告别手动调度，海豚调度器 3.1.x 集群部署让你轻松管理多机！

2.1. 基础组件

• JDK：下载JDK (1.8+ https://www.oracle.com/technetwork/java/javase/downloads/index.html)，安装并配置 JAVA_HOME 环境变量，并将其下的 bin 目录追加到 PATH 环境变量中。如果你的环境中已存在，可以跳过这步。
• 二进制包：在下载页面下载(https://dolphinscheduler.apache.org/zh-cn/download) DolphinScheduler 二进制包
• 数据库：PostgreSQL (8.2.15+ https://www.postgresql.org/download/) 或者 MySQL (5.7+)，两者任选其一即可，如 MySQL 则需要 JDBC Driver 8 版本，可以从中央仓库下载。
• 注册中心：ZooKeeper (3.4.6+)，下载地址https://zookeeper.apache.org/releases.html。
• 进程树分析
• macOS安装pstree
• Fedora/Red/Hat/CentOS/Ubuntu/Debian安装psmisc。

tar -xvf apache-dolphinscheduler-3.1.7-bin.tar.gz
mv apache-dolphinscheduler-3.1.7-bin dolphinscheduler-3.1.7-origin

4.1. 配置用户免密及权限

# 创建用户需使用 root 登录
useradd dolphinscheduler

# 添加密码
echo "dolphinscheduler" | passwd --stdin dolphinscheduler

# 配置 sudo 免密
sed -i '$adolphinscheduler  ALL=(ALL)  NOPASSWD: ALL' etc/sudoers
sed -i 's/Defaults    requirett/#Defaults    requirett/g' etc/sudoers

# 修改目录权限，使得部署用户对二进制包解压后的 apache-dolphinscheduler-*-bin 目录有操作权限
chown -R dolphinscheduler:dolphinscheduler apache-dolphinscheduler-*-bin

• 因为任务执行服务是以 sudo -u {linux-user} 切换不同 linux 用户的方式来实现多租户运行作业，所以部署用户需要有 sudo 权限，而且是免密的。初学习者不理解的话，完全可以暂时忽略这一点。
• 如果发现 etc/sudoers 文件中有 “Defaults requirett” 这行，也请注释掉。

4.2. 配置机器SSH免密登陆

su dolphinscheduler

ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
# 一定要执行下面这个命令，否则免密登录会失败
chmod 600 ~/.ssh/authorized_keys

6.1. install_env.sh

# ---------------------------------------------------------
# INSTALL MACHINE
# ---------------------------------------------------------
# A comma separated list of machine hostname or IP would be installed DolphinScheduler,
# including master, worker, api, alert. If you want to deploy in pseudo-distributed
# mode, just write a pseudo-distributed hostname
# Example for hostnames: ips="ds1,ds2,ds3,ds4,ds5", Example for IPs: ips="192.168.8.1,192.168.8.2,192.168.8.3,192.168.8.4,192.168.8.5"
# 配置海豚调度器要安装到那些机器上
ips=${ips:-"ds01,ds02,ds03,hadoop02,hadoop03,hadoop04,hadoop05,hadoop06,hadoop07,hadoop08"}

# Port of SSH protocol, default value is 22. For now we only support same port in all `ips` machine
# modify it if you use different ssh port
sshPort=${sshPort:-"22"}

# A comma separated list of machine hostname or IP would be installed Master server, it
# must be a subset of configuration `ips`.
# Example for hostnames: masters="ds1,ds2", Example for IPs: masters="192.168.8.1,192.168.8.2"
# 配置 master 角色要安装到哪些机器上
masters=${masters:-"ds01,ds02,ds03,hadoop04,hadoop05,hadoop06,hadoop07,hadoop08"}

# A comma separated list of machine <hostname>:<workerGroup> or <IP>:<workerGroup>.All hostname or IP must be a
# subset of configuration `ips`, And workerGroup have default value as `default`, but we recommend you declare behind the hosts
# Example for hostnames: workers="ds1:default,ds2:default,ds3:default", Example for IPs: workers="192.168.8.1:default,192.168.8.2:default,192.168.8.3:default"
# 配置 worker 角色要安装到哪些机器上，默认都放到 default 的 worker 分组内，其他分组，可以通过海豚调度器界面进行单独配置
workers=${workers:-"ds01:default,ds02:default,ds03:default,hadoop02:default,hadoop03:default,hadoop04:default,hadoop05:default,hadoop06:default,hadoop07:default,hadoop08:default"}

