推荐模型-change oss

qiaojialiang/change_oss.sh

@@ -0,0 +1,86 @@
+#!/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/
+
+
+cat /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new.txt |
+  awk -F " " '{
+      if (NR == 1) {
+          print $1"\t"$2
+      } else {
+          split($0, fields, " ");
+          OFS="\t";
+          line=""
+          for (i = 1; i <= 10 && i <= length(fields); i++) {
+              line = (line ? line "\t" : "") fields[i];
+          }
+              print line
+          }
+      }' > /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt
+if [ $? -ne 0 ]; then
+   echo "新模型文件格式转换失败"
+fi
+# 4.1.2 模型文件上传OSS
+online_model_path=${OSS_PATH}/${model_name}.txt
+$HADOOP fs -test -e ${online_model_path}
+if [ $? -eq 0 ]; then
+    echo "数据存在, 先删除。"
+    $HADOOP fs -rm -r -skipTrash ${online_model_path}
+else
+    echo "数据不存在"
+fi
+$HADOOP fs -put /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new_change.txt ${online_model_path}
+if [ $? -eq 0 ]; then
+    echo "推荐模型文件至OSS成功"
+    # 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
+    cp -f ${LAST_MODEL_HOME}/model_online.txt ${LAST_MODEL_HOME}/model_online_$(date +\%Y\%m\%d).txt
+    cp -f /root/joe/recommend-emr-dataprocess/predict/model_nba8_0709_0713_new.txt ${LAST_MODEL_HOME}/model_online.txt
+    if [ $? -ne 0 ]; then
+        echo "模型备份失败"
+    fi
+    /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}"
+else
+    echo "推荐模型文件至OSS失败"
+    /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}"
+fi