代码拉取完成，页面将自动刷新
同步操作将从 大数据老司机/docker-compose-dolphinscheduler 强制同步，此操作会覆盖自 Fork 仓库以来所做的任何修改，且无法恢复！！！
确定后同步将在后台操作，完成时将刷新页面，请耐心等待。
A permissive license whose main conditions require preservation of copyright and license notices. Contributors provide an express grant of patent rights. Licensed works, modifications, and larger works may be distributed under different terms and without source code.
Apache DolphinScheduler（简称DolphinScheduler）是一种开源的、分布式的、易于使用的大数据工作流调度系统。它旨在为大数据处理提供一个可靠、高效和可扩展的调度解决方案。
这里只讲快速部署，想了解更多可以查阅我这篇文章：Apache DolphinScheduler（海豚调度系统）介绍与环境部署
# 安装yum-config-manager配置工具
yum -y install yum-utils
# 建议使用阿里云yum源：（推荐）
#yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo
yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
# 安装docker-ce版本
yum install -y docker-ce
# 启动并开机启动
systemctl enable --now docker
docker --version
curl -SL https://github.com/docker/compose/releases/download/v2.16.0/docker-compose-linux-x86_64 -o /usr/local/bin/docker-compose
chmod +x /usr/local/bin/docker-compose
docker-compose --version
这里选择docker快速部署的方式：通过 docker-compose 快速部署 MySQL保姆级教程
git clone https://gitee.com/hadoop-bigdata/docker-compose-mysql.git
cd docker-compose-mysql
# create network
docker network create hadoop-network
# 部署
docker-compose -f docker-compose.yaml up -d
# 查看
docker-compose -f docker-compose.yaml ps
# 登录mysql
mysql -uroot -p
# 输入密码：123456
# 创建数据库
create database dolphinscheduler character set utf8 ;
CREATE USER 'dolphinscheduler'@'%'IDENTIFIED BY 'dolphinscheduler@123';
GRANT ALL PRIVILEGES ON dolphinscheduler.* TO 'dolphinscheduler'@'%';
FLUSH PRIVILEGES;
这里选择docker快速部署的方式：【中间件】通过 docker-compose 快速部署 Zookeeper 保姆级教程
git clone https://gitee.com/hadoop-bigdata/docker-compose-zookeeper.git
cd docker-compose-zookeeper
# 部署
docker-compose -f docker-compose.yaml up -d
# 查看
docker-compose -f docker-compose.yaml ps
wget https://dlcdn.apache.org/dolphinscheduler/3.1.7/apache-dolphinscheduler-3.1.7-bin.tar.gz --no-check-certificate
dolphinscheduler/bin/env/install_env.sh#
# 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.
#
# ---------------------------------------------------------
# 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"
# ips=${ips:-"ds1,ds2,ds3,ds4,ds5"}
ips="ds-dolphinscheduler-master-1,ds-dolphinscheduler-master-2,ds-dolphinscheduler-worker-1,ds-dolphinscheduler-worker-2,ds-dolphinscheduler-worker-3,ds-dolphinscheduler-api-1,ds-dolphinscheduler-alert-1"
# Port of SSH protocol, default value is 22. For now we only support same port in all `ips` machine
# modify it if you use different ssh port
sshPort=${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"
# masters=${masters:-"ds1,ds2"}
masters="ds-dolphinscheduler-master-1,ds-dolphinscheduler-master-2"
# A comma separated list of machine <hostname>:<workerGroup> or <IP>:<workerGroup>.All hostname or IP must be a
# subset of configuration `ips`, And workerGroup have default value as `default`, but we recommend you declare behind the hosts
# Example for hostnames: workers="ds1:default,ds2:default,ds3:default", Example for IPs: workers="192.168.8.1:default,192.168.8.2:default,192.168.8.3:default"
# workers=${workers:-"ds1:default,ds2:default,ds3:default,ds4:default,ds5:default"}
workers="ds-dolphinscheduler-worker-1:default,ds-dolphinscheduler-worker-2:default,ds-dolphinscheduler-worker-3: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"
# alertServer=${alertServer:-"ds3"}
alertServer="ds-dolphinscheduler-alert-1"
