我在aws中运行kubernetes中的气流1.9。我希望日志能够进入s3，因为气流容器本身并不长久。
我已经阅读了描述该过程的各种线程和文档，但我仍然无法使其正常工作。首先是一个测试，向我演示s3配置和权限是有效的。这是在我们的一个工作实例上运行的。
使用气流写入s3文件
airflow@airflow-worker-847c66d478-lbcn2:~$ id
uid=1000(airflow) gid=1000(airflow) groups=1000(airflow)
airflow@airflow-worker-847c66d478-lbcn2:~$ env |grep s3
AIRFLOW__CONN__S3_LOGS=s3://vevo-dev-us-east-1-services-airflow/logs/
AIRFLOW__CORE__REMOTE_LOG_CONN_ID=s3_logs
AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER=s3://vevo-dev-us-east-1-services-airflow/logs/
airflow@airflow-worker-847c66d478-lbcn2:~$ python
Python 3.6.4 (default, Dec 21 2017, 01:37:56)
[GCC 4.9.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import airflow
>>> s3 = airflow.hooks.S3Hook('s3_logs')
/usr/local/lib/python3.6/site-packages/airflow/utils/helpers.py:351: DeprecationWarning: Importing S3Hook directly from <module 'airflow.hooks' from '/usr/local/lib/python3.6/site-packages/airflow/hooks/__init__.py'> has been deprecated. Please import from '<module 'airflow.hooks' from '/usr/local/lib/python3.6/site-packages/airflow/hooks/__init__.py'>.[operator_module]' instead. Support for direct imports will be dropped entirely in Airflow 2.0.
DeprecationWarning)
>>> s3.load_string('put this in s3 file', airflow.conf.get('core', 'remote_base_log_folder') + "/airflow-test")
[2018-02-23 18:43:58,437] {{base_hook.py:80}} INFO - Using connection to: vevo-dev-us-east-1-services-airflow
现在让我们从s3中检索文件并查看内容。我们可以看到这里的一切看起来都不错。
root@4f8171d4fe47:/# aws s3 cp s3://vevo-dev-us-east-1-services-airflow/logs//airflow-test .
download: s3://vevo-dev-us-east-1-services-airflow/logs//airflow-test to ./airflow-test
root@4f8171d4fe47:/# cat airflow-test
put this in s3 fileroot@4f8171d4fe47:/stringer#
所以似乎气流s3连接是好的，除了气流作业不使用s3进行记录。以下是我所拥有的设置，我认为某些内容有问题或者我错过了什么。
运行worker / scheduler / master实例的Env vars是
airflow@airflow-worker-847c66d478-lbcn2:~$ env |grep -i s3
AIRFLOW__CONN__S3_LOGS=s3://vevo-dev-us-east-1-services-airflow/logs/
AIRFLOW__CORE__REMOTE_LOG_CONN_ID=s3_logs
AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER=s3://vevo-dev-us-east-1-services-airflow/logs/
S3_BUCKET=vevo-dev-us-east-1-services-airflow
这表明s3_logs连接存在于气流
中airflow@airflow-worker-847c66d478-lbcn2:~$ airflow connections -l|grep s3
│ 's3_logs' │ 's3' │ 'vevo-dev-
us-...vices-airflow' │ None │ False │ False │ None │
我将这个文件https://github.com/apache/incubator-airflow/blob/master/airflow/config_templates/airflow_local_settings.py放在我的泊坞窗图片中。你可以在我们的一个工人身上看到一个例子
airflow@airflow-worker-847c66d478-lbcn2:~$ ls -al /usr/local/airflow/config/
total 32
drwxr-xr-x. 2 root root 4096 Feb 23 00:39 .
drwxr-xr-x. 1 airflow airflow 4096 Feb 23 00:53 ..
-rw-r--r--. 1 root root 4471 Feb 23 00:25 airflow_local_settings.py
-rw-r--r--. 1 root root 0 Feb 16 21:35 __init__.py
我们编辑了该文件以定义REMOTE_BASE_LOG_FOLDER变量。这是我们的版本和上游版本之间的差异
index 899e815..897d2fd 100644
--- a/var/tmp/file
+++ b/config/airflow_local_settings.py
@@ -35,7 +35,8 @@ PROCESSOR_FILENAME_TEMPLATE = '{{ filename }}.log'
# Storage bucket url for remote logging
# s3 buckets should start with "s3://"
# gcs buckets should start with "gs://"
-REMOTE_BASE_LOG_FOLDER = ''
+REMOTE_BASE_LOG_FOLDER = conf.get('core', 'remote_base_log_folder')
+
DEFAULT_LOGGING_CONFIG = {
'version': 1,
在这里，您可以看到我们的某个工作人员的设置是正确的。
>>> import airflow
>>> airflow.conf.get('core', 'remote_base_log_folder')
's3://vevo-dev-us-east-1-services-airflow/logs/'
基于REMOTE_BASE_LOG_FOLDER以＆＃39; s3＆＃39;开头的事实为基础。和REMOTE_LOGGING是真的
>>> airflow.conf.get('core', 'remote_logging')
'True'
我希望此块https://github.com/apache/incubator-airflow/blob/master/airflow/config_templates/airflow_local_settings.py#L122-L123评估为true并使日志转到s3。
任何有s3登录工作1.9的人都可以指出我缺少的东西吗？我想向上游项目提交一份PR以更新文档，因为这似乎是一个非常常见的问题，并且我可以告诉上游文档无效或者不知何故经常被误解。
谢谢！ -G。
答案 0 :(得分：2)
是的，我也很难根据文档设置它。我不得不通过气流的代码来解决它。你可能还有很多事情没有做过。
要检查的一些事项：
1.确保您具有log_config.py文件，并且该文件位于正确的目录：./ config / log_config.py。还要确保你没有忘记该目录中的__init__.py文件
2.确保定义了s3.task处理程序并将其格式化程序设置为airflow.task
3.确保将airflow.task和airflow.task_runner处理程序设置为s3.task
这是一个适合我的log_config.py文件：
# -*- coding: utf-8 -*-
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from airflow import configuration as conf
