update feature

spark/featureEng.py

@@ -153,6 +153,7 @@ def arrayReverse(arr):
 
 def addUserFeatures(samples,dataVocab,multiVocab):
     dataVocab["userid"] = collectColumnToVocab(samples, "userid")
+    dataVocab["user_os"] = ["ios","android","-1"]
 
     extractTagsUdf = F.udf(extractTags, ArrayType(StringType()))
     arrayReverseUdf = F.udf(arrayReverse, ArrayType(StringType()))
@@ -381,7 +382,7 @@ def getClickSql(start, end):
     SELECT DISTINCT t1.partition_date, t1.cl_id device_id, t1.card_id,t1.time_stamp,t1.page_stay 
       FROM
         (
-            select partition_date,cl_id,business_id as card_id,time_stamp,page_stay
+            select partition_date,cl_id,business_id as card_id,time_stamp,page_stay,cl_type as os
             from online.bl_hdfs_maidian_updates
             where action = 'page_view'
             AND partition_date>='{startDay}' and partition_date<='{endDay}'
@@ -425,7 +426,7 @@ def getClickSql(start, end):
 
 def getExposureSql(start, end):
     sql = """
-    SELECT DISTINCT t1.partition_date,t1.cl_id device_id,t1.card_id,t1.time_stamp, 0 as page_stay 
+    SELECT DISTINCT t1.partition_date,t1.cl_id device_id,t1.card_id,t1.time_stamp, 0 as page_stay,cl_type as os 
     from
         (	--新首页卡片曝光
             SELECT partition_date,cl_id,card_id,time_stamp
@@ -756,7 +757,6 @@ if __name__ == '__main__':
     spark.sparkContext.setLogLevel("ERROR")
     # 行为数据
     clickSql = getClickSql(startDay,endDay)
-    print("--------")
     expSql = getExposureSql(startDay,endDay)
 
     clickDF = spark.sql(clickSql)
@@ -766,7 +766,8 @@ if __name__ == '__main__':
     ratingDF = ratingDF.withColumnRenamed("time_stamp", "timestamp")\
         .withColumnRenamed("device_id", "userid")\
         .withColumnRenamed("card_id", "itemid")\
-        .withColumnRenamed("page_stay", "rating")
+        .withColumnRenamed("page_stay", "rating")\
+        .withColumnRenamed("os", "user_os")
 
     print(ratingDF.columns)
     print(ratingDF.show(10, truncate=False))
@@ -846,12 +847,14 @@ if __name__ == '__main__':
     # timestmp8 = int(round(time.time()))
     # print("数据字典生成 耗时s:{}".format(timestmp8 - timestmp7))
     # 字典转为json 存入redis
-    print("数据字典存入redis...")
+    print("数据字典save...")
     print("dataVocab:")
     print(dataVocab.keys())
+    vocab_path = "../vocab/{}_vocab.json".format(VERSION)
 
     dataVocabStr = json.dumps(dataVocab, ensure_ascii=False)
-    dataVocabToRedis(dataVocabStr)
+    open(configUtils.VOCAB_PATH,mode='w',encoding='utf-8').write(dataVocabStr)
+    # dataVocabToRedis(dataVocabStr)
     timestmp9 = int(round(time.time()))
     print("总耗时m:{}".format((timestmp9 - start)/60))
 

train/train_service.py

@@ -183,7 +183,8 @@ if __name__ == '__main__':
 
     # redis中加载数据字典
     print("redis 中加载模型字典...")
-    data_vocab = getDataVocabFromRedis(VERSION)
+    data_vocab = json.load(open(configUtils.VOCAB_PATH,mode='r',encoding='utf-8'))
+    # data_vocab = getDataVocabFromRedis(VERSION)
     assert data_vocab
 
     timestmp1 = int(round(time.time()))

utils/configUtils.py

 SERVICE_VERSION="v1"
-SERVICE_MODEL_PATH = "/srv/apps/tensorServing_models/service"
+SERVICE_MODEL_PATH = "/srv/apps/tensorServing_models/service"
\ No newline at end of file
+VOCAB_PATH = "/srv/apps/serviceRec/vocab/{}_vocab.json".format(SERVICE_VERSION)
\ No newline at end of file