Airflow记录BrokenPipeException

我正在使用集群Airflow环境，其中我有四个用于服务器的AWS ec2实例 .

ec2-instances

• 服务器1：Web服务器，调度程序，Redis队列，PostgreSQL数据库

• 服务器2：Web服务器

• 服务器3： Worker

• 服务器4： Worker

我的设置已经完美地工作了三个月了，但偶尔每周一次，当Airflow试图记录某些东西时，我得到了一个断管异常 .

*** Log file isn't local.
*** Fetching here: http://ip-1-2-3-4:8793/log/foobar/task_1/2018-07-13T00:00:00/1.log

[2018-07-16 00:00:15,521] {cli.py:374} INFO - Running on host ip-1-2-3-4
[2018-07-16 00:00:15,698] {models.py:1197} INFO - Dependencies all met for <TaskInstance: foobar.task_1 2018-07-13 00:00:00 [queued]>
[2018-07-16 00:00:15,710] {models.py:1197} INFO - Dependencies all met for <TaskInstance: foobar.task_1 2018-07-13 00:00:00 [queued]>
[2018-07-16 00:00:15,710] {models.py:1407} INFO - 
--------------------------------------------------------------------------------
Starting attempt 1 of 1
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[2018-07-16 00:00:15,719] {models.py:1428} INFO - Executing <Task(OmegaFileSensor): task_1> on 2018-07-13 00:00:00
[2018-07-16 00:00:15,720] {base_task_runner.py:115} INFO - Running: ['bash', '-c', 'airflow run foobar task_1 2018-07-13T00:00:00 --job_id 1320 --raw -sd DAGS_FOLDER/datalake_digitalplatform_arl_workflow_schedule_test_2.py']
[2018-07-16 00:00:16,532] {base_task_runner.py:98} INFO - Subtask: [2018-07-16 00:00:16,532] {configuration.py:206} WARNING - section/key [celery/celery_ssl_active] not found in config
[2018-07-16 00:00:16,532] {base_task_runner.py:98} INFO - Subtask: [2018-07-16 00:00:16,532] {default_celery.py:41} WARNING - Celery Executor will run without SSL
[2018-07-16 00:00:16,534] {base_task_runner.py:98} INFO - Subtask: [2018-07-16 00:00:16,533] {__init__.py:45} INFO - Using executor CeleryExecutor
[2018-07-16 00:00:16,597] {base_task_runner.py:98} INFO - Subtask: [2018-07-16 00:00:16,597] {models.py:189} INFO - Filling up the DagBag from /home/ec2-user/airflow/dags/datalake_digitalplatform_arl_workflow_schedule_test_2.py
[2018-07-16 00:00:16,768] {cli.py:374} INFO - Running on host ip-1-2-3-4
[2018-07-16 00:16:24,931] {logging_mixin.py:84} WARNING - --- Logging error ---

[2018-07-16 00:16:24,931] {logging_mixin.py:84} WARNING - Traceback (most recent call last):

[2018-07-16 00:16:24,931] {logging_mixin.py:84} WARNING -   File "/usr/lib64/python3.6/logging/__init__.py", line 996, in emit
    self.flush()

[2018-07-16 00:16:24,932] {logging_mixin.py:84} WARNING -   File "/usr/lib64/python3.6/logging/__init__.py", line 976, in flush
    self.stream.flush()

[2018-07-16 00:16:24,932] {logging_mixin.py:84} WARNING - BrokenPipeError: [Errno 32] Broken pipe

[2018-07-16 00:16:24,932] {logging_mixin.py:84} WARNING - Call stack:

[2018-07-16 00:16:24,933] {logging_mixin.py:84} WARNING -   File "/usr/bin/airflow", line 27, in <module>
    args.func(args)

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/usr/local/lib/python3.6/site-packages/airflow/bin/cli.py", line 392, in run
    pool=args.pool,

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/usr/local/lib/python3.6/site-packages/airflow/utils/db.py", line 50, in wrapper
    result = func(*args, **kwargs)

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/usr/local/lib/python3.6/site-packages/airflow/models.py", line 1488, in _run_raw_task
    result = task_copy.execute(context=context)

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/usr/local/lib/python3.6/site-packages/airflow/operators/sensors.py", line 78, in execute
    while not self.poke(context):