# A comma separated list of machine hostname or IP would be installed API server, it
# must be a subset of configuration `ips`.
# Example for hostname: apiServers="ds1", Example for IP: apiServers="192.168.8.1"
# apiServers=${apiServers:-"ds1"}
apiServers="ds-dolphinscheduler-api-1"
# 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.
installPath=${installPath:-"/tmp/dolphinscheduler"}
# The user to deploy DolphinScheduler for all machine we config above. For now user must create by yourself before running `install.sh`
# script. The user needs to have sudo privileges and permissions to operate hdfs. If hdfs is enabled than the root directory needs
# to be created by this user
deployUser=${deployUser:-"dolphinscheduler"}
# The root of zookeeper, for now DolphinScheduler default registry server is zookeeper.
zkRoot=${zkRoot:-"/dolphinscheduler"}
dolphinscheduler/bin/env/dolphinscheduler_env.sh#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# JAVA_HOME, will use it to start DolphinScheduler server
# export JAVA_HOME=${JAVA_HOME:-/opt/java/openjdk}
export JAVA_HOME=/opt/apache/jdk1.8.0_212
# Database related configuration, set database type, username and password
# export DATABASE=${DATABASE:-postgresql}
export DATABASE=${DATABASE:-mysql}
export SPRING_PROFILES_ACTIVE=${DATABASE}
export SPRING_DATASOURCE_URL="jdbc:mysql://mysql-test:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8&useSSL=false"
export SPRING_DATASOURCE_USERNAME=dolphinscheduler
export SPRING_DATASOURCE_PASSWORD=dolphinscheduler@123
# DolphinScheduler server related configuration
export SPRING_CACHE_TYPE=${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}
export REGISTRY_ZOOKEEPER_CONNECT_STRING="zookeeper-node1:2181,zookeeper-node2:2181,zookeeper-node3:2181"
# 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:$PATH
【温馨提示】注意: DolphinScheduler 本身不依赖 Hadoop、Hive、Spark，但如果你运行的任务需要依赖他们，就需要有对应的环境支持。这里暂不添加这些依赖，如有需求的小伙伴，可以关注我公众号：
大数据与云原生技术分享联系到我。
dolphinscheduler/master-server/bin/start.shBIN_DIR=$(dirname $0)
DOLPHINSCHEDULER_HOME=${DOLPHINSCHEDULER_HOME:-$(cd $BIN_DIR/..; pwd)}
source "$DOLPHINSCHEDULER_HOME/conf/dolphinscheduler_env.sh"
JAVA_OPTS=${JAVA_OPTS:-"-server -Duser.timezone=${SPRING_JACKSON_TIME_ZONE} -Xms1g -Xmx1g -Xmn1g -XX:+PrintGCDetails -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dump.hprof"}
if [[ "$DOCKER" == "true" ]]; then
JAVA_OPTS="${JAVA_OPTS} -XX:-UseContainerSupport"
fi
$JAVA_HOME/bin/java $JAVA_OPTS \
-cp "$DOLPHINSCHEDULER_HOME/conf":"$DOLPHINSCHEDULER_HOME/libs/*" \
org.apache.dolphinscheduler.server.master.MasterServer
dolphinscheduler/api-server/bin/start.shBIN_DIR=$(dirname $0)
DOLPHINSCHEDULER_HOME=${DOLPHINSCHEDULER_HOME:-$(cd $BIN_DIR/..; pwd)}
source "$DOLPHINSCHEDULER_HOME/conf/dolphinscheduler_env.sh"
JAVA_OPTS=${JAVA_OPTS:-"-server -Duser.timezone=${SPRING_JACKSON_TIME_ZONE} -Xms1g -Xmx1g -Xmn512m -XX:+PrintGCDetails -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dump.hprof"}
if [[ "$DOCKER" == "true" ]]; then
JAVA_OPTS="${JAVA_OPTS} -XX:-UseContainerSupport"
fi
$JAVA_HOME/bin/java $JAVA_OPTS \
-cp "$DOLPHINSCHEDULER_HOME/conf":"$DOLPHINSCHEDULER_HOME/libs/*" \
org.apache.dolphinscheduler.api.ApiApplicationServer
dolphinscheduler/alert-server/bin/start.shBIN_DIR=$(dirname $0)
DOLPHINSCHEDULER_HOME=${DOLPHINSCHEDULER_HOME:-$(cd $BIN_DIR/..; pwd)}
source "$DOLPHINSCHEDULER_HOME/conf/dolphinscheduler_env.sh"
