A Comprehensive Guide to Building DolphinScheduler 3.2.0 Production-Grade Cluster Deploymentby@zhoujieguang
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3,871 reads

A Comprehensive Guide to Building DolphinScheduler 3.2.0 Production-Grade Cluster Deployment

by Zhou JieguangMay 17th, 2024
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DolphinScheduler provides powerful workflow management and scheduling capabilities for data engineers by simplifying complex task dependencies. In version 3.2.0, DolphinScheduler introduces a series of new features and improvements, significantly enhancing its stability and availability in production environments.
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Introduction: DolphinScheduler provides powerful workflow management and scheduling capabilities for data engineers by simplifying complex task dependencies. In version 3.2.0, DolphinScheduler introduces a series of new features and improvements, significantly enhancing its stability and availability in production environments.

To help readers better understand and apply this version, we have carefully prepared this DolphinScheduler 3.2.0 Production Cluster High Availability Setup Guide, delving into how to set up a high-available DolphinScheduler cluster in a production environment, including but not limited to environment preparation, database configuration, user permission settings, SSH keyless login configuration, ZooKeeper startup, and service startup and shutdown procedures.

1. Environment Preparation

1.1 Cluster Planning

The installation environment is contos 7.9.

DolphinScheduler-3.2.0 Official Website:

Official Installation Documentation:

1.3 Preparatory Work

  • JDK: Download JDK (1.8+), install and configure the JAVA_HOME environment variable, and append its bin directory to the PATH environment variable. Skip this step if JDK is already installed in your environment.
  • Binary Package: Download the DolphinScheduler binary package from the download page.
  • Database: PostgreSQL (8.2.15+) or MySQL (5.7+), choose either of them, e.g., MySQL requires JDBC Driver 8.0.16.
  • Process Tree Analysis:
  • macOS: Install pstree.
  • Fedora/Red/Hat/CentOS/Ubuntu/Debian: Install psmisc.

[hadoop@hadoop1 ~]$ sudo yum install -y psmisc

Note: While DolphinScheduler itself does not depend on Hadoop, Hive, or Spark, corresponding environment support is needed if your tasks rely on them.

2. DolphinScheduler Cluster Installation

2.1 Extract Installation Package

  1. Upload the DolphinScheduler installation package to the /data/software directory of the hadoop1 node.
  2. Extract the package to the current directory.

hadoop@hadoop1 software]$ tar -zxvf apache-dolphinscheduler-3.2.0-bin

2.2 Database Configuration

DolphinScheduler metadata is stored in a relational database, so create the corresponding database and user.

mysql -uroot -p
Create the database:
Mysql>CREATE DATABASE dolphinscheduler DEFAULT CHARACTER SET utf8 DEFAULT COLLATE utf8_general_ci;
//Create the user:
//revise {user} and {password} name and paaaword as you wish
mysql>CREATE USER '{user}'@'%' IDENTIFIED BY '{password}';
mysql>Grant privileges:
mysql>GRANT ALL PRIVILEGES ON dolphinscheduler.* TO '{user}'@'%';

Note: If you encounter an error message _ERROR 1819 (HY000): Your password does not satisfy the current policy requirements_indicating the password does not meet policy requirements, you can either increase password complexity or execute commands to lower the MySQL password strength level.

mysql> set global validate_password_policy=0;
mysql> set global validate_password_length=4;

Granting User Permissions

mysql> GRANT ALL PRIVILEGES ON dolphinscheduler.* TO 'dolphinscheduler'@'%';

If using MySQL, you need to manually download the mysql-connector-java driver (version 8.0.31) and move it to the libs directory of each DolphinScheduler module, including api-server/libs, alert-server/libs, master-server/libs, worker-server/libs, and tools/libs.

Note: If you only want to use MySQL in the data source center, there is no requirement for the version of the MySQL JDBC driver. However, if you want to use MySQL as DolphinScheduler’s metadata database, only version 8.0.16 and above are supported.

echo /data/software/dolphinscheduler-3.2.0/master-server/libs/ /data/software/dolphinscheduler-3.2.0/alert-server/libs/ /data/software/dolphinscheduler-3.2.0/api-server/libs/ /data/software/dolphinscheduler-3.2.0/worker-server/libs/ /data/software/dolphinscheduler-3.2.0/tools/libs/ | xargs -n 1 cp -v /data/software/mysql-8.0.31/mysql-connector-j-8.0.31.jar

2.2 Preparing DolphinScheduler Startup Environment

  • Configure User SSH Access and Permissions

If you already have an existing Hadoop cluster account, it is recommended to use it directly without configuration