# A comma separated list of machine hostname or IP would be installed Alert server, it
# must be a subset of configuration `ips`.
# Example for hostname: alertServer="ds3", Example for IP: alertServer="192.168.8.3"
# 配置 alert 角色安装到哪个机器上，配置一台机器即可
alertServer=${alertServer:-"hadoop03"}

# A comma separated list of machine hostname or IP would be installed API server, it
# must be a subset of configuration `ips`.
# Example for hostname: apiServers="ds1", Example for IP: apiServers="192.168.8.1"
# 配置 api 角色安装到哪个机器上，配置一台机器即可
apiServers=${apiServers:-"hadoop04"}

# The directory to install DolphinScheduler for all machine we config above. It will automatically be created by `install.sh` script if not exists.
# Do not set this configuration same as the current path (pwd). Do not add quotes to it if you using related path.
# 配置安装路径，将会在所有海豚集群的机器上安装服务，一定要和上面解压的二进制包目录区分开，最好带上版本号，以方便后续的升级操作。
installPath=${installPath:-"/opt/dolphinscheduler-3.1.5"}

# The user to deploy DolphinScheduler for all machine we config above. For now user must create by yourself before running `install.sh`
# script. The user needs to have sudo privileges and permissions to operate hdfs. If hdfs is enabled than the root directory needs
# to be created by this user
# 部署使用的用户，用上面自己新建的用户即可
deployUser=${deployUser:-"dolphinscheduler"}

# The root of zookeeper, for now DolphinScheduler default registry server is zookeeper.
# 配置注册到 zookeeper znode 名称，如果配置了多个海豚集群，则需要配置不同的名称
zkRoot=${zkRoot:-"/dolphinscheduler"}

6.2. dolphinscheduler_env.sh

# JDK 路径，一定要修改
export JAVA_HOME=${JAVA_HOME:-/usr/java/jdk1.8.0_202}

# 数据库类型，支持 mysql、postgresql
export DATABASE=${DATABASE:-mysql}
export SPRING_PROFILES_ACTIVE=${DATABASE}
# 连接 url，主要修改下面的 hostname，最后配置的是东八区
export SPRING_DATASOURCE_URL="jdbc:mysql://hostname:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8&useSSL=false&serverTimezone=Asia/Shanghai"
export SPRING_DATASOURCE_USERNAME=dolphinscheduler
# 如果密码比较复杂，则需要前后使用英文单引号括起来
export SPRING_DATASOURCE_PASSWORD='xxxxxxxxxxxxx'

export SPRING_CACHE_TYPE=${SPRING_CACHE_TYPE:-none}
# 配置各角色 JVM 启动时使用的时区，默认为 -UTC，如果想要完全支持东八区，则设置为 -GMT+8
export SPRING_JACKSON_TIME_ZONE=${SPRING_JACKSON_TIME_ZONE:-GMT+8}
export MASTER_FETCH_COMMAND_NUM=${MASTER_FETCH_COMMAND_NUM:-10}

export REGISTRY_TYPE=${REGISTRY_TYPE:-zookeeper}
# 配置使用的 zookeeper 地址
export REGISTRY_ZOOKEEPER_CONNECT_STRING=${REGISTRY_ZOOKEEPER_CONNECT_STRING:-hadoop01:2181,hadoop02:2181,hadoop03:2181}

