Docker-compose教程（安装，使用，快速入门）

一、Docker-Compose概述

    Compose 项目是 Docker 官方的开源项目，负责实现对 Docker 容器集群的快速编排。使用前面介绍的Dockerfile我们很容易定义一个单独的应用容器。然而在日常开发工作中，经常会碰到需要多个容器相互配合来完成某项任务的情况。例如要实现一个 Web 项目，除了 Web 服务容器本身，往往还需要再加上后端的数据库服务容器；再比如在分布式应用一般包含若干个服务，每个服务一般都会部署多个实例。如果每个服务都要手动启停，那么效率之低、维护量之大可想而知。这时候就需要一个工具能够管理一组相关联的的应用容器，这就是Docker Compose。

Compose有2个重要的概念：

项目（Project）：由一组关联的应用容器组成的一个完整业务单元，在 docker-compose.yml 文件中定义。

服务（Service）：一个应用的容器，实际上可以包括若干运行相同镜像的容器实例。

   docker compose运行目录下的所有yml文件组成一个工程，一个工程包含多个服务，每个服务中定义了容器运行的镜像、参数、依赖。一个服务可包括多个容器实例。docker-compose就是docker容器的编排工具，主要就是解决相互有依赖关系的多个容器的管理。

二、安装docker-compose

1.从github上下载docker-compose二进制文件安装

下载最新版的docker-compose文件

官方文档地址：Install Docker Compose | Docker Documentation

https://github.com/docker/compose/releases/download/v2.5.0/docker-compose-linux-x86_64

添加可执行权限

[root@offline-client bin]# mv docker-compose-linux-x86_64 docker-compose
[root@offline-client bin]# docker-compose version
Docker Compose version v2.5.0

2.pip安装

pip install docker-compose

三、Docker-compose实战

1.MySQL示例

1.1 MySQL run

docker run -itd -p 3306:3306 -m="1024M" --privileged=true
-v /data/software/mysql/conf/:/etc/mysql/conf.d
-v /data/software/mysql/data:/var/lib/mysql
-v /data/software/mysql/log/:/var/log/mysql/
-e MYSQL_ROOT_PASSWORD=winner@001 --name=mysql mysql:5.7.19

1.2 mysql-compose.yml

version: "3"
services:
  mysql:
    image: mysql:5.7.19
    restart: always
    container_name: mysql
    ports:
      - 3306:3306
    volumes:
      - /data/software/mysql/conf/:/etc/mysql/conf.d
      - /data/software/mysql/data:/var/lib/mysql
      - /data/software/mysql/log/:/var/log/mysql
    environment:
      MYSQL_ROOT_PASSWORD: 123456
      MYSQL_DATABASE: kangll
      MYSQL_USER: kangll
      MYSQL_PASSWORD: 123456

MySQL 容器启动与关闭

[root@offline-client software]# docker-compose -f docker-compose-mysql.yml down
[root@offline-client software]# docker-compose -f docker-compose-mysql.yml up -d

docker ps 查看MySQL进程

2.CDH单机

2.1系统镜像DockerFile

FROM ubuntu:20.04

# 作者信息
LABEL  kangll <[email protected]>

# 安装 依赖包
RUN apt-get clean && apt-get -y update \ 
&&  apt-get install -y openssh-server  lrzsz vim net-tools openssl gcc openssh-client inetutils-ping \
&&  sed -ri 's/^#?PermitRootLogin\s+.*/PermitRootLogin yes/' /etc/ssh/sshd_config \
&&  sed -ri 's/UsePAM yes/#UsePAM yes/g' /etc/ssh/sshd_config \
&&  ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime \
# 修改 root 密码
&&  useradd  winner \
&&  echo "root:kangll" | chpasswd \
&&  echo "winner:kangll" | chpasswd \
&&  echo "root   ALL=(ALL)       ALL" >> /etc/sudoers \
&&  echo "winner   ALL=(ALL)       ALL" >> /etc/sudoers 
# 生成密钥
#&&  ssh-keygen -t dsa -f /etc/ssh/ssh_host_dsa_key \
#&&  ssh-keygen -t rsa -f /etc/ssh/ssh_host_rsa_key

# 启动sshd服务并且暴露22端口  
RUN mkdir /var/run/sshd
EXPOSE 22
# 执行后台启动 ssh 服务命令
CMD ["/usr/sbin/sshd", "-D"]

2.2CDH镜像DockerFile

FROM ubuntu20-ssh-base:v1.0   # 系统镜像

LABEL  kangll <[email protected]>

RUN ssh-keygen -t rsa -f ~/.ssh/id_rsa -P '' && \
    cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys && \
    sed -i 's/PermitEmptyPasswords yes/PermitEmptyPasswords no /' /etc/ssh/sshd_config  && \
    sed -i 's/PermitRootLogin without-password/PermitRootLogin yes /' /etc/ssh/sshd_config && \
    echo " StrictHostKeyChecking no" >> /etc/ssh/ssh_config && \
    echo " UserKnownHostsFile /dev/null" >> /etc/ssh/ssh_config 

