Traceback (most recent call last): File "/root/.cache/JetBrains/RemoteDev/dist/d3daa55389d56_pycharm-professional-231.9011.9/plugins/python/helpers/pydev/pydevd.py", line 1496, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "/root/.cache/JetBrains/RemoteDev/dist/d3daa55389d56_pycharm-professional-231.9011.9/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "/mnt/disk1/recommmend_sort/my_deepfm.py", line 481, in <module> mp.set_start_method('spawn') File "/usr/local/lib/python3.7/multiprocessing/context.py", line 242, in set_start_method raise RuntimeError('context has already been set') RuntimeError: context has already been set
时间: 2023-09-10 13:08:59 浏览: 63
这个错误提示是在设置进程启动方式时出现了问题。具体来说,这可能是由于在代码的其他部分已经设置了进程启动方式。要解决这个问题,你可以尝试在设置进程启动方式之前检查是否已经设置过。例如,可以使用以下代码:
```python
import multiprocessing as mp
if __name__ == '__main__':
if mp.get_start_method(allow_none=True) is None:
mp.set_start_method('spawn')
```
这里使用了`mp.get_start_method()`函数来检查当前是否已经设置了进程启动方式。如果返回`None`,则说明还没有设置,可以继续使用`mp.set_start_method()`函数来设置启动方式。注意,在使用`spawn`启动方式时,必须将代码放在`if __name__ == '__main__':`语句块中,以避免子进程无限递归创建。
相关问题
Traceback ( most recent call last ) :File " C:/python/kfc.py " , line 8
Traceback (most recent call last): File "C:/python/kfc.py", line 8
这是Python中的错误追踪信息,通常在程序出现错误时会显示。它告诉我们在哪个文件的哪一行出现了错误。
具体来说,"Traceback (most recent call last)" 表示错误追踪的开始,它告诉我们下面的信息是最近一次调用的错误。
"File "C:/python/kfc.py", line 8" 表示错误发生在文件 "C:/python/kfc.py" 的第8行。
如果你想解决这个错误,可以打开 "C:/python/kfc.py" 文件,并检查第8行的代码,看看是否有语法错误或逻辑错误。
Broken DAG: [/root/airflow/dags/sqoop_airflow.py] Traceback (most recent call last):
As an AI language model, I cannot see the full error trace, but the error seems to indicate that there is an issue with the DAG file located at "/root/airflow/dags/sqoop_airflow.py". It is likely that there is a syntax error or an import issue within the file that is preventing it from being properly parsed by Airflow.
To troubleshoot this issue, you can try the following steps:
1. Check the syntax of the DAG file and ensure that all required packages and modules are imported correctly.
2. Verify that the file is located in the correct directory and has the correct file permissions.
3. Restart the Airflow scheduler and webserver to see if the issue persists.
4. Check Airflow's log files for more detailed error messages that may provide additional insight into the issue.