# -*- 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 from elasticsearch import Elasticsearch exists_es_dic = {} es = Elasticsearch([ { 'host': '172.16.31.17', 'port': 9200, }, { 'host': '172.16.31.11', 'port': 9200, }]) 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'") # 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 query,search_pv,search_uv FROM ( SELECT query ,count(t1.cl_id) as search_pv ,count(distinct t1.cl_id) as search_uv FROM ( SELECT partition_date ,params['query'] as query ,cl_id FROM online.bl_hdfs_maidian_updates WHERE partition_date >= {start_date} AND partition_date < {end_date} AND ((action = 'do_search' AND params['input_type']<>'everyone_watch') or action='search_result_click_search') UNION ALL SELECT partition_date,params['query'] as query,cl_id FROM online.bl_hdfs_maidian_updates WHERE partition_date >= {start_date} AND partition_date < {end_date} AND action = 'do_search' and params['input_type']='everyone_watch' and params['tab']='精选' and page_name='home' AND params['query'] not in ('AI测颜值','AI测肤质') --这两个词不跳转搜索结果页 UNION ALL SELECT partition_date,params['query'] as query,cl_id 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']='search_home' UNION ALL SELECT partition_date ,params['card_name'] as query ,cl_id 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 params['card_name'] not in ('AI测颜值','AI测肤质') --这两个词不跳转搜索结果页 --AND page_name='home' android的page_name为空 UNION ALL SELECT partition_date ,params['card_name'] as query ,cl_id FROM online.bl_hdfs_maidian_updates WHERE partition_date >= {start_date} AND partition_date < {end_date} AND action = 'on_click_card' AND page_name='welfare_home' AND params['card_type'] ='search_word' AND params['in_page_pos']='大家都在搜' UNION ALL SELECT partition_date ,params['card_name'] as query ,cl_id FROM online.bl_hdfs_maidian_updates WHERE partition_date >= {start_date} AND partition_date < {end_date} AND int(split(app_version,'\\.')[1]) >= 27 AND action='on_click_card' AND params['card_type']='highlight_word' )t1 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>= {start_date} AND partition_day < {end_date}) tmp ON m.partition_date=tmp.partition_day AND first_channel_source_type=code WHERE partition_date >= {start_date} 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 )t2 on t1.cl_id=t2.device_id AND t1.partition_date = t2.partition_date GROUP BY query ) order by search_pv desc limit 200 """.format(start_date='20201018',end_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.query,res.search_pv) results = es.search( index='gm-dbmw-diary-read', doc_type='diary', timeout='10s', body=body )