update

output/out_put_user_post_each_strategy.py

+# -*- coding:UTF-8 -*-
+# @Time  : 2020/9/25 16:30
+# @File  : out_put_user_post_each_strategy.py
+# @email : litao@igengmei.com
+# @author : litao
+
+
+import hashlib
+import json
+
+import pymysql
+import xlwt, datetime
+import redis
+from meta_base_code.utils.func_from_redis_get_portrait import user_portrait_scan_info,get_user_portrait_tag3_from_redis
+from meta_base_code.utils.func_from_es_get_article import get_es_article_num,get_user_post_from_mysql
+# from pyhive import hive
+from maintenance.func_send_email_with_file import send_file_email
+from typing import Dict, List
+from elasticsearch_7 import Elasticsearch
+from elasticsearch_7.helpers import scan
+import sys
+import time
+from pyspark import SparkConf
+from pyspark.sql import SparkSession, DataFrame
+
+"""
+限定尾号的7000篇内容 曝光了哪些
+用设备找到用户画像  二级诉求和项目分开做
+用画像的标签 在7000篇内容中相关 候选池阅读完
+标签在第一列
+设备数
+曝光数
+曝光数
+精准曝光占比
+内容池数量
+
+
+每个画像多少帖子
+一共曝光了多少个帖子
+"""
+import hashlib
+import json
+
+import pymysql
+import xlwt, datetime
+import redis
+# from pyhive import hive
+from maintenance.func_send_email_with_file import send_file_email
+from typing import Dict, List
+from elasticsearch_7 import Elasticsearch
+from elasticsearch_7.helpers import scan
+import sys
+import time
+from pyspark import SparkConf
+from pyspark.sql import SparkSession, DataFrame
+
+# from pyspark.sql.functions import lit
+# import pytispark.pytispark as pti
+from utils.func_from_es_get_article import get_user_post_from_mysql
+from meta_base_code.utils.func_from_redis_get_portrait import user_portrait_scan_info, get_user_portrait_tag3_from_redis
+from meta_base_code.utils.func_from_es_get_article import get_es_article_num, get_user_post_from_mysql
+
+
+def con_sql(sql):
+    # 从数据库的表里获取数据
+
+    db = pymysql.connect(host='172.16.40.158', port=4000, user='st_user', passwd='aqpuBLYzEV7tML5RPsN1pntUzFy',
+                         db='jerry_prod')
+    cursor = db.cursor()
+    cursor.execute(sql)
+    result = cursor.fetchall()
+    db.close()
+    return result
+
+
+startTime = time.time()
+sparkConf = SparkConf()
+sparkConf.set("spark.sql.crossJoin.enabled", True)
+sparkConf.set("spark.debug.maxToStringFields", "100")
+sparkConf.set("spark.tispark.plan.allow_index_double_read", False)
+sparkConf.set("spark.tispark.plan.allow_index_read", True)
+sparkConf.set("spark.hive.mapred.supports.subdirectories", True)
+sparkConf.set("spark.hadoop.mapreduce.input.fileinputformat.input.dir.recursive", True)
+sparkConf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
+sparkConf.set("mapreduce.output.fileoutputformat.compress", False)
+sparkConf.set("mapreduce.map.output.compress", False)
+sparkConf.set("prod.gold.jdbcuri",
+              "jdbc:mysql://172.16.30.136/doris_prod?user=doris&password=o5gbA27hXHHm&rewriteBatchedStatements=true")
+sparkConf.set("prod.mimas.jdbcuri",
+              "jdbc:mysql://172.16.30.138/mimas_prod?user=mimas&password=GJL3UJe1Ck9ggL6aKnZCq4cRvM&rewriteBatchedStatements=true")
+sparkConf.set("prod.gaia.jdbcuri",
+              "jdbc:mysql://172.16.30.143/zhengxing?user=work&password=BJQaT9VzDcuPBqkd&rewriteBatchedStatements=true")
+sparkConf.set("prod.tidb.jdbcuri",
+              "jdbc:mysql://172.16.40.158:4000/eagle?user=st_user&password=aqpuBLYzEV7tML5RPsN1pntUzFy&rewriteBatchedStatements=true")
+sparkConf.set("prod.jerry.jdbcuri",
+              "jdbc:mysql://172.16.40.158:4000/jerry_prod?user=st_user&password=aqpuBLYzEV7tML5RPsN1pntUzFy&rewriteBatchedStatements=true")
+sparkConf.set("prod.tispark.pd.addresses", "172.16.40.158:2379")
+sparkConf.set("prod.tispark.pd.addresses", "172.16.40.170:4000")
+sparkConf.set("prod.tidb.database", "jerry_prod")
+sparkConf.setAppName("test")
+
+spark = (SparkSession.builder.config(conf=sparkConf).config("spark.sql.extensions", "org.apache.spark.sql.TiExtensions")
+         .config("spark.tispark.pd.addresses", "172.16.40.170:2379").enableHiveSupport().getOrCreate())
+
+spark.sql("ADD JAR hdfs:///user/hive/share/lib/udf/brickhouse-0.7.1-SNAPSHOT.jar")
+spark.sql("ADD JAR hdfs:///user/hive/share/lib/udf/hive-udf-1.0-SNAPSHOT.jar")