# TO DO: Logging format and level should be configured
# in this file instead of from airflow.cfg. Currently
# there are other log format and level configurations in
# settings.py and cli.py. Please see AIRFLOW-1455.
LOG_LEVEL = conf.get('core', 'LOGGING_LEVEL').upper()
LOG_FORMAT = conf.get('core', 'log_format')
BASE_LOG_FOLDER = conf.get('core', 'BASE_LOG_FOLDER')
PROCESSOR_LOG_FOLDER = conf.get('scheduler', 'child_process_log_directory')
FILENAME_TEMPLATE = '{{ ti.dag_id }}/{{ ti.task_id }}/{{ ts }}/{{ try_number }}.log'
PROCESSOR_FILENAME_TEMPLATE = '{{ filename }}.log'
S3_LOG_FOLDER = 's3://your_path_to_airflow_logs'
LOGGING_CONFIG = {
'version': 1,
'disable_existing_loggers': False,
'formatters': {
'airflow.task': {
'format': LOG_FORMAT,
},
'airflow.processor': {
'format': LOG_FORMAT,
},
},
'handlers': {
'console': {
'class': 'logging.StreamHandler',
'formatter': 'airflow.task',
'stream': 'ext://sys.stdout'
},
'file.task': {
'class': 'airflow.utils.log.file_task_handler.FileTaskHandler',
'formatter': 'airflow.task',
'base_log_folder': os.path.expanduser(BASE_LOG_FOLDER),
'filename_template': FILENAME_TEMPLATE,
},
'file.processor': {
'class': 'airflow.utils.log.file_processor_handler.FileProcessorHandler',
'formatter': 'airflow.processor',
'base_log_folder': os.path.expanduser(PROCESSOR_LOG_FOLDER),
'filename_template': PROCESSOR_FILENAME_TEMPLATE,
},
# When using s3 or gcs, provide a customized LOGGING_CONFIG
# in airflow_local_settings within your PYTHONPATH, see UPDATING.md
# for details
's3.task': {
'class': 'airflow.utils.log.s3_task_handler.S3TaskHandler',
'formatter': 'airflow.task',
'base_log_folder': os.path.expanduser(BASE_LOG_FOLDER),
's3_log_folder': S3_LOG_FOLDER,
'filename_template': FILENAME_TEMPLATE,
},
# 'gcs.task': {
# 'class': 'airflow.utils.log.gcs_task_handler.GCSTaskHandler',
# 'formatter': 'airflow.task',
# 'base_log_folder': os.path.expanduser(BASE_LOG_FOLDER),
# 'gcs_log_folder': GCS_LOG_FOLDER,
# 'filename_template': FILENAME_TEMPLATE,
# },
},
'loggers': {
'': {
'handlers': ['console'],
'level': LOG_LEVEL
},
'airflow': {
'handlers': ['console'],
'level': LOG_LEVEL,
'propagate': False,
},
'airflow.processor': {
'handlers': ['file.processor'],
'level': LOG_LEVEL,
'propagate': True,
},
'airflow.task': {
'handlers': ['s3.task'],
'level': LOG_LEVEL,
'propagate': False,
},
'airflow.task_runner': {
'handlers': ['s3.task'],
'level': LOG_LEVEL,
'propagate': True,
},
}
}
答案 1 :(得分：0)
当使用official helm chart部署到k8时，我还必须将远程日志记录配置也添加到工作容器中。 因此，这还不够：
AIRFLOW__CORE__REMOTE_LOGGING: True
AIRFLOW__CORE__REMOTE_LOG_CONN_ID: s3_logs
AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER: 's3://my-log-bucket/logs'
我还必须将这些变量传递给工人
AIRFLOW__KUBERNETES_ENVIRONMENT_VARIABLES__AIRFLOW__CORE__REMOTE_LOGGING: True
AIRFLOW__KUBERNETES_ENVIRONMENT_VARIABLES__AIRFLOW__CORE__REMOTE_LOG_CONN_ID: s3_logs
AIRFLOW__KUBERNETES_ENVIRONMENT_VARIABLES__AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER: 's3://my-log-bucket/logs'