Question

我最近开始使用Airflow。我正在研究DAG：

查询MySQL数据库
提取查询并将其作为JSON文件存储在云存储桶中
将存储的JSON文件上传到BigQuery

Dag导入三个运营商：MySqlOperator，MySqlToGoogleCloudStorageOperator和GoogleCloudStorageToBigQueryOperator

我使用的是Airflow 1.8.0，Python 3和Pandas 0.19.0。

这是我的Dag代码：

sql2gcp_csv = MySqlToGoogleCloudStorageOperator(

    task_id='sql2gcp_csv',
    sql='airflow_gcp/aws_sql_extract_7days.sql',
    bucket='gs://{{var.value.gcs_bucket}}/{{ ds_nodash }}/',
    filename='{{ ds_nodash }}-account-*.json',
    schema_filename='support/file.json',
    approx_max_file_size_bytes=1900000000,
    mysql_conn_id='aws_mysql',
    google_cloud_storage_conn_id='airflow_gcp',

)

但是，当我运行它时，我收到以下错误：

[2017-07-20 22:38:07,478] {models.py:1441} INFO - Marking task as FAILED. 

[2017-07-20 22:38:07,490] {models.py:1462} ERROR - a bytes-like object is required, not 'str'

/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/models.py:1927: PendingDeprecationWarning: Invalid arguments were passed to MySqlOperator. Support for passing such arguments will be dropped in Airflow 2.0. Invalid arguments were:
*args: ()
**kwargs: {'database': 'test'}
category=PendingDeprecationWarning

/home/User/airflow/workspace/env/lib/python3.5/site-
packages/airflow/ti_deps/deps/base_ti_dep.py:94: PendingDeprecationWarning: generator '_get_dep_statuses' raised StopIteration

for dep_status in self._get_dep_statuses(ti, session, dep_context):
Traceback (most recent call last):

File "/home/User/airflow/workspace/env/bin/airflow", line 28, in <module> args.func(args)

File "/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/bin/cli.py", line 422, in run pool=args.pool,

File "/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/utils/db.py", line 53, in wrapper result = func(*args, **kwargs)

File "/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/models.py", line 1374, in run result = task_copy.execute(context=context)

File "/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/contrib/operators/mysql_to_gcs.py", line 91, in execute files_to_upload = self._write_local_data_files(cursor)

File "/home/User/airflow/workspace/env/lib/python3.5/site-packages/airflow/contrib/operators/mysql_to_gcs.py", line 136, in _write_local_data_files 
json.dump(row_dict, tmp_file_handle)

File "/usr/lib/python3.5/json/__init__.py", line 179, in dump 

TypeError: a bytes-like object is required, not 'str'

有谁知道为什么抛出这个异常？

Answer 1

根据您的追溯，您的代码在this point处突破。如您所见，它处理代码：

json.dump(row_dict, tmp_file_handle)

tmp_file_handle是带有默认输入参数的NamedTemporaryFile initialized，也就是说，它模拟以w+b模式打开的文件（因此只接受类似字节的数据，输入）。

问题是在Python 2中所有字符串都是字节，而在Python 3中，字符串是文本（默认编码为utf-8）。

如果您打开Python 2并运行此代码：

In [1]: from tempfile import NamedTemporaryFile
In [2]: tmp_f = NamedTemporaryFile(delete=True)
In [3]: import json
In [4]: json.dump({'1': 1}, tmp_f)

工作正常。

但是如果你打开Python 3并运行相同的代码：

In [54]: from tempfile import NamedTemporaryFile
In [55]: tmp_f = NamedTemporaryFile(delete=True)
In [56]: import json
In [57]: json.dump({'1': 1}, tmp_f)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-57-81743b9013c4> in <module>()
----> 1 json.dump({'1': 1}, tmp_f)

/usr/local/lib/python3.6/json/__init__.py in dump(obj, fp, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
    178     # a debuggability cost
    179     for chunk in iterable:
--> 180         fp.write(chunk)
    181 
    182 

/usr/local/lib/python3.6/tempfile.py in func_wrapper(*args, **kwargs)
    481             @_functools.wraps(func)
    482             def func_wrapper(*args, **kwargs):
--> 483                 return func(*args, **kwargs)
    484             # Avoid closing the file as long as the wrapper is alive,
    485             # see issue #18879.

TypeError: a bytes-like object is required, not 'str'

我们收到与您相同的错误。

这意味着Python 3仍然不完全支持Airflow（正如您在test coverage中看到的那样，模块airflow/contrib/operators/mysql_to_gcs.py尚未在python 2或3中进行过测试）。确认这一点的一种方法是使用python 2运行你的代码并查看它是否有效。

我建议在their JIRA上创建一个问题，请求两个版本的Python的可移植性。

气流mysql到gcp Dag错误

1 个答案: