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FILA_sell_amt_model_daily_operator.py
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FILA_sell_amt_model_daily_operator.py
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from __future__ import print_function
from airflow.operators.python_operator import PythonOperator
from airflow.operators.dummy_operator import DummyOperator
from airflow.operators.email_operator import EmailOperator
from airflow.hooks.presto_hook import PrestoHook
from airflow.operators.bash_operator import BashOperator
from sqlalchemy.sql import text as sa_text
from collections import deque
from airflow.hooks.hive_hooks import HiveCliHook
from airflow.hooks.hive_hooks import HiveServer2Hook
from airflow.operators.hive_operator import HiveOperator
import os
import glob
from airflow.hooks.mysql_hook import MySqlHook
from airflow.models import DAG
import time
import pandas as pd
import pickle
from datetime import datetime, timedelta
import os
from src.sell_amt_utils import *
import logging
logger = logging.getLogger()
default_args = {
'owner': 'Daniel',
'depends_on_past': False,
'start_date': datetime(2018, 3, 11),
'email_on_failure': True,
'email_on_retry': True,
'retries': 5,
'retry_delay': timedelta(minutes=1),
}
def retrieve_dataset_from_presto(**param):
partition = param['item_part']
n_item_ids = len(param['item_ids'])
item_id = param['item_ids'][0]
item_ids = str(tuple(param['item_ids']))
if DEVELOPMENT:
if n_item_ids == 1:
hql = "SELECT ID, ITEM_ID, STOCK_ID, STOCK_AMOUNT, COLLECT_DAY, REG_ID, REG_DT FROM inventory_part WHERE item_part = {} AND item_id = {} LIMIT 500".format(partition, item_id)
else:
hql = "SELECT ID, ITEM_ID, STOCK_ID, STOCK_AMOUNT, COLLECT_DAY, REG_ID, REG_DT FROM inventory_part WHERE item_part = {} AND item_id IN {} LIMIT 500".format(partition, item_ids)
else:
if n_item_ids == 1:
hql = "SELECT ID, ITEM_ID, STOCK_ID, STOCK_AMOUNT, COLLECT_DAY, REG_ID, REG_DT FROM inventory_part WHERE item_part = {} AND item_id = {} ".format(partition, item_id)
else:
hql = "SELECT ID, ITEM_ID, STOCK_ID, STOCK_AMOUNT, COLLECT_DAY, REG_ID, REG_DT FROM inventory_part WHERE item_part = {} AND item_id IN {} ".format(partition, item_ids)
result = presto.get_pandas_df(hql=hql)
result.columns = ["ID", "ITEM_ID", "STOCK_ID", "STOCK_AMOUNT", "COLLECT_DAY", "REG_ID", "REG_DT"]
result.REG_DT = pd.to_datetime(result.REG_DT)
logger.info("time to retrieve partition %s from server...." % partition)
write_to_feather(partition, result, processed=False)
logger.info("retrieving partition %s done" % partition)
def retrieve_item_ids():
import datetime
today = datetime.date.today()
week_of_year = today.isocalendar()[1]
query_date = datetime.date.today() - timedelta(days=5)
hql = "SELECT ID FROM ITEM_PART WHERE WEEK_PART IN ({}, {}) AND UPT_DT >= '{}' AND SITE_NAME IN ('NIKE', 'DESCENTE', 'nbkorea', 'adidas')".format(
week_of_year - 1, week_of_year, query_date)
result = presto.get_pandas_df(hql=hql)
result.columns = ['ITEM_ID']
result = result.assign(ITEM_PART=(result.ITEM_ID // 10000) + 1)
# result_dict = result.groupby('ITEM_PART')['ITEM_ID'].apply(lambda group: group.values).to_dict()
write_to_feather(None, result, meta=True)
def truncate_sell_amt_table_op():
wspider_temp_engine.execute(
sa_text('''TRUNCATE TABLE wspider_temp.MWS_COLT_ITEM_SELL_AMT_DEV''').execution_options(autocommit=True))
def apply_model_op(**param):
partition = param['item_part']
dataset = read_feather(partition, processed=False)
apply_model(partition, dataset)
def transfer_to_mysql_op(**param):
partition = param['item_part']
engine = param['engine']
dataset = read_feather(partition, processed=True)
engine.dispose()
insert_sell_amt_old(dataset)
def remove_meta_file_op():
remove_meta_file()
presto = PrestoHook()
DEVELOPMENT = False
if DEVELOPMENT:
engine = wspider_engine
else:
engine = wspider_temp_engine
EMAIL_LIST = [
'daniel.kim@epopcon.com'
,'zururux@epopcon.com'
]
dag = DAG('FILA_sell_amt_daily_modeling_dag_production2',
default_args=default_args,
dagrun_timeout=timedelta(days=2),
description='Modeling the sell amount',
# schedule_interval='0 0 * * 0',
schedule_interval='0 3 * * *',
# schedule_interval="@once",
catchup=False)
begin_task = DummyOperator(task_id='begin_task', dag=dag)
success_email_task = EmailOperator(
task_id='success_email_task',
to=EMAIL_LIST,
subject='Success!!',
html_content='Success Email', dag=dag)
remove_meta_file_task = PythonOperator(task_id='remove_meta_file_task',
python_callable=remove_meta_file_op,
