cd /tmp

3. 解压下载的压缩包到指定文件夹

mkdir -p /opt/soft/dolphinscheduler
tar -zxvf /tmp/apache-dolphinscheduler-3.1.4-bin.tar.gz -C /opt/soft/dolphinscheduler

msyql -u root -p

CREATE DATABASE dolphinscheduler DEFAULT CHARACTER SET utf8 COLLATE utf8_general_ci;

vim /opt/soft/dolphinscheduler/apache-dolphinscheduler-3.1.4-bin/bin/env/dolphinscheduler_env.sh

内容如下：

# JAVA_HOME, will use it to start DolphinScheduler server
export JAVA_HOME=${JAVA_HOME:-/root/jdk1.8.0_11}   # 修改为自己的jdk安装目录

# 修改MySQL配置
# Database related configuration, set database type, username and password
export DATABASE=${DATABASE:-mysql}
export SPRING_PROFILES_ACTIVE=${DATABASE}
export SPRING_DATASOURCE_URL="jdbc:mysql://localhost:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8&useSSL=false"
export SPRING_DATASOURCE_USERNAME="dolphinscheduler"
export SPRING_DATASOURCE_PASSWORD="dolphinscheduler"

# DolphinScheduler server related configuration
export SPRING_CACHE_TYPE=${SPRING_CACHE_TYPE:-none}
export SPRING_JACKSON_TIME_ZONE=${SPRING_JACKSON_TIME_ZONE:-UTC}
export MASTER_FETCH_COMMAND_NUM=${MASTER_FETCH_COMMAND_NUM:-10}

# Registry center configuration, determines the type and link of the registry center
export REGISTRY_TYPE=${REGISTRY_TYPE:-zookeeper}
export REGISTRY_ZOOKEEPER_CONNECT_STRING=${REGISTRY_ZOOKEEPER_CONNECT_STRING:-localhost:2181}

# Tasks related configurations, need to change the configuration if you use the related tasks.
export HADOOP_HOME=${HADOOP_HOME:-/opt/soft/hadoop}
export HADOOP_CONF_DIR=${HADOOP_CONF_DIR:-/opt/soft/hadoop/etc/hadoop}
export SPARK_HOME1=${SPARK_HOME1:-/opt/soft/spark1}
export SPARK_HOME2=${SPARK_HOME2:-/opt/soft/spark2}
export PYTHON_HOME=${PYTHON_HOME:-/opt/soft/python}
export HIVE_HOME=${HIVE_HOME:-/opt/soft/hive}
export FLINK_HOME=${FLINK_HOME:-/opt/soft/flink}
export DATAX_HOME=${DATAX_HOME:-/opt/soft/datax}
export SEATUNNEL_HOME=${SEATUNNEL_HOME:-/opt/soft/seatunnel}
export CHUNJUN_HOME=${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

9. 修改 application.yaml 文件

vim /opt/soft/dolphinscheduler/apache-dolphinscheduler-3.1.4-bin/standalone-server/conf/application.yaml

主要修改的位置有两处：前面的datasource和后面datasource，这两处都改成如下即可

datasource:
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://127.0.0.1:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8
    username: dolphinscheduler
    password: dolphinscheduler

可以在vim的命令下输入 /datasource ，回车便会跳转，按 n 可以查看下一个

修改后的内容如下所示

spring:
  jackson:
    time-zone: UTC
    date-format: "yyyy-MM-dd HH:mm:ss"
  banner:
    charset: UTF-8
  cache:
    # default enable cache, you can disable by `type: none`
    type: none
    cache-names:
      - tenant
      - user
      - processDefinition
      - processTaskRelation
      - taskDefinition
    caffeine:
      spec: maximumSize=100,expireAfterWrite=300s,recordStats
  sql:
    init:
      schema-locations: classpath:sql/dolphinscheduler_h2.sql
  datasource:
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://127.0.0.1:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8
    username: dolphinscheduler
    password: dolphinscheduler
  quartz:
    job-store-type: jdbc
    jdbc:
      initialize-schema: never
    properties:
      org.quartz.threadPool:threadPriority: 5
      org.quartz.jobStore.isClustered: true
      org.quartz.jobStore.class: org.springframework.scheduling.quartz.LocalDataSourceJobStore
      org.quartz.scheduler.instanceId: AUTO
      org.quartz.jobStore.tablePrefix: QRTZ_
      org.quartz.jobStore.acquireTriggersWithinLock: true
      org.quartz.scheduler.instanceName: DolphinScheduler
      org.quartz.threadPool.class: org.quartz.simpl.SimpleThreadPool
      org.quartz.jobStore.useProperties: false
      org.quartz.threadPool.makeThreadsDaemons: true
      org.quartz.threadPool.threadCount: 25
      org.quartz.jobStore.misfireThreshold: 60000
      org.quartz.scheduler.makeSchedulerThreadDaemon: true
      org.quartz.jobStore.driverDelegateClass: org.quartz.impl.jdbcjobstore.StdJDBCDelegate
      org.quartz.jobStore.clusterCheckinInterval: 5000
  servlet:
    multipart:
      max-file-size: 1024MB
      max-request-size: 1024MB
  messages:
    basename: i18n/messages
  jpa:
    hibernate:
      ddl-auto: none
  mvc:
    pathmatch:
      matching-strategy: ANT_PATH_MATCHER

