Apache DolphinScheduler 如何实现自动化打包+单机/集群部署？

Apache DolphinScheduler 是一款开源的分布式任务调度系统，旨在帮助用户实现复杂任务的自动化调度和管理。DolphinScheduler 支持多种任务类型，可以在单机或集群环境下运行。下面将介绍如何实现 DolphinScheduler 的自动化打包和单机/集群部署。

自动化打包

所需环境：maven、jdk

执行以下shell完成代码拉取及打包，打包路径：/opt/action/dolphinscheduler/dolphinscheduler-dist/target/apache-dolphinscheduler-dev-SNAPSHOT-bin.tar.gz

sudo su - root 

单机部署

1、DolphinScheduler运行所需环境

所需环境jdk、zookeeper、mysql

初始化zookeeper（高版本zookeeper推荐使用v3.8及以上版本）环境

安装包官网下载地址：https://zookeeper.apache.org/

sudo su - root 

jdk、mysql这里不做过多赘述。

2、初始化配置

2.1 配置文件初始化

初始化文件要放到指定目录（本文章以/opt/action/tool举例）

• 2.1.1新建文件夹

mkdir -p /opt/action/tool
mkdir -p /opt/Dsrelease

• 2.1.2新建初始化文件common.properties

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# user data local directory path, please make sure the directory exists and have read write permissions
data.basedir.path=/tmp/dolphinscheduler

# resource storage type: HDFS, S3, NONE
resource.storage.type=HDFS

# resource store on HDFS/S3 path, resource file will store to this hadoop hdfs path, self configuration, please make sure the directory exists on hdfs and have read write permissions. "/dolphinscheduler" is recommended
resource.upload.path=/dolphinscheduler

# whether to startup kerberos
hadoop.security.authentication.startup.state=false

# java.security.krb5.conf path
java.security.krb5.conf.path=/opt/krb5.conf

# login user from keytab username
login.user.keytab.username=hdfs-mycluster@ESZ.COM

# login user from keytab path
login.user.keytab.path=/opt/hdfs.headless.keytab

# kerberos expire time, the unit is hour
kerberos.expire.time=2
# resource view suffixs
#resource.view.suffixs=txt,log,sh,bat,conf,cfg,py,java,sql,xml,hql,properties,json,yml,yaml,ini,js
# if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
hdfs.root.user=root
# if resource.storage.type=S3, the value like: s3a://dolphinscheduler; if resource.storage.type=HDFS and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir
fs.defaultFS=file:///
aws.access.key.id=minioadmin
aws.secret.access.key=minioadmin
aws.region=us-east-1
aws.endpoint=http://localhost:9000
# resourcemanager port, the default value is 8088 if not specified
resource.manager.httpaddress.port=8088
# if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty
yarn.resourcemanager.ha.rm.ids=192.168.xx.xx,192.168.xx.xx
# if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace aws2 to actual resourcemanager hostname
yarn.application.status.address=http://aws2:%s/ws/v1/cluster/apps/%s
# job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)
yarn.job.history.status.address=http://aws2:19888/ws/v1/history/mapreduce/jobs/%s

# datasource encryption enable
datasource.encryption.enable=false

# datasource encryption salt
datasource.encryption.salt=!@#$%^&*

# data quality option
data-quality.jar.name=dolphinscheduler-data-quality-dev-SNAPSHOT.jar

#data-quality.error.output.path=/tmp/data-quality-error-data

# Network IP gets priority, default inner outer

# Whether hive SQL is executed in the same session
support.hive.oneSession=false

# use sudo or not, if set true, executing user is tenant user and deploy user needs sudo permissions; if set false, executing user is the deploy user and doesn't need sudo permissions
sudo.enable=true

# network interface preferred like eth0, default: empty
#dolphin.scheduler.network.interface.preferred=

# network IP gets priority, default: inner outer
#dolphin.scheduler.network.priority.strategy=default

# system env path
#dolphinscheduler.env.path=dolphinscheduler_env.sh

# development state
development.state=false

# rpc port
alert.rpc.port=50052

# Url endpoint for zeppelin RESTful API
zeppelin.rest.url=http://localhost:8080

• 2.1.3新建初始化文件core-site.xml

fs.defaultFS
hdfs://aws1


ha.zookeeper.quorum
aws1:2181


hadoop.proxyuser.root.hosts
*


hadoop.proxyuser.root.groups
*

• 2.1.4新建初始化文件hdfs-site.xml

dfs.replication
1


dfs.namenode.name.dir
/opt/bigdata/hadoop/ha/dfs/name


dfs.datanode.data.dir
/opt/bigdata/hadoop/ha/dfs/data


dfs.namenode.secondary.http-address
aws2:50090


dfs.namenode.checkpoint.dir
/opt/bigdata/hadoop/ha/dfs/secondary


dfs.nameservices
aws1


dfs.ha.namenodes.aws1
nn1,nn2


dfs.namenode.rpc-address.aws1.nn1
aws1:8020


dfs.namenode.rpc-address.aws1.nn2
aws2:8020


dfs.namenode.http-address.aws1.nn1
aws1:50070


dfs.namenode.http-address.aws1.nn2
aws2:50070





dfs.datanode.address
aws1:50010


dfs.datanode.ipc.address
aws1:50020


dfs.datanode.http.address
aws1:50075


dfs.datanode.https.address
aws1:50475


dfs.namenode.shared.edits.dir
qjournal://aws1:8485;aws2:8485;aws3:8485/mycluster


dfs.journalnode.edits.dir
/opt/bigdata/hadoop/ha/dfs/jn


dfs.client.failover.proxy.provider.aws1
org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider


dfs.ha.fencing.methods
sshfence


dfs.ha.fencing.ssh.private-key-files
/root/.ssh/id_dsa


dfs.ha.automatic-failover.enabled
true

• 2.1.5上传初始化jar包mysql-connector-java-8.0.16.jar
• 2.1.6上传初始化jar包ojdbc8.jar

2.2 初始化文件替换

cd /opt/Dsrelease
sudo rm -r $today/

echo "rm -r $today"

cd /opt/release

cp $packge_tar /opt/Dsrelease

cd /opt/Dsrelease

tar -zxvf $packge_tar
mv $packge  $today
p_api_lib=/opt/Dsrelease/$today/api-server/libs/
p_master_lib=/opt/Dsrelease/$today/master-server/libs/
p_worker_lib=/opt/Dsrelease/$today/worker-server/libs/
p_alert_lib=/opt/Dsrelease/$today/alert-server/libs/
p_tools_lib=/opt/Dsrelease/$today/tools/libs/
p_st_lib=/opt/Dsrelease/$today/standalone-server/libs/


p_api_conf=/opt/Dsrelease/$today/api-server/conf/
p_master_conf=/opt/Dsrelease/$today/master-server/conf/
p_worker_conf=/opt/Dsrelease/$today/worker-server/conf/
p_alert_conf=/opt/Dsrelease/$today/alert-server/conf/
p_tools_conf=/opt/Dsrelease/$today/tools/conf/
p_st_conf=/opt/Dsrelease/$today/standalone-server/conf/


cp $p0 $p4 $p_api_lib
cp $p0 $p4 $p_master_lib
cp $p0 $p4 $p_worker_lib
cp $p0 $p4 $p_alert_lib
cp $p0 $p4 $p_tools_lib
cp $p0 $p4 $p_st_lib

echo "cp $p0 $p_api_lib"

cp $p1 $p2 $p3 $p_api_conf
cp $p1 $p2 $p3 $p_master_conf
cp $p1 $p2 $p3 $p_worker_conf
cp $p1 $p2 $p3 $p_alert_conf
cp $p1 $p2 $p3 $p_tools_conf
cp $p1 $p2 $p3 $p_st_conf



echo "cp $p1 $p2 $p3 $p_api_conf"
}

define_param(){

packge_tar=apache-dolphinscheduler-dev-SNAPSHOT-bin.tar.gz
packge=apache-dolphinscheduler-dev-SNAPSHOT-bin
p0=/opt/action/tool/mysql-connector-java-8.0.16.jar
p1=/opt/action/tool/common.properties
p2=/opt/action/tool/core-site.xml
p3=/opt/action/tool/hdfs-site.xml
p4=/opt/action/tool/ojdbc8.jar

today=`date +%m%d`


}

2.3 配置文件内容替换

sed  -i 's/spark2/spark/g' /opt/Dsrelease/$today/worker-server/conf/dolphinscheduler_env.sh

