${current_minute}"
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msg="广告特征数据校验失败，大数据分区没有数据: ${today_early_1}${endTime}"
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- /root/anaconda3/bin/python ad/utils_monitor.py ${msg}
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+ /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
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exit 1
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fi
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done
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@@ -53,7 +53,7 @@ table:alg_recsys_ad_sample_all_new
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if [ $? -ne 0 ]; then
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echo "Spark原始样本生产任务执行失败"
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msg="广告特征数据生成失败，Spark原始样本生产任务执行失败"
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- /root/anaconda3/bin/python ad/utils_monitor.py ${msg}
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+ /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
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exit 1
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else
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echo "spark原始样本生产执行成功"
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@@ -73,7 +73,7 @@ savePath:${bucketFeatureSavePath}
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if [ $? -ne 0 ]; then
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echo "Spark特征分桶处理任务执行失败"
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msg="广告特征分桶失败，Spark特征分桶处理任务执行失败"
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- /root/anaconda3/bin/python ad/utils_monitor.py ${msg}
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+ /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
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exit 1
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else
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echo "spark特征分桶处理执行成功"
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@@ -84,7 +84,7 @@ fi
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$HADOOP fs -text ${bucketFeatureSavePath}/${today_early_1}/* | /root/sunmingze/alphaFM/bin/fm_train -m model/${model_name}_${today_early_1}.txt -dim 1,1,0 -core 8
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if [ $? -ne 0 ]; then
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echo "模型训练失败"
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- /root/anaconda3/bin/python ad/utils_monitor.py "广告模型训练失败"
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+ /root/anaconda3/bin/python ad/ad_monitor_util.py "广告模型训练失败"
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exit 1
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fi
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@@ -126,7 +126,7 @@ if [ $? -eq 0 ]; then
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echo "推荐模型文件至OSS成功"
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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 ad/utils_monitor.py "推荐模型文件至OSS失败"
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+ /root/anaconda3/bin/python ad/ad_monitor_util.py "推荐模型文件至OSS失败"
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fi
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# 7.3 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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