# 配置使用到的一些环境变量，按照自己的需要进行配置即可，所有需要的组件，都自己安装
export HADOOP_HOME=${HADOOP_HOME:-/opt/cloudera/parcels/CDH/lib/hadoop}
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-/etc/hadoop/conf}
export SPARK_HOME1=${SPARK_HOME1:-/opt/soft/spark1}
export SPARK_HOME2=${SPARK_HOME2:-/opt/spark-3.3.2}
export PYTHON_HOME=${PYTHON_HOME:-/opt/python-3.9.16}
export HIVE_HOME=${HIVE_HOME:-/opt/cloudera/parcels/CDH/lib/hive}
export FLINK_HOME=${FLINK_HOME:-/opt/flink-1.15.3}
export DATAX_HOME=${DATAX_HOME:-/opt/datax}
export SEATUNNEL_HOME=${SEATUNNEL_HOME:-/opt/seatunnel-2.1.3}
export CHUNJUN_HOME=${CHUNJUN_HOME:-/opt/soft/chunjun}

export PATH=$HADOOP_HOME/bin:$SPARK_HOME1/bin:$SPARK_HOME2/bin:$PYTHON_HOME/bin:$JAVA_HOME/bin:$HIVE_HOME/bin:$FLINK_HOME/bin:$DATAX_HOME/bin:$SEATUNNEL_HOME/bin:$CHUNJUN_HOME/bin:$PATH

6.3. common.properties

# 本地路径，主要用来存放任务运行时的临时文件，要保证用户对该文件具有读写权限，一般保持默认即可，如果后续任务运行报错说是对该目录下的文件没有操作权限，直接将该目录权限修改为 777 即可
data.basedir.path=/tmp/dolphinscheduler

# resource view suffixs
#resource.view.suffixs=txt,log,sh,bat,conf,cfg,py,java,sql,xml,hql,properties,json,yml,yaml,ini,js

# 保存资源的地方，可用值为: HDFS, S3, OSS, NONE
resource.storage.type=HDFS
# 资源上传的基本路径，必须以 dolphinscheduler 开头，要保证用户对该目录有读写权限
resource.storage.upload.base.path=/dolphinscheduler

# The AWS access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.access.key.id=minioadmin
# The AWS secret access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.secret.access.key=minioadmin
# The AWS Region to use. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.region=cn-north-1
# The name of the bucket. You need to create them by yourself. Otherwise, the system cannot start. All buckets in Amazon S3 share a single namespace; ensure the bucket is given a unique name.
resource.aws.s3.bucket.name=dolphinscheduler
# You need to set this parameter when private cloud s3. If S3 uses public cloud, you only need to set resource.aws.region or set to the endpoint of a public cloud such as S3.cn-north-1.amazonaws.com.cn
resource.aws.s3.endpoint=http://localhost:9000

# alibaba cloud access key id, required if you set resource.storage.type=OSS
resource.alibaba.cloud.access.key.id=<your-access-key-id>
# alibaba cloud access key secret, required if you set resource.storage.type=OSS
resource.alibaba.cloud.access.key.secret=<your-access-key-secret>
# alibaba cloud region, required if you set resource.storage.type=OSS
resource.alibaba.cloud.region=cn-hangzhou
# oss bucket name, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.bucket.name=dolphinscheduler
# oss bucket endpoint, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.endpoint=https://oss-cn-hangzhou.aliyuncs.com

# if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
resource.hdfs.root.user=hdfs
# 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
# 
resource.hdfs.fs.defaultFS=hdfs://bigdata:8020

# 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


# 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=hadoop02,hadoop03
# if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace ds1 to actual resourcemanager hostname
yarn.application.status.address=http://ds1:%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://hadoop02:19888/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
setTaskDirToTenant.enable=false

# 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

# set path of conda.sh
conda.path=/opt/anaconda3/etc/profile.d/conda.sh

# Task resource limit state
task.resource.limit.state=false

# mlflow task plugin preset repository
ml.mlflow.preset_repository=https://github.com/apache/dolphinscheduler-mlflow
# mlflow task plugin preset repository version
ml.mlflow.preset_repository_version="main"

6.4. application.yaml

spring:
  banner:
    charset: UTF-8
  jackson:
    # 将时区设置为东八区，只修改这一个地方即可
    time-zone: GMT+8
    date-format: "yyyy-MM-dd HH:mm:ss"

