所以我有一个任务的测试 dag,这是一个简单的 ETL 尝试从 mssql 数据库中提取数据并将它们加载到 postgres 数据库。所以它的工作方式是按日期选择并插入过去 360 天的 postgres 数据库。但任务在 10 天左右后 select 语句超时。
def get_receiveCars(**kwargs):
#get current date
end_date = datetime.now()
#loop for 360 days
for x in range(360):
startDate = today - timedelta(days=x)
delete_dataPostgres(startDate.strftime('%Y-%m-%d'), "received sample")
select_dataMsql(startDate)
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选择语句是:
def select_dataMsql(startDate):
#insert data
endDate = str(startDate.strftime('%Y-%m-%d')) + " 23:59:59"
ms_hook = MsSqlHook(mssql_conn_id='mssql_db')
select_sql="""select carColor, carBrand, fuelType, COUNT(DISTINCT RequestID ) AS received
FROM Requests
where
ReceivedDateTime >= %s
AND ReceivedDateTime< %s
GROUP BY carColor, carBrand, fuelType"""
cond = (startDate, endDate)
results =ms_hook.get_records(select_sql, parameters=cond)
insert_data(results, startDate)
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这是我的爸爸
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from src.get_receiveCars import get_receiveCars
#from src.transform_data import transform_data
#from src.load_table import load_table
import requests
import json
import os
# Define the default dag arguments.
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'email': XXXXX,
'email_on_failure': True,
'email_on_retry': False,
'retries': 3,
'retry_delay': timedelta(minutes=1)
}
# Define the dag, the start date and how frequently it runs.
# I chose the dag to run everday by using 1440 minutes.
dag = DAG(
dag_id='reveive_sample',
default_args=default_args,
dagrun_timeout=timedelta(minutes=200),
schedule_interval= '@daily',
start_date=datetime(2020, 10, 30))
# First task is to query get the weather from openweathermap.org.
mid_task = PythonOperator(
task_id='get_receiveCars',
provide_context=True,
python_callable=get_receiveCars,
dag=dag)
# Set task1
mid_task
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日志
- Start syncing user roles.
[2020-10-30 18:29:40,238] {timeout.py:42} ERROR - Process timed out, PID: 84214
[2020-10-30 18:29:40,238] {dagbag.py:259} ERROR - Failed to import: /root/airflow/dags/receive_sample.py
Traceback (most recent call last):
File "/root/airflow/lib/python3.6/site-packages/airflow/models/dagbag.py", line 256, in process_file
m = imp.load_source(mod_name, filepath)
File "/usr/local/lib/python3.6/imp.py", line 172, in load_source
module = _load(spec)
File "<frozen importlib._bootstrap>", line 684, in _load
File "<frozen importlib._bootstrap>", line 665, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 678, in exec_module
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "/root/airflow/dags/receive_sample.py", line 5, in <module>
from src.get_receiveCars import get_receiveCars
File "/root/airflow/dags/src/get_receiveCars.py", line 56, in <module>
get_receiveCars()
File "/root/airflow/dags/src/get_receiveCars.py", line 17, in get_receiveCars
delete_data(startDate.strftime('%Y-%m-%d'), "received cars")
File "/root/airflow/dags/src/get_receiveCars.py", line 26, in delete_data
pg_hook.run(delete_sql, parameters=cond)
File "/root/airflow/lib/python3.6/site-packages/airflow/hooks/dbapi_hook.py", line 172, in run
cur.execute(s, parameters)
File "/usr/local/lib/python3.6/encodings/utf_8.py", line 15, in decode
def decode(input, errors='strict'):
File "/root/airflow/lib/python3.6/site-packages/airflow/utils/timeout.py", line 43, in handle_timeout
raise AirflowTaskTimeout(self.error_message)
airflow.exceptions.AirflowTaskTimeout: Timeout, PID: 84214
[2020-10-30 18:29:40,260] {security.py:477} INFO - Start syncing user roles.
[2020-10-30 18:29:40,350] {security.py:477} INFO - Start syncing user roles.
[2020-10-30 18:29:40,494] {security.py:387} INFO - Fetching a set of all permission, view_menu from FAB meta-table
[2020-10-30 18:29:40,550] {security.py:387} INFO - Fetching a set of all permission, view_menu from FAB meta-table
[2020-10-30 18:29:40,639] {security.py:387} INFO - Fetching a set of all per
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您尚未execution_timeout在default_args- 我会从以下内容开始:
\n\nexecution_timeout (datetime.timedelta) \xe2\x80\x93 允许执行此任务实例的最大时间,如果超过,则会引发并失败。
\n
dagrun_timeout有不同的含义:
\n\ndagrun_timeout (datetime.timedelta) \xe2\x80\x93 指定 DagRun 在超时/失败之前应运行多长时间,以便可以创建新的 DagRun。仅当活动 DagRuns == max_active_runs 时,才会对计划的 DagRun 强制执行超时。
\n
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