JAVA_OPTS=${JAVA_OPTS:-"-server -Duser.timezone=${SPRING_JACKSON_TIME_ZONE} -Xms1g -Xmx1g -Xmn512m -XX:+PrintGCDetails -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dump.hprof"}
if [[ "$DOCKER" == "true" ]]; then
JAVA_OPTS="${JAVA_OPTS} -XX:-UseContainerSupport"
fi
$JAVA_HOME/bin/java $JAVA_OPTS \
-cp "$DOLPHINSCHEDULER_HOME/conf":"$DOLPHINSCHEDULER_HOME/libs/*" \
org.apache.dolphinscheduler.api.ApiApplicationServer
[root@local-168-182-110 docker-compose-mysql]# cat ../dolphinscheduler/apache-dolphinscheduler-3.1.7-bin/alert-server/bin/start.sh|grep -v '#'
BIN_DIR=$(dirname $0)
DOLPHINSCHEDULER_HOME=${DOLPHINSCHEDULER_HOME:-$(cd $BIN_DIR/..; pwd)}
source "$DOLPHINSCHEDULER_HOME/conf/dolphinscheduler_env.sh"
JAVA_OPTS=${JAVA_OPTS:-"-server -Duser.timezone=${SPRING_JACKSON_TIME_ZONE} -Xms1g -Xmx1g -Xmn512m -XX:+PrintGCDetails -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dump.hprof"}
if [[ "$DOCKER" == "true" ]]; then
JAVA_OPTS="${JAVA_OPTS} -XX:-UseContainerSupport"
fi
$JAVA_HOME/bin/java $JAVA_OPTS \
-cp "$DOLPHINSCHEDULER_HOME/conf":"$DOLPHINSCHEDULER_HOME/libs/*" \
org.apache.dolphinscheduler.alert.AlertServer
dolphinscheduler/worker-server/bin/start.shBIN_DIR=$(dirname $0)
DOLPHINSCHEDULER_HOME=${DOLPHINSCHEDULER_HOME:-$(cd $BIN_DIR/..; pwd)}
source "$DOLPHINSCHEDULER_HOME/conf/dolphinscheduler_env.sh"
export DOLPHINSCHEDULER_WORK_HOME=${DOLPHINSCHEDULER_HOME}
JAVA_OPTS=${JAVA_OPTS:-"-server -Duser.timezone=${SPRING_JACKSON_TIME_ZONE} -Xms1g -Xmx1g -Xmn2g -XX:+PrintGCDetails -Xloggc:gc.log -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=dump.hprof"}
if [[ "$DOCKER" == "true" ]]; then
JAVA_OPTS="${JAVA_OPTS} -XX:-UseContainerSupport"
fi
$JAVA_HOME/bin/java $JAVA_OPTS \
-cp "$DOLPHINSCHEDULER_HOME/conf":"$DOLPHINSCHEDULER_HOME/libs/*" \
org.apache.dolphinscheduler.server.worker.WorkerServer
wget https://repo1.maven.org/maven2/mysql/mysql-connector-java/8.0.16/mysql-connector-java-8.0.16.jar
#!/usr/bin/env sh
wait_for() {
echo Waiting for $1 to listen on $2...
while ! nc -z $1 $2; do echo waiting...; sleep 1s; done
}
startDolphinScheduler() {
node_type=$1
if [ "$node_type" = "master" ];then
bash ${DolphinScheduler_HOME}/bin/dolphinscheduler-daemon.sh start master-server
# 查看日志
tail -f ${DolphinScheduler_HOME}/master-server/logs/dolphinscheduler-master.log
elif [ "$node_type" = "api" ];then
wait_for $2 $3
bash ${DolphinScheduler_HOME}//bin/dolphinscheduler-daemon.sh start api-server
# 查看日志
tail -f ${DolphinScheduler_HOME}/api-server/logs/dolphinscheduler-api.log
elif [ "$node_type" = "alert" ];then
wait_for $2 $3
bash ${DolphinScheduler_HOME}//bin/dolphinscheduler-daemon.sh start alert-server
# 查看日志
tail -f ${DolphinScheduler_HOME}/alert-server/logs/dolphinscheduler-alert.log
elif [ "$node_type" = "worker" ];then
wait_for $2 $3
bash ${DolphinScheduler_HOME}//bin/dolphinscheduler-daemon.sh start worker-server
# 查看日志
tail -f ${DolphinScheduler_HOME}/worker-server/logs/dolphinscheduler-worker.log
fi
}
# 初始化数据库
bash ${DolphinScheduler_HOME}/tools/bin/upgrade-schema.sh
startDolphinScheduler $@
FROM registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/centos-jdk:7.7.1908
ADD apache-dolphinscheduler-3.1.7-bin.tar.gz /opt/apache
# 添加 DolphinScheduler 包
ENV DolphinScheduler_VERSION 3.1.7
ADD apache-dolphinscheduler-${DolphinScheduler_VERSION}-bin.tar.gz /opt/apache/
ENV DolphinScheduler_HOME /opt/apache/dolphinscheduler
RUN ln -s /opt/apache/apache-dolphinscheduler-${DolphinScheduler_VERSION}-bin $DolphinScheduler_HOME
# 添加MySQL 驱动
COPY mysql-connector-java-8.0.16.jar ${DolphinScheduler_HOME}/tools/libs/
COPY mysql-connector-java-8.0.16.jar ${DolphinScheduler_HOME}/master-server/libs/
COPY mysql-connector-java-8.0.16.jar ${DolphinScheduler_HOME}/worker-server/libs/
COPY mysql-connector-java-8.0.16.jar ${DolphinScheduler_HOME}/alert-server/libs/
COPY mysql-connector-java-8.0.16.jar ${DolphinScheduler_HOME}/api-server/libs/
# copy bootstrap.sh
COPY bootstrap.sh /opt/apache/
RUN chmod +x /opt/apache/bootstrap.sh
WORKDIR /opt/apache
开始构建镜像
docker build -t registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7 . --no-cache --progress=plain
# 为了方便小伙伴下载即可使用，我这里将镜像文件推送到阿里云的镜像仓库
docker push registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7
### 参数解释
# -t：指定镜像名称
# . ：当前目录Dockerfile
# -f：指定Dockerfile路径
# --no-cache：不缓存
version: '3'
services:
dolphinscheduler-master:
image: registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7
user: "hadoop:hadoop"
restart: always
privileged: true
env_file:
- .env
volumes:
- ./dolphinscheduler/bin/env/install_env.sh:${DolphinScheduler_HOME}/bin/env/install_env.sh
- ./dolphinscheduler/bin/env/dolphinscheduler_env.sh:${DolphinScheduler_HOME}/bin/env/dolphinscheduler_env.sh
- ./dolphinscheduler/master-server/bin/start.sh:${DolphinScheduler_HOME}/master-server/bin/start.sh
- ./dolphinscheduler/worker-server/bin/start.sh:${DolphinScheduler_HOME}/worker-server/bin/start.sh
- ./dolphinscheduler/alert-server/bin/start.sh:${DolphinScheduler_HOME}/alert-server/bin/start.sh
- ./dolphinscheduler/api-server/bin/start.sh:${DolphinScheduler_HOME}/api-server/bin/start.sh
expose:
- "${DolphinScheduler_MASTER_PORT}"
deploy:
replicas: 2
command: ["sh","-c","/opt/apache/bootstrap.sh master"]
networks:
- hadoop-network
healthcheck:
test: ["CMD-SHELL", "netstat -tnlp|grep :${DolphinScheduler_MASTER_PORT} || exit 1"]
interval: 15s
timeout: 15s
retries: 5
dolphinscheduler-worker:
image: registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7
user: "hadoop:hadoop"
restart: always
privileged: true
env_file:
- .env
volumes:
- ./dolphinscheduler/bin/env/install_env.sh:${DolphinScheduler_HOME}/bin/env/install_env.sh
- ./dolphinscheduler/bin/env/dolphinscheduler_env.sh:${DolphinScheduler_HOME}/bin/env/dolphinscheduler_env.sh
- ./dolphinscheduler/master-server/bin/start.sh:${DolphinScheduler_HOME}/master-server/bin/start.sh
- ./dolphinscheduler/worker-server/bin/start.sh:${DolphinScheduler_HOME}/worker-server/bin/start.sh
- ./dolphinscheduler/alert-server/bin/start.sh:${DolphinScheduler_HOME}/alert-server/bin/start.sh
- ./dolphinscheduler/api-server/bin/start.sh:${DolphinScheduler_HOME}/api-server/bin/start.sh
expose:
- "${DolphinScheduler_WORKER_PORT}"
deploy:
replicas: 3
command: ["sh","-c","/opt/apache/bootstrap.sh worker ds-dolphinscheduler-master-1 ${DolphinScheduler_MASTER_PORT}"]
networks:
- hadoop-network
healthcheck:
test: ["CMD-SHELL", "netstat -tnlp|grep :${DolphinScheduler_WORKER_PORT} || exit 1"]
interval: 15s
timeout: 15s
retries: 5
dolphinscheduler-api:
image: registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7
user: "hadoop:hadoop"
restart: always
privileged: true
env_file:
- .env
volumes:
- ./dolphinscheduler/bin/env/install_env.sh:${DolphinScheduler_HOME}/bin/env/install_env.sh
- ./dolphinscheduler/bin/env/dolphinscheduler_env.sh:${DolphinScheduler_HOME}/bin/env/dolphinscheduler_env.sh
