推荐模型-并行

qiaojialiang/xunlian.sh

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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}/20240711/* | ${FM_HOME}/fm_train -m ${MODEL_PATH}/${model_name}_0709_0711.txt -dim 1,1,8 -im /root/joe/recommend-emr-dataprocess/model/model_nba8_20240711.txt -core 8
+
+
+$HADOOP fs -text ${bucketDataPath}/20240712/* | ${FM_HOME}/fm_predict -m ${LAST_MODEL_HOME}/model_online.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_0709_0711_online.txt
+$HADOOP fs -text ${bucketDataPath}/20240712/* | ${FM_HOME}/fm_predict -m ${MODEL_PATH}/${model_name}_0709_0711.txt -dim 8 -core 8 -out ${PREDICT_PATH}/${model_name}_0709_0711_new.txt