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/home/ec2-user/airflow/plugins/custom_plugins.py", line 35, in poke
    directory = os.listdir(full_path)

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING -   File "/usr/local/lib/python3.6/site-packages/airflow/utils/timeout.py", line 36, in handle_timeout
    self.log.error("Process timed out")

[2018-07-16 00:16:24,934] {logging_mixin.py:84} WARNING - Message: 'Process timed out'
Arguments: ()

[2018-07-16 00:16:24,942] {models.py:1595} ERROR - Timeout
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/site-packages/airflow/models.py", line 1488, in _run_raw_task
    result = task_copy.execute(context=context)
  File "/usr/local/lib/python3.6/site-packages/airflow/operators/sensors.py", line 78, in execute
    while not self.poke(context):
  File "/home/ec2-user/airflow/plugins/custom_plugins.py", line 35, in poke
    directory = os.listdir(full_path)
  File "/usr/local/lib/python3.6/site-packages/airflow/utils/timeout.py", line 37, in handle_timeout
    raise AirflowTaskTimeout(self.error_message)
airflow.exceptions.AirflowTaskTimeout: Timeout
[2018-07-16 00:16:24,942] {models.py:1624} INFO - Marking task as FAILED.
[2018-07-16 00:16:24,956] {models.py:1644} ERROR - Timeout

有时错误也会说

*** Log file isn't local.
*** Fetching here: http://ip-1-2-3-4:8793/log/foobar/task_1/2018-07-12T00:00:00/1.log
*** Failed to fetch log file from worker. 404 Client Error: NOT FOUND for url: http://ip-1-2-3-4:8793/log/foobar/task_1/2018-07-12T00:00:00/1.log

我不确定为什么日志工作〜95％的时间但在其他时间随机失败 . 以下是我的Airflow.cfg文件中的日志设置，

# The folder where airflow should store its log files
# This path must be absolute
base_log_folder = /home/ec2-user/airflow/logs

# Airflow can store logs remotely in AWS S3 or Google Cloud Storage. Users
# must supply an Airflow connection id that provides access to the storage
# location.
remote_log_conn_id =
encrypt_s3_logs = False

# Logging level
logging_level = INFO

# Logging class
# Specify the class that will specify the logging configuration
# This class has to be on the python classpath
# logging_config_class = my.path.default_local_settings.LOGGING_CONFIG
logging_config_class =

# Log format
log_format = [%%(asctime)s] {%%(filename)s:%%(lineno)d} %%(levelname)s - %%(message)s
simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s

# Name of handler to read task instance logs.
# Default to use file task handler.
task_log_reader = file.task

# Log files for the gunicorn webserver. '-' means log to stderr.
access_logfile = -
error_logfile = 

# The amount of time (in secs) webserver will wait for initial handshake
# while fetching logs from other worker machine
log_fetch_timeout_sec = 5

# When you start an airflow worker, airflow starts a tiny web server
# subprocess to serve the workers local log files to the airflow main
# web server, who then builds pages and sends them to users. This defines
# the port on which the logs are served. It needs to be unused, and open
# visible from the main web server to connect into the workers.
worker_log_server_port = 8793

# How often should stats be printed to the logs
print_stats_interval = 30

child_process_log_directory = /home/ec2-user/airflow/logs/scheduler

我想知道是否可能我应该尝试不同的技术来记录我的日志记录，例如写入S3 Bucket，或者我还能做些什么来解决这个问题 .

Update:

将日志写入S3无法解决此问题 . 此外，错误现在更加一致（仍然是零星的） . 现在发生的情况更像是50％ . 我注意到的一件事是它正在进行的任务是我的AWS EMR创建任务 . 启动AWS EMR集群大约需要20分钟，然后任务必须等待Spark命令在EMR集群上运行 . 所以单个任务运行大约30分钟 . 我想知道这对于一个Airflow任务是否运行太长，如果这就是为什么它开始写入日志失败的原因 . 如果是这种情况，那么我可以分解EMR任务，以便创建EMR有一个任务，然后是EMR集群上Spark命令的另一个任务 .

Note:

我've also created a new bug ticket on Airflow' s Jira这里https://issues.apache.org/jira/browse/AIRFLOW-2844