Create a deployment user and be sure to configure sudo password-free. Take, for example, creating a Hadoop user

# To create a user, you need to log in as rootuseradd hadoop

# Add a passwordecho "hadoop" | passwd --stdin hadoop# Configure sudo password-freesed -i '$ahadoop  ALL=(ALL)  NOPASSWD: NOPASSWD: ALL' /etc/sudoerssed -i 's/Defaults    requirett/#Defaults    requirett/g' /etc/sudoers# Modify the directory permissions so that the deployment user has the operation permission to the apache-dolphinscheduler-*-bin directory after the binary package is decompressedchown -R hadoop:hadoop apache-dolphinscheduler-*-binchmod -R 755 apache-dolphinscheduler-*-bin


1. Because the task execution service implements multi-tenant running jobs by switching between different Linux users with sudo -u {linux-user}, the deployment user needs to have sudo permissions, and it is password-free. If a beginner doesn’t understand, he or she can ignore this for a while

2. If you find a line “Defaults requirett” in the /etc/sudoers file, please comment it out as well

  • Configure SSH password-free login on the machineSince resources need to be sent to different machines during installation, SSH password-free login is required between each machine. The following steps are performed to configure passwordless login
su hadoop
ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa
cat ~/.ssh/ >> ~/.ssh/authorized_keys
chmod 600 ~/.ssh/authorized_keys

Note: After the configuration is complete, you can run the command ssh localhost to determine whether it is successful, if you can ssh login without entering a password, it will prove that it is successful

2.3 Start ZooKeeper (no need to configure a Hadoop cluster)

Go to the zookeeper installation directory and copy the zoo_sample.cfg configuration file to conf/zoo.cfg, and change the value in dataDir in conf/zoo.cfg to dataDir=./tmp/zookeeper

# Start ZooKeeper
./bin/ start

2.4 Revise file

The file outlines the machines on which DolphinScheduler will be installed and the services that will be deployed on each machine. Located at bin/env/, you can modify the environment variables using the format: export <ENV_NAME>=. Below are the configuration details:

# Modify it if you use a different SSH port
# A comma-separated list of machine hostname or IP addresses that will host the Master server. It must be a subset of the configuration `ips`.
# Example for hostnames: masters="ds1,ds2", Example for IPs: masters=","
# A comma-separated list of machine <hostname>:<workerGroup> or <IP>:<workerGroup>. All hostnames or IPs must be a subset of the configuration `ips`, and the workerGroup has a default value of `default`, but we recommend you declare it after the hosts.
# Example for hostnames: workers="ds1:default,ds2:default,ds3:default", Example for IPs: workers=",,"
# A comma-separated list of machine hostname or IP addresses that will host the Alert server. It must be a subset of the configuration `ips`.
# Example for hostname: alertServer="ds3", Example for IP: alertServer=""
# A comma-separated list of machine hostname or IP addresses that will host the API server. It must be a subset of the configuration `ips`.
# Example for hostname: apiServers="ds1", Example for IP: apiServers=""
# The directory to install DolphinScheduler on all machines defined above. It will automatically be created by the `` script if it doesn't exist.
# Do not set this configuration to be the same as the current path (pwd). Do not enclose it in quotes if you are using a relative path.
# The user to deploy DolphinScheduler on all machines defined above. This user must be created manually before running the `` script. The user needs sudo privileges and permissions to operate HDFS. If HDFS is enabled, the root directory must be created by this user.
# The root directory of ZooKeeper. For now, DolphinScheduler's default registry server is ZooKeeper.
# It will delete ${zkRoot} in ZooKeeper when you run, so please keep it consistent with registry.zookeeper.namespace in yml files.
# Similarly, if you want to modify the value, please modify registry.zookeeper.namespace in yml files as well.

2.5 Modify the file

The file ./bin/env/dolphinscheduler_env.shdescribes the following configurations: The database configuration of DolphinScheduler, the detailed configuration method is in [Initializing the Database], some task type external dependency paths or library files, such as JAVA_HOME and SPARK_HOME, are defined here.

