我有一个Airflow docker容器和另外两个容器（dc1和dc2）。我正在尝试在task1的dc1中执行命令（通过DockerOperator），并将其输出用于task2的dc2命令中。
我有一个可行的解决方案，但不幸的是，它并不可靠：（
我正在读取dc1日志，并且在99％的日志中都能正常工作
command1.py
# a simple version of the real script
print({'date': '2020-05-03'})
airflow / dags / dag1.py
# a wrapper class
class DOperator(DockerOperator):
def __init__(self, task_id, command, dag, *args, **kwargs):
super().__init__(
image='docker_image:latest',
task_id=task_id,
command=command,
api_version='auto',
auto_remove=True,
docker_url='unix://var/run/docker.sock',
network_mode='bridge',
tty=True,
xcom_push=True,
dag=dag,
*args,
**kwargs
)
def execute(self, context):
# get the last log line from docker stdout
docker_log = super().execute(context)
# push XComs from the json
if docker_log:
try:
result = json.loads(docker_log)
for key in result.keys():
context['ti'].xcom_push(key=key, value=result[key])
except:
pass
return docker_log
# Dcocker container 1
task1 = DOperator(
dag=dag,
task_id='task1',
command='python comand1.py', # its output is '2020-05-03'
)
# Dcocker container 2
task2 = DOperator(
task_id='task2',
command='python comand2.py --date={}'.format(
"{{{{ task_instance.xcom_pull(dag_id='{}', task_ids='{}', key='{}') }}}}".format(
dag.dag_id,
task1.task_id,
'date'
)
)
task1 >> task2
dc1日志
[2020-08-31 06:50:38,868] {{docker_operator.py:242}} INFO - {"date": "2020-05-03"}
但没有时为1％
在那种情况下，dc1日志中包含一行多余的空行，我无法正确提取输出
dc1日志
[2020-08-31 06:50:38,868] {{docker_operator.py:242}} INFO - {"date": "2020-05-03"}
[2020-08-31 06:50:38,868] {{docker_operator.py:242}} INFO -
所以我的问题是：
答案 0 :(得分：0)
您可以在实例化Docker Operator时尝试添加xcom_all=True。来自airflow DockerOperator docs：
xcom_push（布尔）–是否使用XCom将stdout推送到下一步。默认值为False。
xcom_all（布尔）–推所有标准输出或仅推最后一行。默认值为False（最后一行）。
将xcom_all设置为True会将所有日志行推送到XCOM，然后您可以在下游任务中解析该日志以检索所需的信息。这样，您就不必依赖位于日志末尾的数据。
答案 1 :(得分：0)
以下内容适用于您的工作。我的解决方案使用XCOM流量在容器之间传递数据。它确实需要在dockerized任务之间执行任务，以便可以提取XCOM。以下是示例示例，我用它来演示其他人如何将XCOM通信传入和传出容器化的Airflow Task。我知道它适用于气流1.10.6。我刚刚升级到1.10.12，但由于XCOM_JSON没有传递到容器而遇到了一些问题。希望这会有所帮助..如果您有任何疑问，请提问，我会尽力阐述。
example_docker_dag.py
import time
import logging
import datetime
from airflow.hooks.base_hook import BaseHook
from airflow.models import DAG, Variable, XCom
from airflow.operators.python_operator import PythonOperator
from airflow.operators.bash_operator import BashOperator
from airflow.operators.docker_operator import DockerOperator
from airflow.utils.dates import days_ago
import ast
logger = logging.getLogger(__name__)
args = {
'start_date': days_ago(1),
'ownder': 'mjcamp'
}
dag = DAG(
dag_id ='example-docker-dag',
default_args=args,
max_active_runs=6,
schedule_interval='@daily'
)
def make_xcom_traffic(**context):
print("some task that does things..")
time.sleep(2)
data = dict(test="Pass some data to the next task or tasks.", number=545)
Variable.set("Example-XCom", data)
return data # conventional way of doing XCOM ... don't have to really return anything but for uniforimity sake
def read_xcom(**context):
print("Read XCOM from DockerOperator.. and maybe do things..")
time.sleep(1)
# Grab xcom from previous task(dockerized task)..
data = context['task_instance'].xcom_pull(task_ids=context['task'].upstream_task_ids, key='return_value')
# Airflow seems to be broken and will return all 'stdoout' as the XCOM traffic so we have to parse it or
# write our code to only `print` the serialized thing we want.. in this case we are just printing a directionary.
# if you do something like this and have string data in your return value.. either don't use
# new lines for your stirngs or choose a different way to break things..
xcom_data = data[0].split('\n')[-1]
print("THIS IS WHAT I WANT:", xcom_data)
xcom_data = ast.literal_eval(xcom_data)
# Showing we have a python dictionary now...
print("Int =>", xcom_data["Int"])
print("Str =>", xcom_data["Str"])
print("Float =>", xcom_data["Float"])
t1 = PythonOperator(
task_id='make-xcom-traffic',
provide_context=True,
python_callable=make_xcom_traffic,
dag=dag)
t2 = DockerOperator(
environment={
"Example-XCom" : Variable.get("Example-XCom"),
},
task_id="docker-text",
image="example-docker-task",
auto_remove=True,
xcom_push=True,
xcom_all=False, # <<<=== things are broken in Airflow and this doesn't do what you expect.. it does nothing
docker_url='unix:///var/run/docker.sock',
# docker_conn_id='containeryard',
api_version='auto',
dag=dag
)
t3 = PythonOperator(
task_id='var-test',
provide_context=True,
python_callable=read_xcom,
dag=dag
)
t1 >> t2 >> t3
Dockerfile
FROM python:3.6
ENV EXAMPLE_XCOM=not-set
COPY ./requirements.txt /tmp/requirements.txt
RUN pip install -r /tmp/requirements.txt
COPY ./code.py /tmp/code.py
CMD ["/usr/local/bin/python", "/tmp/code.py"]
requirments.txt
pandas==0.24.2
numpy==1.17.1
code.py
import ast
import pandas as pd
import numpy as np
import os
from datetime import datetime
import json
import glob
xcom_json = os.getenv('XCOM_JSON')
print('Hello, from Airflow-Worker!')
print('Time on deck is...', datetime.now())
# Jst to show what things get passed in as environment variables
print('My ENV is >>', os.environ.keys())
# Data being passed in as XCom like variable
print("Received EXAMPLE XCOM TRAFFIC >>", os.getenv("Example-XCom"))
xcom_data = ast.literal_eval(os.getenv("Example-XCom"))
print("The Number =>", xcom_data["number"])
intvar = np.random.randint(0,100)
strvar = "test_string ===>>" + xcom_data["test"]
floatvar = np.random.rand() * xcom_data["number"]
# make a dictionary / json like object to return in `stdout`
result = dict(Int=intvar, Str=strvar, Float=floatvar)
# return the results as stdout for airflow
print(result)
Key: Example-XCom
Value: {'test': 'Pass some data to the next task or tasks.', 'number': 545}