在气流上使用docker操作符安装目录不起作用
我正在尝试使用docker操作符使用airflow自动执行一些脚本 气流版本:在气流上使用docker操作符安装目录不起作用,docker,airflow,airflow-operator,Docker,Airflow,Airflow Operator,我正在尝试使用docker操作符使用airflow自动执行一些脚本 气流版本:apache气流==1.10.12 我要做的是使用此代码将我的项目的所有文件(包括文件夹和文件)“复制”到容器中 以下文件ml intermediate.py位于该目录下~/aiffort/dags/ml intermediate.py: """ Template to convert a Ploomber DAG to Airflow """ from ai
apache气流==1.10.12
我要做的是使用此代码将我的项目的所有文件(包括文件夹和文件)“复制”到容器中
以下文件ml intermediate.py
位于该目录下~/aiffort/dags/ml intermediate.py
:
"""
Template to convert a Ploomber DAG to Airflow
"""
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.utils.dates import days_ago
from ploomber.spec import DAGSpec
from soopervisor.script.ScriptConfig import ScriptConfig
script_cfg = ScriptConfig.from_path('/home/letyndr/airflow/dags/ml-intermediate')
# Replace the project root to reflect the new location - or maybe just
# write a soopervisor.yaml, then we can we rid of this line
script_cfg.paths.project = '/home/letyndr/airflow/dags/ml-intermediate'
# TODO: use lazy_import from script_cfg
dag_ploomber = DAGSpec('/home/letyndr/airflow/dags/ml-intermediate/pipeline.yaml',
lazy_import=True).to_dag()
dag_ploomber.name = "ML Intermediate"
default_args = {
'start_date': days_ago(0),
}
dag_airflow = DAG(
dag_ploomber.name.replace(' ', '-'),
default_args=default_args,
description='Ploomber dag',
schedule_interval=None,
)
script_cfg.save_script()
from airflow.operators.docker_operator import DockerOperator
for task_name in dag_ploomber:
DockerOperator(task_id=task_name,
image="continuumio/miniconda3",
api_version="auto",
auto_remove=True,
# command="sh /home/letyndr/airflow/dags/ml-intermediate/script.sh",
command="sleep 600",
docker_url="unix://var/run/docker.sock",
volumes=[
"/home/letyndr/airflow/dags/ml-intermediate:/home/letyndr/airflow/dags/ml-intermediate:rw",
"/home/letyndr/airflow-data/ml-intermediate:/home/letyndr/airflow-data/ml-intermediate:rw"
],
working_dir=script_cfg.paths.project,
dag=dag_airflow,
container_name=task_name,
)
for task_name in dag_ploomber:
task_ploomber = dag_ploomber[task_name]
task_airflow = dag_airflow.get_task(task_name)
for upstream in task_ploomber.upstream:
task_airflow.set_upstream(dag_airflow.get_task(upstream))
dag = dag_airflow
当我使用Airflow执行这个DAG时,我得到一个错误,docker没有找到/home/letyndr/Airflow/dags/ml intermediate/script.sh
脚本。我更改了docker操作符sleep 600的执行命令,以进入容器并使用正确的路径检查容器中的文件
例如,当我在容器中时,我可以转到这个路径/home/letyndr/aiffort/dags/ml intermediate/
,但我看不到应该在那里的文件
我尝试复制Airflow如何检查包的这一部分,特别是创建docker容器的这一部分:
这是docker实现的一个复制:
import docker
client = docker.APIClient()
# binds = {
# "/home/letyndr/airflow/dags": {
# "bind": "/home/letyndr/airflow/dags",
# "mode": "rw"
# },
# "/home/letyndr/airflow-data/ml-intermediate": {
# "bind": "/home/letyndr/airflow-data/ml-intermediate",
# "mode": "rw"
# }
# }
binds = ["/home/letyndr/airflow/dags:/home/letyndr/airflow/dags:rw",
"/home/letyndr/airflow-data/ml-intermediate:/home/letyndr/airflow-data/ml-intermediate:rw"]
container = client.create_container(
image="continuumio/miniconda3",
command="sleep 600",
volumes=["/home/letyndr/airflow/dags", "/home/letyndr/airflow-data/ml-intermediate"],
host_config=client.create_host_config(binds=binds),
working_dir="/home/letyndr/airflow/dags",
name="simple_example",
)
client.start(container=container.get("Id"))
我发现,只有在设置了host\u config
和volumes
的情况下,装载卷才能工作,问题是,在aiffaire上的实现只设置了host\u config
,而没有设置卷
。我在方法create\u container
上添加了参数,它成功了
你知道我是否正确使用了docker操作符,还是这是一个问题