+spark.sql("CREATE TEMPORARY FUNCTION json_map AS 'brickhouse.udf.json.JsonMapUDF'")
+spark.sql("CREATE TEMPORARY FUNCTION is_json AS 'com.gmei.hive.common.udf.UDFJsonFormatCheck'")
+spark.sql("CREATE TEMPORARY FUNCTION arrayMerge AS 'com.gmei.hive.common.udf.UDFArryMerge'")
+
+sql = """
+select card_id from strategy_content_exposure_index where card_content_type="user_post" and preciseexposure_num>=50 and ctr>=0.05 and avg_page_stay>=20 and create_day="2020-09-17"
+"""
+second_demands_count_dict, tags_v3_count_dict, second_demands_card_id_list, tags_v3_card_id_list, second_demands_tractate_dict, tags_v3_tractate_dict = get_user_post_from_mysql(
+    sql)
+print(second_demands_count_dict, tags_v3_count_dict, second_demands_card_id_list, tags_v3_card_id_list)
+
+time.sleep(20)
+t = 1
+day_num = 0 - t
+now = (datetime.datetime.now() + datetime.timedelta(days=day_num))
+last_30_day_str = (now + datetime.timedelta(days=-31)).strftime("%Y%m%d")
+today_str = now.strftime("%Y%m%d")
+today_str_format = now.strftime("%Y-%m-%d")
+yesterday_str = (now + datetime.timedelta(days=-1)).strftime("%Y%m%d")
+yesterday_str_format = (now + datetime.timedelta(days=-1)).strftime("%Y-%m-%d")
+one_week_age_str = (now + datetime.timedelta(days=-7)).strftime("%Y%m%d")
+device_id_dict = {}
+
+huidu_device_id_sql = r"""
+select t2.device_id from 
+(select distinct(first_device) as device_id from online.ml_user_history_detail where partition_date = {today_str} and  substr(md5(first_device),-1) in ('8', '9', 'a', 'b') and last_active_date >= {last_30_day_str}) t2
+ LEFT JOIN
+    (
+        select distinct device_id
+        from ml.ml_d_ct_dv_devicespam_d  --去除机构刷单设备，即作弊设备（浏览和曝光事件去除）
+        WHERE partition_day='{today_str}'
+
+        union all
+
+        select distinct device_id
+        from dim.dim_device_user_staff   --去除内网用户
+    )spam_pv
+    on spam_pv.device_id=t2.device_id
+        LEFT JOIN
+    (
+        SELECT partition_date,device_id
+        FROM
+            (--找出user_id当天活跃的第一个设备id
+          SELECT user_id,partition_date,
+                  if(size(device_list) > 0, device_list [ 0 ], '') AS device_id
+            FROM online.ml_user_updates
+            WHERE partition_date='{today_str}'
+        )t1
+                JOIN
+            (  --医生账号
+          SELECT distinct user_id
+          FROM online.tl_hdfs_doctor_view
+          WHERE partition_date = '{today_str}'
+
+          --马甲账号/模特用户
+          UNION ALL
+          SELECT user_id
+          FROM ml.ml_c_ct_ui_user_dimen_d
+          WHERE partition_day = '{today_str}'
+          AND (is_puppet = 'true' or is_classifyuser = 'true')
+
+          UNION ALL
+          --公司内网覆盖用户
+          select distinct user_id
+          from dim.dim_device_user_staff
+
+          UNION ALL
+          --登陆过医生设备
+          SELECT distinct t1.user_id
+            FROM
+            (
+                SELECT user_id, v.device_id as device_id
+                FROM online.ml_user_history_detail
+                    LATERAL VIEW EXPLODE(device_history_list) v AS device_id
+                WHERE partition_date = '{today_str}'
+            ) t1
+            JOIN
+            (
+                SELECT device_id
+                FROM online.ml_device_history_detail
+                WHERE partition_date = '{today_str}'
+                AND is_login_doctor = '1'
+            ) t2
+                ON t1.device_id = t2.device_id
+        )t2
+            on t1.user_id=t2.user_id
+        group by partition_date,device_id
+    )dev
+    on t2.device_id=dev.device_id
+WHERE spam_pv.device_id IS NULL
+  and dev.device_id is null
+
+""".format(today_str=today_str, last_30_day_str=last_30_day_str)
+
+print(huidu_device_id_sql)
+huidu_device_id_df = spark.sql(huidu_device_id_sql)
+huidu_device_id_df.createOrReplaceTempView("dev_view")
+huidu_device_id_df.show(1)
+sql_res = huidu_device_id_df.collect()
+# 设备id
+for device_id in sql_res:
+    device_id_dict[device_id.device_id] = 1
+
+# 设备对应画像数量
+second_demands_tag_count = {}
+projects_demands_tag_count = {}
+# 设备id对应的画像
+second_demands_tag_dict = {}
+projects_demands_tag_dict = {}
+total_tag_count = {}