- ./dolphinscheduler/master-server/bin/start.sh:${DolphinScheduler_HOME}/master-server/bin/start.sh
- ./dolphinscheduler/worker-server/bin/start.sh:${DolphinScheduler_HOME}/worker-server/bin/start.sh
- ./dolphinscheduler/alert-server/bin/start.sh:${DolphinScheduler_HOME}/alert-server/bin/start.sh
- ./dolphinscheduler/api-server/bin/start.sh:${DolphinScheduler_HOME}/api-server/bin/start.sh
ports:
- "${DolphinScheduler_API_PORT}"
deploy:
replicas: 1
command: ["sh","-c","/opt/apache/bootstrap.sh api ds-dolphinscheduler-master-1 ${DolphinScheduler_MASTER_PORT}"]
networks:
- hadoop-network
healthcheck:
test: ["CMD-SHELL", "netstat -tnlp|grep :${DolphinScheduler_API_PORT} || exit 1"]
interval: 15s
timeout: 15s
retries: 5
dolphinscheduler-alert:
image: registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/dolphinscheduler:3.1.7
user: "hadoop:hadoop"
restart: always
privileged: true
env_file:
- .env
volumes:
- ./dolphinscheduler/bin/env/install_env.sh:${DolphinScheduler_HOME}/bin/env/install_env.sh
- ./dolphinscheduler/bin/env/dolphinscheduler_env.sh:${DolphinScheduler_HOME}/bin/env/dolphinscheduler_env.sh
- ./dolphinscheduler/master-server/bin/start.sh:${DolphinScheduler_HOME}/master-server/bin/start.sh
- ./dolphinscheduler/worker-server/bin/start.sh:${DolphinScheduler_HOME}/worker-server/bin/start.sh
- ./dolphinscheduler/alert-server/bin/start.sh:${DolphinScheduler_HOME}/alert-server/bin/start.sh
- ./dolphinscheduler/api-server/bin/start.sh:${DolphinScheduler_HOME}/api-server/bin/start.sh
expose:
- "${DolphinScheduler_ALERT_PORT}"
deploy:
replicas: 1
command: ["sh","-c","/opt/apache/bootstrap.sh alert ds-dolphinscheduler-master-1 ${DolphinScheduler_MASTER_PORT}"]
networks:
- hadoop-network
healthcheck:
test: ["CMD-SHELL", "netstat -tnlp|grep :${DolphinScheduler_ALERT_PORT} || exit 1"]
interval: 10s
timeout: 10s
retries: 5
# 连接外部网络
networks:
hadoop-network:
external: true
.env 文件内容：
DolphinScheduler_HOME=/opt/apache/dolphinscheduler
DolphinScheduler_MASTER_PORT=5678
DolphinScheduler_WORKER_PORT=1234
DolphinScheduler_API_PORT=12345
DolphinScheduler_ALERT_PORT=50052
# p=sr：项目名，默认项目名是当前目录名称
docker-compose -f docker-compose.yaml -p=ds up -d
# 查看
docker-compose -f docker-compose.yaml -p=ds ps
# 卸载
docker-compose -f docker-compose.yaml -p=ds down
# http://<your_ip>:12345/dolphinscheduler/ui/login
# 这里的端口是api 对外的端口，可以通过命令获取对外端口，docker-compose -f docker-compose.yaml -p=ds down
http://192.168.182.110:32770/dolphinscheduler/ui/login
默认账户密码：admin/dolphinscheduler123
# 初始化数据库
bash ${DolphinScheduler_HOME}/tools/bin/upgrade-schema.sh
# 启停 Master
bash ./bin/dolphinscheduler-daemon.sh start master-server
# 查看日志
tail -f master-server/logs/dolphinscheduler-master.log
# bash ./bin/dolphinscheduler-daemon.sh stop master-server
# 启停 Api
bash ./bin/dolphinscheduler-daemon.sh start api-server
# 查看日志
tail -f api-server/logs/dolphinscheduler-api.log
# bash ./bin/dolphinscheduler-daemon.sh stop api-server
# 启停 Alert
bash ./bin/dolphinscheduler-daemon.sh start alert-server
# 查看日志
tail -f alert-server/logs/dolphinscheduler-alert.log
# bash ./bin/dolphinscheduler-daemon.sh stop alert-server
# 启停 Worker
bash ./bin/dolphinscheduler-daemon.sh start worker-server
# 查看日志
tail -f worker-server/logs/dolphinscheduler-worker.log
# bash ./bin/dolphinscheduler-daemon.sh stop worker-server
这里没有添加hadoop等组件的依赖包，如有需要用到大数据组件依赖包，则可以在我的镜像基础之上添加依赖包即可，如有任何问题可以关注我公众号：大数据与云原生技术分享 来咨询问题，如本篇文章对您有所帮助，麻烦帮忙一键三连（点赞、转发、收藏）~
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