registry:
  type: zookeeper
  zookeeper:
    namespace: dolphinscheduler
    connect-string: localhost:2181
    retry-policy:
      base-sleep-time: 60ms
      max-sleep: 300ms
      max-retries: 5
    session-timeout: 30s
    connection-timeout: 9s
    block-until-connected: 600ms
    digest: ~

security:
  authentication:
    # Authentication types (supported types: PASSWORD,LDAP)
    type: PASSWORD
    # IF you set type `LDAP`, below config will be effective
    ldap:
      # ldap server config
      urls: ldap://ldap.forumsys.com:389/
      base-dn: dc=example,dc=com
      username: cn=read-only-admin,dc=example,dc=com
      password: password
      user:
        # admin userId when you use LDAP login
        admin: read-only-admin
        identity-attribute: uid
        email-attribute: mail
        # action when ldap user is not exist (supported types: CREATE,DENY)
        not-exist-action: CREATE

# Traffic control, if you turn on this config, the maximum number of request/s will be limited.
# global max request number per second
# default tenant-level max request number
traffic:
  control:
    global-switch: false
    max-global-qps-rate: 300
    tenant-switch: false
    default-tenant-qps-rate: 10
    #customize-tenant-qps-rate:
      # eg.
      #tenant1: 11
      #tenant2: 20

master:
  listen-port: 5678
  # master fetch command num
  fetch-command-num: 10
  # master prepare execute thread number to limit handle commands in parallel
  pre-exec-threads: 10
  # master execute thread number to limit process instances in parallel
  exec-threads: 10
  # master dispatch task number per batch
  dispatch-task-number: 3
  # master host selector to select a suitable worker, default value: LowerWeight. Optional values include random, round_robin, lower_weight
  host-selector: lower_weight
  # master heartbeat interval
  heartbeat-interval: 10s
  # Master heart beat task error threshold, if the continuous error count exceed this count, the master will close.
  heartbeat-error-threshold: 5
  # master commit task retry times
  task-commit-retry-times: 5
  # master commit task interval
  task-commit-interval: 1s
  state-wheel-interval: 5s
  # master max cpuload avg, only higher than the system cpu load average, master server can schedule. default value -1: the number of cpu cores * 2
  max-cpu-load-avg: -1
  # master reserved memory, only lower than system available memory, master server can schedule. default value 0.3, the unit is G
  reserved-memory: 0.3
  # failover interval
  failover-interval: 10m
  # kill yarn jon when failover taskInstance, default true
  kill-yarn-job-when-task-failover: true
  worker-group-refresh-interval: 10s

worker:
  # worker listener port
  listen-port: 1234
  # worker execute thread number to limit task instances in parallel
  exec-threads: 10
  # worker heartbeat interval
  heartbeat-interval: 10s
  # Worker heart beat task error threshold, if the continuous error count exceed this count, the worker will close.
  heartbeat-error-threshold: 5
  # worker host weight to dispatch tasks, default value 100
  host-weight: 100
  # tenant corresponds to the user of the system, which is used by the worker to submit the job. If system does not have this user, it will be automatically created after the parameter worker.tenant.auto.create is true.
  tenant-auto-create: true
  #Scenes to be used for distributed users.For example,users created by FreeIpa are stored in LDAP.This parameter only applies to Linux, When this parameter is true, worker.tenant.auto.create has no effect and will not automatically create tenants.
  tenant-distributed-user: false
  # worker max cpuload avg, only higher than the system cpu load average, worker server can be dispatched tasks. default value -1: the number of cpu cores * 2
  max-cpu-load-avg: -1
  # worker reserved memory, only lower than system available memory, worker server can be dispatched tasks. default value 0.3, the unit is G
  reserved-memory: 0.3
  # default worker groups separated by comma, like 'worker.groups=default,test'
  groups:
    - default
  # alert server listen host
  alert-listen-host: localhost
  alert-listen-port: 50052
  task-execute-threads-full-policy: REJECT