dag=dag)
success_email_task >> remove_meta_file_task
path = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
filename = "item_ids.feather"
complete_filename = os.path.join(path, "tmp_feathers/meta", filename)
if not os.path.exists(complete_filename):
retrieve_item_ids()
else:
result = read_feather(None, meta=True)
result_dict = result.groupby('ITEM_PART')['ITEM_ID'].apply(lambda group: group.values).to_dict()
# print(result_dict)
for key, value in result_dict.items():
retrieve_dataset_from_presto_task = PythonOperator(task_id='retrieve_dataset_from_presto_task_{}'.format(key),
op_kwargs={'item_part': key, 'item_ids': value},
python_callable=retrieve_dataset_from_presto,
# priority_weight=1,
dag=dag)
apply_model_task = PythonOperator(task_id='apply_model_task_{}'.format(key),
op_kwargs={'item_part': key},
python_callable=apply_model_op,
# priority_weight=2,
dag=dag)
transfer_to_mysql_temp_task = PythonOperator(task_id='transfer_to_mysql_temp_task_{}'.format(key),
op_kwargs={'item_part': key, 'engine': engine},
python_callable=transfer_to_mysql_op,
# priority_weight=5,
dag=dag)
begin_task >> retrieve_dataset_from_presto_task >> apply_model_task >> transfer_to_mysql_temp_task >> success_email_task
# retrieve_item_ids_task = PythonOperator(task_id='retrieve_item_ids_task',
# python_callable=retrieve_item_ids,
# dag=dag)
# truncate_sell_amt_table_task = PythonOperator(
# task_id='truncate_sell_amt_table_task',
# python_callable=truncate_sell_amt_table_op,
# dag=dag)
# retrieving_email_task = EmailOperator(
# task_id='retrieving_email_task',
# to=EMAIL_LIST,
# subject='Retrieving part is successfully done! [1/3]',
# html_content='Retrieving part => Modeling part', dag=dag)
# modeling_email_task = EmailOperator(
# task_id='modeling_email_task',
# to=EMAIL_LIST,
# subject='Modeling part is successfully done! [1/2]',
# html_content='Modeling part => Transfering part', dag=dag)
#
#
#
# modeling_email_task >> truncate_sell_amt_table_task
# for idx, item_part in enumerate(range(10)):
#
# retrieve_dataset_from_presto_task = PythonOperator(task_id='retrieve_dataset_from_presto_task_%s' % item_part,
# op_kwargs={'item_part': item_part},
# python_callable=retrieve_dataset_from_presto,
# priority_weight=1,
# dag=dag)
#
# apply_model_task = PythonOperator(task_id='apply_model_task_%s' % item_part,
# op_kwargs={'item_part': item_part},
# python_callable=apply_model_op,
# priority_weight=2,
# dag=dag)
#
# transfer_to_mysql_temp_task = PythonOperator(task_id='transfer_to_mysql_temp_task_%s' % item_part,
# op_kwargs={'item_part': item_part, 'engine': wspider_temp_engine},
# python_callable=transfer_to_mysql_op,
# dag=dag)
#
# begin_task >> retrieve_dataset_from_presto_task >> apply_model_task >> modeling_email_task
# truncate_sell_amt_table_task >> transfer_to_mysql_temp_task >> final_email_task
#
# start = 0
#
# genesis_task = DummyOperator(task_id='Genesis', dag=dag)
#
#
#
# TOTAL_PARTITION = 400
# N_CHUNCKS = 100
#
# for end in range(0, TOTAL_PARTITION+1, N_CHUNCKS)[1:]:
#
# begin_task = DummyOperator(task_id='begin_part_%s_task' % end, dag=dag)
# success_email_task = EmailOperator(
# task_id='success_email_part_%s_task' % end,
# to=EMAIL_LIST,
# subject='Part %s is successfully done!' % end,
# html_content='Part %s is successfully done!' % end,
# dag=dag)
#
#
#
#
# modeling_email_task = EmailOperator(
# task_id='modeling_email_part_%s_task' % end,
# to=EMAIL_LIST,
# subject='Modeling part %s is successfully done!' % end,
# html_content='Modeling part %s is successfully done!' % end, dag=dag)
#
# for idx, item_part in enumerate(range(start, end)):
#
#
# retrieve_dataset_from_presto_task = PythonOperator(task_id='retrieve_dataset_from_presto_part_%s_task_%s' % (end, item_part),
# op_kwargs={'item_part': item_part},
# python_callable=retrieve_dataset_from_presto,
# priority_weight=1,
# dag=dag)
#
# apply_model_task = PythonOperator(task_id='apply_model_part_%s_task_%s' % (end, item_part),
# op_kwargs={'item_part': item_part},
# python_callable=apply_model_op,
# priority_weight=2,
# dag=dag)
#
# transfer_to_mysql_temp_task = PythonOperator(task_id='transfer_to_mysql_temp_part_%s_task_%s' % (end, item_part),
# op_kwargs={'item_part': item_part, 'engine': wspider_temp_engine},
# python_callable=transfer_to_mysql_op,
# dag=dag)
#
# begin_task >> retrieve_dataset_from_presto_task >> apply_model_task >> modeling_email_task >> transfer_to_mysql_temp_task >> success_email_task
# truncate_sell_amt_table_task >> begin_task
#
# start = end