6.5. service.57a50399.js和service.57a50399.js.gz

驱动配置

数据库用户

create database `dolphinscheduler` character set utf8mb4 collate utf8mb4_general_ci;
create user 'dolphinscheduler'@'%' IDENTIFIED WITH mysql_native_password by 'your_password';
grant ALL PRIVILEGES ON dolphinscheduler.* to 'dolphinscheduler'@'%';
flush privileges;

执行数据库升级脚本：

bash tools/bin/upgrade-schema.sh

# 一键停止集群所有服务
bash ./bin/stop-all.sh

# 一键开启集群所有服务
bash ./bin/start-all.sh

# 启停 Master
bash ./bin/dolphinscheduler-daemon.sh stop master-server
bash ./bin/dolphinscheduler-daemon.sh start master-server

# 启停 Worker
bash ./bin/dolphinscheduler-daemon.sh start worker-server
bash ./bin/dolphinscheduler-daemon.sh stop worker-server

# 启停 Api
bash ./bin/dolphinscheduler-daemon.sh start api-server
bash ./bin/dolphinscheduler-daemon.sh stop api-server

# 启停 Alert
bash ./bin/dolphinscheduler-daemon.sh start alert-server
bash ./bin/dolphinscheduler-daemon.sh stop alert-server

10.1. 标准方式

1. 新节点
1. 安装配置好 JDK。
2. 新建海豚用户（Linux 用户），然后配置免密登录、权限等。
2. 之前安装海豚调度器时解压二进制安装包的机器上。
1. 登录安装海豚的用户。
2. 切换到之前安装海豚调度器时解压二进制安装包，修改配置文件：bin/env/install_env.sh
   ，在该配置文件中，修改需要在新节点上部署的角色。
3. 执行 /bin/install.sh
    文件进行安装，该脚本会按照 bin/env/install_env.sh
    文件中的配置，将整个目录重新 scp
    到所有的机器，之后停止所有机器上的角色，然后再启动所有角色。

10.2. 简单方式

1. 新节点
1. 安装配置好 JDK。
2. 新建海豚用户（Linux 用户），然后配置免密登录、权限等。
2. 之前安装海豚调度器时解压二进制安装包的机器上。
1. 登录安装海豚的用户。
2. 将之前修改完配置的整个目录直接压缩，然后传输到新节点上。
3. 新节点
1. 在新节点上解压文件，然后将其重命名到之前配置文件 bin/env/install_env.sh
    中配置的安装目录下。
2. 登录安装海豚的用户。
3. 需要在新节点部署哪些角色，就启动哪些角色，具体脚本位置：/bin/dolphinscheduler-daemon.sh
   ，启动命令为：

./dolphinscheduler-daemon.sh start master-server
./dolphinscheduler-daemon.sh start worker-server

1. 登录到海豚调度器界面，然后“监控中心”中观察，对应角色在新节点是否启动。

1. 在需要下线的机器上，通过 /bin/dolphinscheduler-daemon.sh
   脚本停止机器上所有的角色，停止命令为：

./dolphinscheduler-daemon.sh stop worker-server

1. 登录到海豚调度器界面，然后“监控中心”中观察，刚才机器上停止的角色是否已经消失。
2. 在之前安装海豚调度器时解压二进制安装包的机器上
3. 登录安装海豚的用户。
4. 修改配置文件：bin/env/install_env.sh
   ，在该配置文件中，删除下线角色对应的机器。

1. 上传新版二进制包。
2. 解压，解压到和旧版安装目录不同的目录，或者是重命名也可以。
3. 修改配置文件，比较简单的方式是，将上面步骤中涉及到的所有配置文件，从之前安装的目录下拷贝到新版本目录下，替换即可。
4. 将其他节点上部署的一些组件，全部打包，然后解压放到新节点对应的位置。具体需要拷贝哪些组件，可以查看 dolphinscheduler_env.sh 文件中的配置。
5. 配置驱动，参考《初始化数据库》中的步骤。
6. 停止之前的集群。
7. 备份整个数据库。
8. 执行数据库升级脚本，参考《初始化数据库》中的步骤。
9. 执行安装脚本，参考《安装》。
10. 升级完成，登录界面，查看“监控中心”，看所有角色是否都成功启动。

我知道你在看哟