一、如何製作AirFlow容器
1、安裝docker環境
基於centos環境下進行部署,建議在centos6或者centos7的環境下
1.1、下載docker安裝包
下載地址:https://download.docker.com/linux/static/stable/x86_64/
推薦使用的版本是18.09.6
1.2、下載到本地後解壓
tar -zxf docker-18.09.6.tgz
1.3、將解壓出來的docker文件內容移動到 /usr/bin/ 目錄下
cp docker/* /usr/bin/
1.4、將docker註冊爲service
新建文件
vim /etc/systemd/system/docker.service
並添加以下內容
[Unit]
Description=Docker Application Container Engine
Documentation=https://docs.docker.com
After=network-online.target firewalld.service
Wants=network-online.target
[Service]
Type=notify
# the default is not to use systemd for cgroups because the delegate issues still
# exists and systemd currently does not support the cgroup feature set required
# for containers run by docker
ExecStart=/usr/bin/dockerd
ExecReload=/bin/kill -s HUP $MAINPID
# Having non-zero Limit*s causes performance problems due to accounting overhead
# in the kernel. We recommend using cgroups to do container-local accounting.
LimitNOFILE=infinity
LimitNPROC=infinity
LimitCORE=infinity
# Uncomment TasksMax if your systemd version supports it.
# Only systemd 226 and above support this version.
#TasksMax=infinity
TimeoutStartSec=0
# set delegate yes so that systemd does not reset the cgroups of docker containers
Delegate=yes
# kill only the docker process, not all processes in the cgroup
KillMode=process
# restart the docker process if it exits prematurely
Restart=on-failure
StartLimitBurst=3
StartLimitInterval=60s
[Install]
WantedBy=multi-user.target
添加文件權限
chmod +x /etc/systemd/system/docker.service
systemctl daemon-reload
1.5、啓動docker
systemctl start docker
1.6、驗證
systemctl status docker #查看Docker狀態
docker -v #查看Docker版本
2. 在Docker環境安裝AirFlow
2.1、下載源碼到/root/airflow文件夾
git clone https://github.com/puckel/docker-airflow.git /root/airflow
2.2、運行容器
運行容器命令:
docker run --net=bridge --name AirFlow
-e MYSQL_IP_PORT="172.16.117.125:3306/airflow"
-e MYSQL_USERNAME="root"
-e MYSQL_PASSWORD="123456"
-v /usr/local/airflow/dags:/usr/local/airflow/dags
-v /usr/local/airflow/airflowSql:/usr/local/airflow/airflowSql
-v /usr/local/airflow/airflow.cfg:/usr/local/airflow/airflow.cfg -id -p 8081:8080
--privileged=true puckel/docker-airflow
解釋:
AirFlow:容器的名稱
MYSQL_IP_PORT:mysql數據庫的ip地址:端口號/數據庫名稱
MYSQL_USERNAME:登錄mysql數據庫的用戶名
MYSQL_PASSWORD:登錄mysql的密碼
-v /usr/local/airflow/dags:/usr/local/airflow/dags
宿主機的存放dag文件目錄:容器存放dag文件目錄
-v /usr/local/airflow/airflowSql:/usr/local/airflow/airflowSql
宿主機的存放執行腳本文件目錄:容器存放執行腳本文件目錄
-v /usr/local/airflow/airflow.cfg:/usr/local/airflow/airflow.cfg
將airflow的配置文件映射到宿主機
puckel/docker-airflow 鏡像名稱
2.3、進入容器
docker exec -it -u root AirFlow bash
/*
默認是進入到容器的/usr/local/airflow目錄下(airflow的默認安裝目錄)
*/
2.4、修改配置文件
vim airflow.cfg
dags_folder =$AIRFLOW_HOME/dags #DAG文件存放的目錄
base_log_folder = $AIRFLOW_HOME/logs #運行日誌存放目錄
executor = LocalExecutor
sql_alchemy_conn = mysql://$MYSQL_USERNAME:$MYSQL_PASSWORD@$MYSQL_IP_PORT
load_examples = False
dags_are_paused_at_creation = False
2.5、初始化數據庫
airflow initdb
如果初始化出現這樣的錯誤:
airflow.exceptions.AirflowException: Could not create Fernet object: Incorrect padding
解決辦法:
python -c "from cryptography.fernet import Fernet;
print(Fernet.generate_key().decode())"
export AIRFLOW__CORE__FERNET_KEY=oNu9XwewQNyx9mAJT2vZvtm3qzPRZIWRqwk9hSVch4A=
airflow initdb // 重新運行初始化數據庫
2.6、後臺運行
後臺運行服務webserver和scheduler
nohup airflow webserver>>$AIRFLOW_HOME/airflow-webserver.log 2>&1 &
後臺運行調度
nohup airflow scheduler>>$AIRFLOW_HOME/airflow-scheduler.log 2>&1 &
2.7、在瀏覽器打開地址: 172.16.117.125:8081
二、如何將部署好的AirFlow容器遷移到其他服務器
/*
在容器遷移之前,先給容器安裝幾個常用的命令,考慮到目標服務器可能不能聯網
*/
1、安裝 vim ping ifconfig 等常用命令
apt-get update
apt-get install vim //安裝vim
apt-get install net-tools //安裝ifconfig
apt-get install iputils-ping //安裝ping
2、將配置好的airflow容器製作成鏡像
docker commit 0e3d77afccc3 airflow
/*
docker commit 容器ID 鏡像名稱
*/
3、將鏡像保存爲一個文件包
docker save -o airflow.tar airflow
4、將該文件包拷貝到需要遷移的服務器上
5、在新的服務器上把文件包加載成鏡像
docker load -i airflow.tar
6、通過新導入的鏡像來啓動容器
docker run --net=bridge --name AirFlow --hostname airflow