+total_tag_count_pro = {}
+temp_null_count = 0
+
+for redis_count, device_id in enumerate(device_id_dict):
+
+    # if redis_count >= 50:break
+    second_demands = []
+    projects = []
+    total_answer_content_num = 0
+    total_tractate_content_num = 0
+    total_diary_content_num = 0
+    # print(sql_res)
+    try:
+        res = get_user_portrait_tag3_from_redis(device_id)
+    except:
+        continue
+    if res.get("second_demands"):
+        second_demands = res.get("second_demands")
+        # print(second_demands)
+        for tag in second_demands:
+            if tag in second_demands_tag_count:
+                second_demands_tag_count[tag] += 1
+            else:
+                second_demands_tag_count[tag] = 1
+            if tag in second_demands_count_dict:
+                total_tractate_content_num += second_demands_count_dict[tag]
+        second_demands_tag_dict[device_id] = second_demands
+    if res.get("projects"):
+        projects = res.get("projects")
+        # print(projects)
+        for tag in projects:
+            if tag in projects_demands_tag_count:
+                projects_demands_tag_count[tag] += 1
+            else:
+                projects_demands_tag_count[tag] = 1
+
+            if tag in tags_v3_count_dict:
+                total_tractate_content_num += tags_v3_count_dict[tag]
+        projects_demands_tag_dict[device_id] = projects
+    # print(total_answer_content_num, total_tractate_content_num, total_diary_content_num)
+    tmp_count_num = 0
+
+# 7000片内容的曝光
+
+exposure_sql = """
+   SELECT
+        cl_id,
+        card_id,
+        transaction_type,
+        count(distinct app_session_id) as session_pv
+        FROM
+        (
+           SELECT 
+                  cl_id,
+                  card_id,
+                  app_session_id,
+                  transaction_type
+           from online.ml_community_precise_exposure_detail
+           WHERE partition_date>= '${today_str}'
+           AND action in ('page_precise_exposure','home_choiceness_card_exposure') --7745版本action改为page_precise_exposure
+           AND is_exposure = '1'  ----精准曝光
+           AND page_name ='home'
+           AND tab_name = '精选'
+           AND (transaction_type in ('-1','smr','hotspot','pgc','newdata','hotspot_feed','aistragegy','excestragegy','FIXEDSTRATEGY','FIXEDSTRATEGY_VIDEO','high_quality_fmctr')
+                or transaction_type like '%ctr' or transaction_type like '%cvr' or transaction_type like 'deeplink%')
+           AND card_content_type in ('user_post')
+           AND transaction_type in ('high_quality_fmctr')
+           group by 
+                  cl_id,
+                  transaction_type,
+                  card_id,
+                  app_session_id
+        ) a  group by cl_id,card_id,transaction_type
+""".format(today_str="20200918")
+
+print(exposure_sql)
+exposure_df = spark.sql(exposure_sql)
+# exposure_df.createOrReplaceTempView("exposure_df")
+exposure_df.show(1)
+sql_res = exposure_df.collect()
+session_pv_all = 0
+card_id_set = set()
+
+second_demands_id_count = {}
+projects_demands_id_count = {}
+
+baoguang_dict = {}
+# 遍历card_id 找出对应的device_id是否在灰度里
+# 找出card_id 对应帖子的标签 并分类汇总 得到 标签-计数字段
+for res in sql_res:
+    # partition_date = res.partition_date
+    # print(res)
+    cl_id = res.cl_id
+    card_id = res.card_id
+
+    if cl_id in device_id_dict:
+        # print("has device")
+        # print(type(card_id),card_id)
+        # print("has card_id")
+        session_pv = res.session_pv
+        # card_id_set.update(card_id)
+        if cl_id in second_demands_tag_dict:
+            if int(card_id) in second_demands_tractate_dict:
+                # print(cl_id, second_demands_tag_dict[card_id])
+                for tag_id in second_demands_tractate_dict[int(card_id)]:
+
+                    if tag_id in second_demands_id_count:
+                        second_demands_id_count[tag_id][int(card_id)] = 1
+                    else:
+                        second_demands_id_count[tag_id] = {}
+                        second_demands_id_count[tag_id][int(card_id)] = 1
+
+                # if tag_id in baoguang_dict:
+                #     baoguang_dict[tag_id] += session_pv
+                # else:
+                #     baoguang_dict[tag_id] = session_pv
+
+        if cl_id in projects_demands_tag_dict:
+            if int(card_id) in tags_v3_tractate_dict:
+                # print(cl_id,projects_demands_tag_dict[cl_id])
+                for tag_id in tags_v3_tractate_dict[int(card_id)]:
+                    if tag_id in projects_demands_id_count:
+                        projects_demands_id_count[tag_id][int(card_id)] = 1
+                    else:
+                        projects_demands_id_count[tag_id] = {}
+                        projects_demands_id_count[tag_id][int(card_id)] = 1
+
+final_projects_list = []
+second_demands_list = []
+print(projects_demands_id_count)
+time.sleep(10)
+print(second_demands_id_count)
+time.sleep(10)
+
+for tag_id in second_demands_tag_count:
+    temp_dict = {
+        "tag_name": tag_id,
+        "device_count": second_demands_tag_count[tag_id],
+        "tractate_count": second_demands_count_dict.get(tag_id),
+        "exporsure_count": len(second_demands_id_count[tag_id]) if second_demands_id_count.get(tag_id) else 0,
+
+    }
+    print(temp_dict['tag_name'], temp_dict['device_count'], temp_dict['tractate_count'], temp_dict['exporsure_count'])
+    # print(temp_dict)
+    # if temp_dict['tractate_count'] <  temp_dict['exporsure_count']:
+    #     print("error" , second_demands_id_count[tag_id])
+# print(1)
+# for tag_id in second_demands_count_dict:
+#     if tag_id not in second_demands_tag_count:
+#         temp_dict = {
+#             "tag_name": tag_id,
+#             "device_count": second_demands_tag_count.get(tag_id),
+#             "tractate_count": second_demands_count_dict.get(tag_id),
+#             "exporsure_count": 0,
+#
+#         }
+#         print(temp_dict)
+
+print("----------------------------------------------")
+for tag_id in projects_demands_tag_count:
+    temp_dict = {
+        "tag_name": tag_id,
+        "device_count": projects_demands_tag_count[tag_id],
+        "tractate_count": tags_v3_count_dict.get(tag_id),
+        "exporsure_count": len(projects_demands_id_count[tag_id]) if projects_demands_id_count.get(tag_id) else 0,
+
+    }
+    # if temp_dict['tractate_count'] <  temp_dict['exporsure_count']:
+    #     print("error" , projects_demands_id_count[tag_id])
+
+    print(temp_dict['tag_name'], temp_dict['device_count'], temp_dict['tractate_count'], temp_dict['exporsure_count'])
+# print(2)
+# for tag_id in tags_v3_count_dict:
+#     if tag_id not in projects_demands_tag_count:
+#         temp_dict = {
+#             "tag_name": tag_id,
+#             "device_count": projects_demands_tag_count.get(tag_id),
+#             "tractate_count": tags_v3_count_dict.get(tag_id),
+#             "exporsure_count": 0,
+#
+#         }
+#         print(temp_dict['tag_name'],temp_dict['device_count'],temp_dict['tractate_count'],temp_dict['exporsure_count'])
\ No newline at end of file

task/spark_test.py

@@ -80,16 +80,20 @@ spark.sql("CREATE TEMPORARY FUNCTION arrayMerge AS 'com.gmei.hive.common.udf.UDF
 
 
 sql_search_ctr = r"""
-SELECT
-        count(1)
-        from
+  SELECT
+        cl_id,
+        card_id,
+        transaction_type,
+        count(distinct app_session_id) as session_pv
+        FROM
         (
            SELECT 
                   cl_id,
                   card_id,
-                  app_session_id
+                  app_session_id,
+                  transaction_type
            from online.ml_community_precise_exposure_detail
-           WHERE partition_date>='{today_str}'
+           WHERE partition_date>= '${today_str}'
            AND action in ('page_precise_exposure','home_choiceness_card_exposure') --7745版本action改为page_precise_exposure
            AND is_exposure = '1'  ----精准曝光
            AND page_name ='home'
@@ -103,7 +107,7 @@ SELECT
                   transaction_type,
                   card_id,
                   app_session_id
-        )
+        ) a  group by cl_id,card_id,transaction_type
 """.format(today_str='20200922')
 
 print(sql_search_ctr)