alert:
  port: 50052
  # Mark each alert of alert server if late after x milliseconds as failed.
  # Define value is (0 = infinite), and alert server would be waiting alert result.
  wait-timeout: 0

python-gateway:
  # Weather enable python gateway server or not. The default value is true.
  enabled: true
  # Authentication token for connection from python api to python gateway server. Should be changed the default value
  # when you deploy in public network.
  auth-token: jwUDzpLsNKEFER4*a8gruBH_GsAurNxU7A@Xc
  # The address of Python gateway server start. Set its value to `0.0.0.0` if your Python API run in different
  # between Python gateway server. It could be be specific to other address like `127.0.0.1` or `localhost`
  gateway-server-address: 0.0.0.0
  # The port of Python gateway server start. Define which port you could connect to Python gateway server from
  # Python API side.
  gateway-server-port: 25333
  # The address of Python callback client.
  python-address: 127.0.0.1
  # The port of Python callback client.
  python-port: 25334
  # Close connection of socket server if no other request accept after x milliseconds. Define value is (0 = infinite),
  # and socket server would never close even though no requests accept
  connect-timeout: 0
  # Close each active connection of socket server if python program not active after x milliseconds. Define value is
  # (0 = infinite), and socket server would never close even though no requests accept
  read-timeout: 0

server:
  port: 12345
  servlet:
    session:
      timeout: 120m
    context-path: /dolphinscheduler/
  compression:
    enabled: true
    mime-types: text/html,text/xml,text/plain,text/css,text/javascript,application/javascript,application/json,application/xml
  jetty:
    max-http-form-post-size: 5000000

management:
  endpoints:
    web:
      exposure:
        include: '*'
  endpoint:
    health:
      enabled: true
      show-details: always
  health:
    db:
      enabled: true
    defaults:
      enabled: false
  metrics:
    tags:
      application: ${spring.application.name}

audit:
  enabled: true

metrics:
  enabled: true

# Override by profile
---
spring:
  config:
    activate:
      on-profile: postgresql
  quartz:
    properties:
      org.quartz.jobStore.driverDelegateClass: org.quartz.impl.jdbcjobstore.PostgreSQLDelegate
  datasource:
    driver-class-name: org.postgresql.Driver
    url: jdbc:postgresql://127.0.0.1:5432/dolphinscheduler
    username: root
    password: root

---
spring:
  config:
    activate:
      on-profile: mysql
  sql:
     init:
       schema-locations: classpath:sql/dolphinscheduler_mysql.sql
  datasource:
    driver-class-name: com.mysql.cj.jdbc.Driver
    url: jdbc:mysql://127.0.0.1:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8
    username: dolphinscheduler
    password: dolphinscheduler

步骤四：初始化数据库

10.配置MySQL驱动

cd /opt/soft/dolphinscheduler
wget https://repo1.maven.org/maven2/mysql/mysql-connector-java/8.0.16/mysql-connector-java-8.0.16.jar -P /tmp
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/worker-server/libs
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/api-server/libs
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/alert-server/libs
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/master-server/libs
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/tools/libs
cp /tmp/mysql-connector-java-8.0.16.jar apache-dolphinscheduler-3.1.4-bin/standalone-server/libs/standalone-server

11.初始化Dolphinscheduler数据库

cd /opt/soft/dolphinscheduler/apache-dolphinscheduler-3.1.4-bin
bash tools/bin/upgrade-schema.sh

出现如下表示成功

步骤五：启动DolphinScheduler

12. 进入bin目录中启动

cd /opt/soft/dolphinscheduler/apache-dolphinscheduler-3.1.4-bin/bin
./dolphinscheduler-daemon.sh start standalone-server

./dolphinscheduler-daemon.sh stop standalone-server