我正在尝试执行一个数据流python文件,该文件使用DataFlowPythonOperator通过气流DAG从GCS存储桶读取文本文件。我已经能够独立执行python文件,但是当我通过气流执行它时它失败了。我正在使用服务帐户来验证我的默认gcp连接。 我在执行作业时得到的错误是:
{gcp_dataflow_hook.py:108} INFO - Start waiting for DataFlow process to complete.
{models.py:1417} ERROR - DataFlow failed with return code 2
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/airflow/models.py", line 1374, in run
result = task_copy.execute(context=context)
File "/usr/local/lib/python2.7/dist-packages/airflow/contrib/operators/dataflow_operator.py", line 182, in execute
self.py_file, self.py_options)
File "/usr/local/lib/python2.7/dist-packages/airflow/contrib/hooks/gcp_dataflow_hook.py", line 152, in start_python_dataflow
task_id, variables, dataflow, name, ["python"] + py_options)
File "/usr/local/lib/python2.7/dist-packages/airflow/contrib/hooks/gcp_dataflow_hook.py", line 138, in _start_dataflow
_Dataflow(cmd).wait_for_done()
File "/usr/local/lib/python2.7/dist-packages/airflow/contrib/hooks/gcp_dataflow_hook.py", line 119, in wait_for_done
self._proc.returncode))
Exception: DataFlow failed with return code 2
我的气流脚本:
from airflow import DAG
from airflow.contrib.operators.dataflow_operator import DataFlowPythonOperator
from datetime import datetime, timedelta
# Default DAG parameters
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'email': <email>,
'email_on_failure': False,
'email_on_retry': False,
'start_date': datetime(2018, 4, 30),
'retries': 1,
'retry_delay': timedelta(minutes=1),
'dataflow_default_options': {
'project': '<Project ID>'
}
}
dag = DAG(
dag_id='df_dag_readfromgcs',
default_args=default_args,
schedule_interval=timedelta(minutes=60)
)
task1 = DataFlowPythonOperator(
task_id='task1',
py_file='~<path>/1readfromgcs.py',
gcp_conn_id='default_google_cloud_connection',
dag=dag
)
我的Dataflow python文件(1readfromgcs.py)包含以下代码:
from __future__ import absolute_import
import argparse
import logging
import apache_beam as beam
import apache_beam.pipeline as pipeline
import apache_beam.io as beamio
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.io import ReadFromText
def runCode(argv=None):
parser = argparse.ArgumentParser()
parser.add_argument('--input',
default='<Input file path>',
help='File name')
known_args, pipeline_args = parser.parse_known_args(argv)
pipeline_args.extend([
'--project=<project name>',
'--runner=DataflowRunner',
'--job_name=<job name>',
'--region=europe-west1',
'--staging_location=<GCS staging location>',
'--temp_location=<GCS temp location>'
])
pipeline_options = PipelineOptions(pipeline_args)
p = beam.pipeline.Pipeline(options=pipeline_options)
rows = p | 'read' >> beam.io.ReadFromText(known_args.input)
p.run().wait_until_finish()
if __name__ == '__main__':
logging.getLogger().setLevel(logging.INFO)
runCode()
我无法调试并找出此异常的原因,并且根据我在Airflow:https://github.com/apache/incubator-airflow/blob/master/airflow/contrib/hooks/gcp_dataflow_hook.py文件中的调查,错误来自以下几行:
def wait_for_done(self):
reads = [self._proc.stderr.fileno(), self._proc.stdout.fileno()]
self.log.info("Start waiting for DataFlow process to complete.")
while self._proc.poll() is None:
ret = select.select(reads, [], [], 5)
if ret is not None:
for fd in ret[0]:
line = self._line(fd)
self.log.debug(line[:-1])
else:
self.log.info("Waiting for DataFlow process to complete.")
if self._proc.returncode is not 0:
raise Exception("DataFlow failed with return code {}".format(
self._proc.returncode))
感谢您的想法并帮助解决我的问题。
答案 0 :(得分:0)
此例外源自_proc
subprocess
。它从shell返回退出代码。
我还没有使用过这个组件。根据正在执行的内容,此退出代码2将说明退出的原因。例如。 bash中的退出代码表示:
滥用shell builtins
可以连接到
缺少关键字或命令,或权限问题
因此它可能连接到基础DataFlow配置。尝试在模拟用户 airflow 时手动执行文件。