Commit c61d32b0 authored by 赵威's avatar 赵威

get answer click ids

parent 27e9e630
import multiprocessing
import os
import sys
import time
from collections import defaultdict
sys.path.append(os.path.realpath("."))
from gensim.models import Word2Vec, word2vec
from utils.date import get_ndays_before_no_minus, get_ndays_before_with_format
from utils.files import DATA_PATH, MODEL_PATH
from utils.spark import get_spark
answer_click_ids_model_path = os.path.join(MODEL_PATH, "answer_click_ids_item2vec_model")
def get_answer_click_data(spark, start, end):
reg = r"""^\\d+$"""
sql = """
SELECT DISTINCT t1.partition_date, t1.cl_id, cast(t1.business_id as int) card_id, t1.app_session_id
FROM
(select partition_date,cl_id,business_id,action,page_name,page_stay, app_session_id
from online.bl_hdfs_maidian_updates
where action = 'page_view'
AND partition_date BETWEEN '{}' AND '{}'
AND page_name='answer_detail'
AND page_stay>=1
AND cl_id is not null
AND cl_id != ''
AND business_id is not null
AND business_id != ''
AND business_id rlike '{}'
) AS t1
JOIN
(select partition_date,active_type,first_channel_source_type,device_id
from online.ml_device_day_active_status
where partition_date BETWEEN '{}' AND '{}'
AND active_type IN ('1', '2', '4')
AND first_channel_source_type not IN ('yqxiu1','yqxiu2','yqxiu3','yqxiu4','yqxiu5','mxyc1','mxyc2','mxyc3'
,'wanpu','jinshan','jx','maimai','zhuoyi','huatian','suopingjingling','mocha','mizhe','meika','lamabang'
,'js-az1','js-az2','js-az3','js-az4','js-az5','jfq-az1','jfq-az2','jfq-az3','jfq-az4','jfq-az5','toufang1'
,'toufang2','toufang3','toufang4','toufang5','toufang6','TF-toufang1','TF-toufang2','TF-toufang3','TF-toufang4'
,'TF-toufang5','tf-toufang1','tf-toufang2','tf-toufang3','tf-toufang4','tf-toufang5','benzhan','promotion_aso100'
,'promotion_qianka','promotion_xiaoyu','promotion_dianru','promotion_malioaso','promotion_malioaso-shequ'
,'promotion_shike','promotion_julang_jl03','promotion_zuimei')
AND first_channel_source_type not LIKE 'promotion\\_jf\\_%') as t2
ON t1.cl_id = t2.device_id
AND t1.partition_date = t2.partition_date
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='{}'
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=t1.cl_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>='{}' AND partition_date<'{}'
)t1
JOIN
( --医生账号
SELECT distinct user_id
FROM online.tl_hdfs_doctor_view
WHERE partition_date = '{}'
--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 = '{}'
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 = '{}'
)t1
JOIN
(
SELECT device_id
FROM online.ml_device_history_detail
WHERE partition_date = '{}'
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 t1.partition_date=dev.partition_date and t1.cl_id=dev.device_id
WHERE (spam_pv.device_id IS NULL or spam_pv.device_id ='')
and (dev.device_id is null or dev.device_id ='')
""".format(start, end, reg, start, end, end, start, end, end, end, end, end)
# print("sql", flush=True)
# print(sql, flush=True)
df = spark.sql(sql)
return df
if __name__ == "__main__":
begin_time = time.time()
spark = get_spark("answer_click_ids")
click_df = get_answer_click_data(spark, get_ndays_before_no_minus(180), get_ndays_before_no_minus(1))
click_df.show(5, False)
print(click_df.count())
# spark-submit --master yarn --deploy-mode client --queue root.strategy --driver-memory 16g --executor-memory 1g --executor-cores 1 --num-executors 70 --conf spark.default.parallelism=100 --conf spark.storage.memoryFraction=0.5 --conf spark.shuffle.memoryFraction=0.3 --conf spark.locality.wait=0 --jars /srv/apps/tispark-core-2.1-SNAPSHOT-jar-with-dependencies.jar,/srv/apps/spark-connector_2.11-1.9.0-rc2.jar,/srv/apps/mysql-connector-java-5.1.38.jar /srv/apps/strategy_embedding/word_vector/answer.py
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