# -*- coding:UTF-8 -*-
# @Time  : 2020/9/8 13:39
# @File  : spark_test.py
# @email : litao@igengmei.com
# @author : litao

# -*- 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("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'")

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 last_active_date >= {last_30_day_str}) t2
(select device_id from online.ml_device_day_active_status where partition_date = '{today_str}' and active_type in (1,2)) 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='20200926', last_30_day_str='20200926')

print(huidu_device_id_sql)
huidu_device_id_df = spark.sql(huidu_device_id_sql)
huidu_device_id_df.createOrReplaceTempView("dev_view")
sql_search_ctr = r"""
   SELECT   card_name,count(card_name)
--             click.partition_date as partition_date
--             ,active_type
--             ,device_os_type
--             ,channel
--             ,count(click.cl_id) as all_search_click_pv_724
--             ,count(distinct click.cl_id) as all_search_click_uv_724
        FROM
        (
            SELECT cl_id,partition_date,action,params['page_name'] as page_name,'' as input_type,app_version,params['card_name'] as card_name
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date >= '{start_date}'  
              AND partition_date < '{end_date}'  
              AND action = 'on_click_navbar_search'
              AND (int(split(app_version,'\\.')[0]) = 7 AND int(split(app_version,'\\.')[1]) >= 24)

            UNION all
            SELECT cl_id,partition_date,action,params['page_name'] as page_name,params['input_type'] as input_type,app_version,params['card_name'] as card_name
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date >= '{start_date}'  
              AND partition_date < '{end_date}'  
              AND action = 'do_search'
              AND params['input_type'] = '详情页默认词'

            union all 
            SELECT cl_id,partition_date,action,'home' as page_name,'首页-猜你喜欢' as input_type,app_version,params['card_name'] as card_name
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date >= '{start_date}'  
              AND partition_date < '{end_date}'  
              AND action = 'on_click_card'
              AND params['in_page_pos']='猜你喜欢'
              AND params['tab_name']='精选'
              AND params['card_type']='search_word'
              --AND page_name='home' android的page_name为空

            union all 
            SELECT cl_id,partition_date,action,params['page_name'] as page_name,'美购首页-大家都在搜' as input_type,app_version,params['card_name'] as card_name
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date >= '{start_date}'  
              AND partition_date < '{end_date}'  
              AND action = 'on_click_card'
              AND params['page_name']='welfare_home'
              AND params['card_type'] ='search_word'
              AND params['in_page_pos']='大家都在搜'

            union all 
            SELECT cl_id,partition_date,action,params['page_name'] as page_name,'高亮词' as input_type,app_version,params['card_name'] as card_name
            FROM online.bl_hdfs_maidian_updates
            WHERE partition_date >= '{start_date}'  
              AND partition_date < '{end_date}'  
              AND action = 'on_click_card'
              AND params['card_type'] ='highlight_word'
        ) group by card_name
""".format(start_date='20201024',partition_date='20201025')

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)

