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# -*- coding:UTF-8 -*-
# @Time : 2020/9/4 17:07
# @File : search_meigou_ctr.py
# @email : litao@igengmei.com
# @author : litao
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
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("search_answer_ctr")
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'")
task_list = []
task_days = 3
for t in range(0, task_days):
day_num = 0 - t
now = (datetime.datetime.now() + datetime.timedelta(days=day_num))
last_30_day_str = (now + datetime.timedelta(days=-30)).strftime("%Y%m%d")
today_str = now.strftime("%Y%m%d")
yesterday_str = (now + datetime.timedelta(days=-1)).strftime("%Y%m%d")
one_week_age_str = (now + datetime.timedelta(days=-7)).strftime("%Y%m%d")
sql_search_ctr = r"""
SELECT
exp.partition_date as partition_date
,active_type
,device_os_type
,sum(service_exp_pv) as service_exp_pv
,sum(neirong_exp_pv) as neirong_exp_pv
,sum(service_click_pv) as service_click_pv
,sum(neirong_click_pv) as neirong_click_pv
FROM
(
SELECT t1.partition_day as partition_date,device_id
,service_exp_pv,neirong_exp_pv,service_click_pv,neirong_click_pv
FROM
(--搜索结果页卡片精准曝光
SELECT partition_day,
device_id,
count(CASE WHEN card_content_type='service' THEN 1 END) as service_exp_pv,
count(CASE WHEN card_content_type<>'service' THEN 1 END) as neirong_exp_pv
FROM
(
SELECT device_id,partition_day,card_content_type
FROM ml.mid_ml_c_et_pe_preciseexposure_dimen_d
WHERE partition_day >= '{partition_day}'
and partition_day < '{end_date}'
and action in ('page_precise_exposure','home_choiceness_card_exposure')
and is_exposure = '1'
and page_code in ('search_result_diary','search_result_doctor','search_result_hospital','search_result_more'
,'search_result_more_infomation','search_result_more_user','search_result_post','search_result_welfare'
,'search_result_wiki','search_result_question_answer')
AND (card_content_type IN ('answer','qa','question') or card_type in ('answer','qa','question'))
)a
group by partition_day,card_content_type,device_id
)t1
LEFT JOIN
(--搜索结果页卡片点击
SELECT cl_id,partition_date
,sum(CASE WHEN card_content_type='service' THEN click_pv END) as service_click_pv
,sum(CASE WHEN card_content_type='neirong' THEN click_pv END) as neirong_click_pv
FROM
(
SELECT partition_date,cl_id,'service' as card_content_type,count(1) as click_pv
FROM online.bl_hdfs_maidian_updates
WHERE partition_date >= '{partition_day}'
AND partition_date < '{end_date}'
AND ((action in ('search_result_click_recommend_item','search_result_welfare_click_item')
AND page_name in ('search_result_more','search_result_welfare'))
or (action = 'goto_welfare_detail' AND params ['from'] = 'search_result_welfare_recommend')
or (action = 'on_click_card' AND params['card_content_type'] in ('service') AND page_name in ('search_result_more','search_result_welfare')))
GROUP BY partition_date,cl_id,'service'
UNION ALL
SELECT partition_date,cl_id,'neirong' as card_content_type,count(1) as click_pv
FROM online.bl_hdfs_maidian_updates
WHERE partition_date >= '{partition_day}'
AND partition_date < '{end_date}'
AND ((action in ('on_click_topic_card','on_click_diary_card','search_result_click_infomation_item')
AND page_name in ('search_result_more','search_result_diary','search_result_post'))
or (action = 'on_click_card' AND params['card_content_type'] in ('answer','diary') AND page_name in ('search_result_more','search_result_diary','search_result_question_answer')))
GROUP BY partition_date,cl_id,'neirong'
)t2
GROUP BY cl_id,partition_date
)t2
ON t1.partition_day=t2.partition_date AND t1.device_id=t2.cl_id
)exp
JOIN
(
SELECT partition_date,device_id,t2.active_type,t2.channel,t2.device_os_type
FROM
(
SELECT
partition_date,m.device_id
,array(device_os_type ,'合计') as device_os_type
,array(case WHEN active_type = '4' THEN '老活'
WHEN active_type in ('1','2') then '新增' END ,'合计') as active_type
,array(CASE WHEN is_ai_channel = 'true' THEN 'AI' ELSE '其他' END , '合计') as channel
FROM online.ml_device_day_active_status m
LEFT JOIN
(SELECT code,is_ai_channel,partition_day
FROM DIM.DIM_AI_CHANNEL_ZP_NEW
WHERE partition_day>= '{partition_day}' AND partition_day < '{end_date}' ) tmp
ON m.partition_date=tmp.partition_day AND first_channel_source_type=code
where partition_date >= '{partition_day}'
AND partition_date < '{end_date}'
AND active_type in ('1','2','4')
) mas
LATERAL VIEW explode(mas.channel) t2 AS channel
LATERAL VIEW explode(mas.device_os_type) t2 AS device_os_type
LATERAL VIEW explode(mas.active_type) t2 AS active_type
)dev_channel
on dev_channel.device_id = exp.device_id
AND dev_channel.partition_date = exp.partition_date
GROUP BY exp.partition_date,active_type,device_os_type
""".format(partition_day=yesterday_str, end_date=today_str)
print(sql_search_ctr)
search_ctr_df = spark.sql(sql_search_ctr)
# spam_pv_df.createOrReplaceTempView("dev_view")
search_ctr_df.show(1)
sql_res = search_ctr_df.collect()
print("-------------------------------")
for res in sql_res:
print(res)
device_os_type = res.device_os_type
active_type = res.active_type
partition_date = yesterday_str
pid = hashlib.md5((partition_date + device_os_type + active_type).encode("utf8")).hexdigest()
click_num = res.neirong_click_pv
exposure = res.neirong_exp_pv
try:
search_ctr = round(click_num / exposure, 5)
except:
search_ctr = 0
instert_sql = """replace into search_answer_ctr(
partition_date,device_os_type,active_type,pid,click_num,exposure,search_ctr) VALUES('{partition_date}','{device_os_type}','{active_type}','{pid}',{click_num},{exposure},{search_ctr});""".format(
partition_date=partition_date, device_os_type=device_os_type, active_type=active_type, pid=pid,
click_num=click_num,
exposure=exposure, search_ctr=search_ctr
)
print(instert_sql)
# cursor.execute("set names 'UTF8'")
db = pymysql.connect(host='172.16.40.158', port=4000, user='st_user', passwd='aqpuBLYzEV7tML5RPsN1pntUzFy',
db='jerry_prod')
cursor = db.cursor()
res = cursor.execute(instert_sql)
db.commit()
print(res)