If you do not use certain task types, you can ignore the external dependencies of the tasks, but you must change the JAVA_HOME, registry, and database-related configurations according to your environment.

export JAVA_HOME=${JAVA_HOME:-/data/module/jdk1.8.0_212}
# Database related configuration, set database type, username and password
export DATABASE=${DATABASE:-mysql}
export SPRING_DATASOURCE_URL="jdbc:mysql://xxxx:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8"
# Registry center configuration, determines the type and link of the registry center
export REGISTRY_TYPE=${REGISTRY_TYPE:-zookeeper}
export HADOOP_HOME=${HADOOP_HOME:-/data/module/hadoop-3.3.4}
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-/data/module/hadoop-3.3.4/etc/hadoop}
export SPARK_HOME1=${SPARK_HOME1:-/data/module/spark-3.3.1}
#export SPARK_HOME2=${SPARK_HOME2:-/opt/soft/spark2}
#export PYTHON_HOME=${PYTHON_HOME:-/opt/soft/python}
export HIVE_HOME=${HIVE_HOME:-/data/module/hive-3.1.3}
export FLINK_HOME=${FLINK_HOME:-/data/module/flink-1.16.2}
export DATAX_HOME=${DATAX_HOME:-/data/module/datax}
#export SEATUNNEL_HOME=${SEATUNNEL_HOME:-/opt/soft/seatunnel}
#export CHUNJUN_HOME=${CHUNJUN_HOME:-/opt/soft/chunjun}

After configuring the environment variables, you can proceed with the DolphinScheduler installation process.

2.6 Initialize the database

After completing the above steps, you have created a new database for DolphinScheduler and configured it in DolphinScheduler. Now, you can initialize the database through a quick Shell script.

bash tools/bin/

2.7 Modify the application.yaml file

There are5 files, the parts that need to be modified are the same, but the other configurations inside are different and need to be rewritten separately. They are:

  • master-server/conf/application.yaml
  • api-server/conf/application.yaml
  • worker-server/conf/application.yaml
  • alert-server/conf/application.yaml
  • tools/conf/application.yaml

    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://xxxx:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8
    username: xxx
    password: xxx
  type: zookeeper
    namespace: dolphinscheduler
    connect-string: xxxx
      base-sleep-time: 60ms
      max-sleep: 300ms
      max-retries: 5
    session-timeout: 30s
    connection-timeout: 9s
    block-until-connected: 600ms
    digest: ~
      on-profile: mysql
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql:/xxxx:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8
    username: xxxx
    password: xxxx
      org.quartz.jobStore.driverDelegateClass: org.quartz.impl.jdbcjobs

2.8. Modify File

Similarly, there are 5 files to modify, with the same sections needing modification but with different configurations inside. The modifications need to be made separately for:

  • master-server/conf/
  • api-server/conf/
  • worker-server/conf/
  • alert-server/conf/
  • tools/conf/

data.basedir.path=Customize the local file storage location
# resource store on HDFS/S3 path, resource file will store to this base path, self configuration, please make sure the directory exists on hdfs and have read write permissions. "/dolphinscheduler" is recommended the hdsf location
resource.hdfs.root.user=Customize the username and keep it consistent with the previous configuration in the document.
# if, the value like: s3a://dolphinscheduler; if and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir
#A highly available IP address
# 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
# job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)

Note: In this case, DolphinScheduler’s distributed storage is using HDFS. If other configurations are required, you can configure them according to the instructions on the official website.

2.9. Distributed Storage HDFS Dependency Distribution

echo /data/software/dolphinscheduler-3.2.0/master-server/conf/ /data/software/dolphinscheduler-3.2.0/alert-server/conf/ /data/software/dolphinscheduler-3.2.0/api-server/conf/ /data/software/dolphinscheduler-3.2.0/worker-server/conf/ | xargs -n 1 cp -v /data/module/hadoop-3.3.4/etc/hadoop/core-site.xml /data/module/hadoop-3.3.4/etc/hadoop/hdfs-site.xml

2.10 Start DolphinScheduler

Using the deployment user created above, run the following command to complete the deployment, and the post-deployment run logs will be stored in the logs folder.

bash ./bin/

Note: For the first deployment, there may be 5 times sh: bin/ No such file or directory information, which can be ignored as non-important information

2.11 Log in to DolphinScheduler

Log in to the system UI by accessing the browser address http://localhost:12345/dolphinscheduler/ui. The default username and password is admin/dolphinscheduler123

3. Start and Stop Services

# Stop all cluster services
bash ./bin/
# Start all cluster services
bash ./bin/
# Start/stop Master
bash ./bin/ stop master-server
bash ./bin/ start master-server
# Start/stop Worker
bash ./bin/ start worker-server
bash ./bin/ stop worker-server
# Start/stop API
bash ./bin/ start api-server
bash ./bin/ stop api-server
# Start/stop Alert
bash ./bin/ start alert-server
bash ./bin/ stop alert-server