-e MYSQL_IP_PORT="172.16.117.125:3306/airflow"
-e MYSQL_USERNAME="root" -e MYSQL_PASSWORD="123456"
-v /usr/local/airflow/dags:/usr/local/airflow/dags
-v /usr/local/airflow/airflowSql:/usr/local/airflow/airflowSql
-v /usr/local/airflow/airflow.cfg:/usr/local/airflow/airflow.cfg -id -p 8084:8080 --privileged=true airflow
解釋:
AirFlow:容器的名稱
MYSQL_IP_PORT:mysql數據庫的ip地址:端口號/數據庫名稱
MYSQL_USERNAME:登錄mysql數據庫的用戶名
MYSQL_PASSWORD:登錄mysql的密碼
-v /usr/local/airflow/dags:/usr/local/airflow/dags
宿主機的存放dag文件目錄:容器存放dag文件目錄
-v /usr/local/airflow/airflowSql:/usr/local/airflow/airflowSql
宿主機的存放執行腳本文件目錄:容器存放執行腳本文件目錄
-v /usr/local/airflow/airflow.cfg:/usr/local/airflow/airflow.cfg
將airflow的配置文件映射到宿主機
airflow 鏡像名稱
7、進入容器
docker exec -it -u root AirFlow bash
/*
默認是進入到容器的/usr/local/airflow目錄下(airflow的默認安裝目錄)
*/
8、修改配置文件
vim airflow.cfg
dags_folder =$AIRFLOW_HOME/dags #DAG文件存放的目錄
base_log_folder = $AIRFLOW_HOME/logs #運行日誌存放目錄
executor = LocalExecutor
sql_alchemy_conn = mysql://$MYSQL_USERNAME:$MYSQL_PASSWORD@$MYSQL_IP_PORT
load_examples = False
dags_are_paused_at_creation = False
9、初始化數據庫
airflow initdb
如果初始化出現這樣的錯誤:
airflow.exceptions.AirflowException: Could not create Fernet object: Incorrect padding
解決辦法:
python -c "from cryptography.fernet import Fernet;
print(Fernet.generate_key().decode())"
export AIRFLOW__CORE__FERNET_KEY=oNu9XwewQNyx9mAJT2vZvtm3qzPRZIWRqwk9hSVch4A=
airflow initdb // 重新運行初始化數據庫
10、後臺運行
後臺運行服務webserver和scheduler
nohup airflow webserver>>$AIRFLOW_HOME/airflow-webserver.log 2>&1 &
後臺運行調度
nohup airflow scheduler>>$AIRFLOW_HOME/airflow-scheduler.log 2>&1 &
11、在瀏覽器打開地址: 172.16.117.125:8084
/*
新的服務器ip地址:對應服務器的端口號(我這裏是8084)
*/
三、如何使用AirFlow容器
1、將dag任務文件放到/usr/local/airflow/dags目錄下(這個根據前面的配置來定)
2、調度任務在airflow所在服務器的模板
import airflow
import time
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.operators.python_operator import PythonOperator
from datetime import datetime,timedelta
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2019, 12, 17,17,12,1),
'retries': 5,
'retry_delay': timedelta(seconds=5),
}
dag = DAG(
'c_test',
default_args=default_args,
description='my second DAG',
schedule_interval=timedelta(minutes=1)
)
filename1='/usr/local/airflow/test/a1.txt'
filename2='/usr/local/airflow/test/a2.txt'
filename3='/usr/local/airflow/test/a3.txt'
def print_hello1():
print("Hello World!1111111")
current_time = time.asctime( time.localtime(time.time()) )
with open(filename1,'a') as f:
f.write(current_time)
def print_hello2():
print("Hello World!22222222")
current_time = time.asctime( time.localtime(time.time()) )
with open(filename2,'a') as f:
f.write(current_time)
def print_hello3():
print("Hello World!33333333")
current_time = time.asctime( time.localtime(time.time()) )
with open(filename3,'a') as f:
f.write(current_time)
task1 = PythonOperator(
task_id='task_1',
python_callable=print_hello1,
dag=dag)
task2 = PythonOperator(
task_id='task_2',
python_callable=print_hello2,
dag=dag)
task3 = PythonOperator(
task_id='task_3',
python_callable=print_hello3,
dag=dag)
task2.set_upstream(task1)
task3.set_upstream(task1)
3、調度任務在遠程服務器模板
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.operators import ExternalTaskSensor
from airflow.operators import EmailOperator
from datetime import datetime, timedelta
from airflow.contrib.hooks.ssh_hook import SSHHook
from airflow.contrib.operators.ssh_operator import SSHOperator
sshHook = SSHHook(remote_host='172.16.117.126',username='root',password='GXcxkfbrgx@26',timeout=30)
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': datetime(2019, 12, 27,10,22,0),
'retries': 3,
'retryDelay': timedelta(seconds=5),
'end_date': datetime(9999, 12, 31)
}
dag = DAG('hello',
default_args=default_args,
schedule_interval='0 * * * *')
hello = SSHOperator(
ssh_hook=sshHook,
task_id='hello',
dag=dag,
command='/opt/sh/hello.sh '
)
hello
/*
sshHook = SSHHook(remote_host='172.16.117.126',username='root',password='GXcxkfbrgx@26',timeout=30)
sshHook = SSHHook(remote_host='遠程服務器ip地址',username='用戶名',password='密碼',timeout=30)
*/