cd /opt/Dsrelease/$today/bin/env/
sed -i '$aexport SPRING_PROFILES_ACTIVE=permission_shiro' dolphinscheduler_env.sh
sed -i '$aexport DATABASE="mysql"' dolphinscheduler_env.sh
sed -i '$aexport SPRING_DATASOURCE_DRIVER_CLASS_NAME="com.mysql.jdbc.Driver"' dolphinscheduler_env.sh
#自定义修改mysql配置
sed -i '$aexport SPRING_DATASOURCE_URL="jdbc:mysql://ctyun6:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8&allowMultiQueries=true&allowPublicKeyRetrieval=true"' dolphinscheduler_env.sh
sed -i '$aexport SPRING_DATASOURCE_USERNAME="root"' dolphinscheduler_env.sh
sed -i '$aexport SPRING_DATASOURCE_PASSWORD="root@123"' dolphinscheduler_env.sh
echo "替换jdbc配置成功"
#自定义修改zookeeper配置
sed -i '$aexport REGISTRY_TYPE=${REGISTRY_TYPE:-zookeeper}' dolphinscheduler_env.sh
sed -i '$aexport REGISTRY_ZOOKEEPER_CONNECT_STRING=${REGISTRY_ZOOKEEPER_CONNECT_STRING:-ctyun6:2181}' dolphinscheduler_env.sh
echo "替换zookeeper配置成功"
sed -i 's/resource.storage.type=HDFS/resource.storage.type=NONE/' /opt/Dsrelease/$today/master-server/conf/common.properties
sed -i 's/resource.storage.type=HDFS/resource.storage.type=NONE/' /opt/Dsrelease/$today/worker-server/conf/common.properties
sed -i 's/resource.storage.type=HDFS/resource.storage.type=NONE/' /opt/Dsrelease/$today/alert-server/conf/common.properties
sed -i 's/resource.storage.type=HDFS/resource.storage.type=NONE/' /opt/Dsrelease/$today/api-server/conf/common.properties
sed -i 's/hdfs.root.user=root/resource.hdfs.root.user=root/' /opt/Dsrelease/$today/master-server/conf/common.properties
sed -i 's/hdfs.root.user=root/resource.hdfs.root.user=root/' /opt/Dsrelease/$today/worker-server/conf/common.properties
sed -i 's/hdfs.root.user=root/resource.hdfs.root.user=root/' /opt/Dsrelease/$today/alert-server/conf/common.properties
sed -i 's/hdfs.root.user=root/resource.hdfs.root.user=root/' /opt/Dsrelease/$today/api-server/conf/common.properties
sed -i 's/fs.defaultFS=file:/resource.fs.defaultFS=file:/' /opt/Dsrelease/$today/master-server/conf/common.properties
sed -i 's/fs.defaultFS=file:/resource.fs.defaultFS=file:/' /opt/Dsrelease/$today/worker-server/conf/common.properties
sed -i 's/fs.defaultFS=file:/resource.fs.defaultFS=file:/' /opt/Dsrelease/$today/alert-server/conf/common.properties
sed -i 's/fs.defaultFS=file:/resource.fs.defaultFS=file:/' /opt/Dsrelease/$today/api-server/conf/common.properties
sed -i '$aresource.hdfs.fs.defaultFS=file:///' /opt/Dsrelease/$today/api-server/conf/common.properties
echo "替换common.properties配置成功"
# 替换master worker内存 api alert也可进行修改，具体根据当前服务器硬件配置而定，但要遵循Xms=Xmx=2Xmn的规律
cd /opt/Dsrelease/$today/
sed -i 's/Xms4g/Xms2g/g' worker-server/bin/start.sh
sed -i 's/Xmx4g/Xmx2g/g' worker-server/bin/start.sh
sed -i 's/Xmn2g/Xmn1g/g' worker-server/bin/start.sh
sed -i 's/Xms4g/Xms2g/g' master-server/bin/start.sh
sed -i 's/Xmx4g/Xmx2g/g' master-server/bin/start.sh
sed -i 's/Xmn2g/Xmn1g/g' master-server/bin/start.sh
echo "master worker内存修改完成"

}

3、删除HDFS配置

echo "开始删除hdfs配置"
sudo rm /opt/Dsrelease/$today/api-server/conf/core-site.xml
sudo rm /opt/Dsrelease/$today/api-server/conf/hdfs-site.xml
sudo rm /opt/Dsrelease/$today/worker-server/conf/core-site.xml
sudo rm /opt/Dsrelease/$today/worker-server/conf/hdfs-site.xml
sudo rm /opt/Dsrelease/$today/master-server/conf/core-site.xml
sudo rm /opt/Dsrelease/$today/master-server/conf/hdfs-site.xml
sudo rm /opt/Dsrelease/$today/alert-server/conf/core-site.xml
sudo rm /opt/Dsrelease/$today/alert-server/conf/hdfs-site.xml
echo "结束删除hdfs配置"
}

4、MySQL初始化

init_mysql(){

sql_path="/opt/Dsrelease/$today/tools/sql/sql/dolphinscheduler_mysql.sql"
sourceCommand="source $sql_path"
echo $sourceCommand
echo "开始source："
mysql -hlocalhost -uroot -proot@123 -D "dolphinscheduler" -e "$sourceCommand"
echo "结束source："
}

5、启动DolphinScheduler服务

stop_all_server(){
cd /opt/Dsrelease/$today
./bin/dolphinscheduler-daemon.sh stop api-server
./bin/dolphinscheduler-daemon.sh stop master-server
./bin/dolphinscheduler-daemon.sh stop worker-server
./bin/dolphinscheduler-daemon.sh stop alert-server
ps -ef|grep api-server|grep -v grep|awk '{print "kill -9 " $2}' |sh
ps -ef|grep master-server |grep -v grep|awk '{print "kill -9 " $2}' |sh
ps -ef|grep worker-server |grep -v grep|awk '{print "kill -9 " $2}' |sh
ps -ef|grep alert-server |grep -v grep|awk '{print "kill -9 " $2}' |sh
}

run_all_server(){
cd /opt/Dsrelease/$today
./bin/dolphinscheduler-daemon.sh start api-server
./bin/dolphinscheduler-daemon.sh start master-server
./bin/dolphinscheduler-daemon.sh start worker-server
./bin/dolphinscheduler-daemon.sh start alert-server
}

集群部署

1、开放mysql和zookeeper对外端口 2、集群部署及启动

复制完成初始化的文件夹到指定的服务器，启动指定服务即可完成集群部署，要连同一个Zookeeper和MySQL。

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