Traceback (most recent call last): File "/root/bin/job/gen_sqlserver_datax_config.py", line 148, in <module> main(sys.argv[1:]) File "/root/bin/job/gen_sqlserver_datax_config.py", line 144, in main generate_json(source_database, source_table) File "/root/bin/job/gen_sqlserver_datax_config.py", line 117, in generate_json "column": get_hive_columns(source_database, source_table), File "/root/bin/job/gen_sqlserver_datax_config.py", line 80, in get_hive_columns return list(map(lambda x: {"name": x[0], "type": type_mapping(x[1].lower())}, meta)) File "/root/bin/job/gen_sqlserver_datax_config.py", line 80, in <lambda> return list(map(lambda x: {"name": x[0], "type": type_mapping(x[1].lower())}, meta)) File "/root/bin/job/gen_sqlserver_datax_config.py", line 77, in type_mapping return mappings[sqlserver_type] KeyError: 'numeric'
时间: 2024-04-28 08:26:50 浏览: 12
这是一个 Python 的错误信息,它提示代码中出现了 KeyError,即访问了一个不存在的键。具体来说,代码中有一个 type_mapping 函数,它接受一个参数 sqlserver_type,根据这个参数返回一个类型映射。但是在这个函数中,访问了一个不存在的键 'numeric',导致出现了 KeyError。可能的原因是,代码中没有为 'numeric' 这种类型提供一个映射。需要检查代码中的 mappings 是否包含了所有可能的类型,并且检查输入的 sqlserver_type 是否正确。
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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.