feat:修改定时任务脚本

ad/01_ad_model_update_everyday.sh

@@ -23,64 +23,64 @@ 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
 
-# 1 判断依赖的数据表是否生产完成
-source /root/anaconda3/bin/activate py37
-while true; do
-  python_return_code=$(python ad/ad_utils.py --excute_program check_ad_origin_hive --partition ${today} --hh 10)
-  if [ $python_return_code -eq 0 ]; then
-    echo "Python程序返回0，退出循环。"
-    break
-  fi
-  echo "Python程序返回非0值，等待五分钟后再次调用。"
-  sleep 300
-  current_hour=$(date +%H)
-  current_minute=$(date +%M)
-  if (( current_hour > max_hour || (current_hour == max_hour && current_minute >= max_minute) )); then
-    echo "最长等待时间已到，失败:${current_hour}-${current_minute}"
-    msg="广告特征数据校验失败，大数据分区没有数据: ${today}10"
-    /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
-    exit 1
-  fi
-done
-
-
-# 2 原始特征生成
-/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8/bin/spark-class2 org.apache.spark.deploy.SparkSubmit \
---class com.aliyun.odps.spark.zhp.makedata_ad.makedata_ad_31_originData_20240620 \
---master yarn --driver-memory 1G --executor-memory 2G --executor-cores 1 --num-executors 16 \
-./target/spark-examples-1.0.0-SNAPSHOT-shaded.jar \
-tablePart:64 repartition:16 \
-beginStr:${today_early_1}00 endStr:${today}10 \
-savePath:${originDataSavePath} \
-table:alg_recsys_ad_sample_all filterHours:00,01,02,03,04,05,06,07 \
-idDefaultValue:0.01
-if [ $? -ne 0 ]; then
-   echo "Spark原始样本生产任务执行失败"
-   msg="广告特征数据生成失败，Spark原始样本生产任务执行失败"
-   /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
-   exit 1
-else
-    echo "spark原始样本生产执行成功"
-fi
-
-
-# 3 特征分桶
-/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8/bin/spark-class2 org.apache.spark.deploy.SparkSubmit \
---class com.aliyun.odps.spark.zhp.makedata_ad.makedata_ad_33_bucketData_20240622 \
---master yarn --driver-memory 2G --executor-memory 4G --executor-cores 1 --num-executors 16 \
-./target/spark-examples-1.0.0-SNAPSHOT-shaded.jar \
-beginStr:${today_early_1} endStr:${today} repartition:100 \
-filterNames:adid_,targeting_conversion_ \
-readPath:${originDataSavePath} \
-savePath:${bucketFeatureSavePath}
-if [ $? -ne 0 ]; then
-   echo "Spark特征分桶处理任务执行失败"
-   msg="广告特征分桶失败，Spark特征分桶处理任务执行失败"
-   /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
-   exit 1
-else
-   echo "spark特征分桶处理执行成功"
-fi
+## 1 判断依赖的数据表是否生产完成
+#source /root/anaconda3/bin/activate py37
+#while true; do
+#  python_return_code=$(python ad/ad_utils.py --excute_program check_ad_origin_hive --partition ${today} --hh 10)
+#  if [ $python_return_code -eq 0 ]; then
+#    echo "Python程序返回0，退出循环。"
+#    break
+#  fi
+#  echo "Python程序返回非0值，等待五分钟后再次调用。"
+#  sleep 300
+#  current_hour=$(date +%H)
+#  current_minute=$(date +%M)
+#  if (( current_hour > max_hour || (current_hour == max_hour && current_minute >= max_minute) )); then
+#    echo "最长等待时间已到，失败:${current_hour}-${current_minute}"
+#    msg="广告特征数据校验失败，大数据分区没有数据: ${today}10"
+#    /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
+#    exit 1
+#  fi
+#done
+#
+#
+## 2 原始特征生成
+#/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8/bin/spark-class2 org.apache.spark.deploy.SparkSubmit \
+#--class com.aliyun.odps.spark.zhp.makedata_ad.makedata_ad_31_originData_20240620 \
+#--master yarn --driver-memory 1G --executor-memory 2G --executor-cores 1 --num-executors 16 \
+#./target/spark-examples-1.0.0-SNAPSHOT-shaded.jar \
+#tablePart:64 repartition:16 \
+#beginStr:${today_early_1}00 endStr:${today}10 \
+#savePath:${originDataSavePath} \
+#table:alg_recsys_ad_sample_all filterHours:00,01,02,03,04,05,06,07 \
+#idDefaultValue:0.01
+#if [ $? -ne 0 ]; then
+#   echo "Spark原始样本生产任务执行失败"
+#   msg="广告特征数据生成失败，Spark原始样本生产任务执行失败"
+#   /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
+#   exit 1
+#else
+#    echo "spark原始样本生产执行成功"
+#fi
+#
+#
+## 3 特征分桶
+#/opt/apps/SPARK2/spark-2.4.8-hadoop3.2-1.0.8/bin/spark-class2 org.apache.spark.deploy.SparkSubmit \
+#--class com.aliyun.odps.spark.zhp.makedata_ad.makedata_ad_33_bucketData_20240622 \
+#--master yarn --driver-memory 2G --executor-memory 4G --executor-cores 1 --num-executors 16 \
+#./target/spark-examples-1.0.0-SNAPSHOT-shaded.jar \
+#beginStr:${today_early_1} endStr:${today} repartition:100 \
+#filterNames:adid_,targeting_conversion_ \
+#readPath:${originDataSavePath} \
+#savePath:${bucketFeatureSavePath}
+#if [ $? -ne 0 ]; then
+#   echo "Spark特征分桶处理任务执行失败"
+#   msg="广告特征分桶失败，Spark特征分桶处理任务执行失败"
+#   /root/anaconda3/bin/python ad/ad_monitor_util.py ${msg}
+#   exit 1
+#else
+#   echo "spark特征分桶处理执行成功"
+#fi
 
 
 # 4 模型训练