# JDK 
ADD jdk-8u162-linux-x64.tar.gz /hadoop/software/
ENV JAVA_HOME=/hadoop/software/jdk1.8.0_162
ENV CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
ENV PATH=$JAVA_HOME/bin:$PATH

# hadoop
ADD hadoop-2.6.0-cdh5.15.0.tar.gz /hadoop/software/
ENV HADOOP_HOME=/hadoop/software/hadoop
ENV HADOOP_CONF_DIR=/hadoop/software/hadoop/etc/hadoop
ENV PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

# spark
ADD spark-1.6.0-cdh5.15.0.tar.gz /hadoop/software/
ENV SPARK_HOME=/hadoop/software/spark
ENV PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin

# hbase
ADD hbase-1.2.0-cdh5.15.0.tar.gz  /hadoop/software/
ENV HBASE_HOME=/hadoop/software/hbase
ENV PATH=$PATH:$HBASE_HOME/bin

# hive
ADD hive-1.1.0-cdh5.15.0.tar.gz /hadoop/software/
ENV HIVE_HOME=/hadoop/software/hive
ENV HIVE_CONF_DIR=/hadoop/software/hive/conf
ENV PATH=$HIVE_HOME/bin:$PATH

# scala
ADD scala-2.10.5.tar.gz /hadoop/software/
ENV SCALA_HOME=/hadoop/software/scala
ENV PATH=$PATH:$SCALA_HOME/bin

ADD azkaban.3.30.1.tar.gz /hadoop/software/

WORKDIR /hadoop/software/
RUN ln -s jdk1.8.0_162 jdk \
&& ln -s spark-1.6.0-cdh5.15.0 spark \
&& ln -s scala-2.10.5 scala  \
&& ln -s hadoop-2.6.0-cdh5.15.0 hadoop \
&& ln -s hbase-1.2.0-cdh5.15.0 hbase \ 
&& ln -s hive-1.1.0-cdh5.15.0 hive

WORKDIR /hadoop/software/hadoop/share/hadoop
RUN ln -s mapreduce2 mapreduce

WORKDIR /hadoop/software/

# 添加winner用户
RUN chown -R winner:winner /hadoop/software/ && \
    chmod -R +x  /hadoop/software/ 

## 集群启动脚本
COPY  start-cluster.sh  /bin/
RUN chmod +x /bin/start-cluster.sh

CMD ["bash","-c","/bin/start-cluster.sh && tail -f /dev/null"]

start-cluster脚本，方便多次启动和在log中查看启动日志

#!/bin/bash
#########################################################################
#                                                                     #
# 脚本功能: winner-aio-docker, docker-compose安装,环境初始化          #
# 作    者: kangll                                                    #
# 创建时间: 2022-02-28                                                #
# 修改时间: 2022-04-07                                                #
# 当前版本: 2.0v                                                      #
# 调度周期: 初始化任务执行一次                                        #
# 脚本参数: 无                                                        #
##########################################################################

source /etc/profile
source ~/.bash_profile
set -e
rm -rf /tmp/*

### 判断NameNode初始化文件夹是否存在,决定是否格式化
NNPath=/hadoop/software/hadoop/data/dfs/name/current
if [ -d "$NNPath" ];then
     echo "------------------------------------------> NameNode已格式化 <--------------------------------------"
else
     echo "------------------------------------------> NameNode开始格式化 <------------------------------------"
     /hadoop/software/hadoop/bin/hdfs namenode -format
fi

# NameNode, SecondaryNameNode monitor
namenodeCount=`ps -ef |grep NameNode |grep -v "grep" |wc -l`
if [ $namenodeCount -le 1 ];then
      /usr/sbin/sshd 
      echo "-----------------------------------------> Namenode 启动 <---------------------------------------- "
      start-dfs.sh
else
      echo "----------------------------> Namenode, SecondaryNameNode 正常 <---------------------------------- "
fi

#DataNode
DataNodeCount=`ps -ef |grep DataNode |grep -v "grep" |wc -l`
if [ $DataNodeCount == 0 ];then
       /usr/sbin/sshd
       echo "-------------------------------------> DataNode 启动 <-------------------------------------------"
       start-dfs.sh
else
       echo "-------------------------------------> DataNode 正常 <-------------------------------------------"
fi

#HBase Monitor
hmasterCount=`ps -ef |grep HMaster |grep -v "grep" |wc -l`
if [ $hmasterCount == 0 ];then
         /usr/sbin/sshd
       echo "-------------------------------------> hmaster  启动 <-------------------------------------------"
     start-hbase.sh
else
       echo "-------------------------------------> hmaster  正常 <-------------------------------------------"
fi

#HBase  RegionServer Monitor
regionCount=`ps -ef |grep HRegionServer |grep -v "grep" |wc -l`
if [ $regionCount == 0 ];then
       echo "--------------------------------------> RegionServer 启动 <---------------------------------------"
       /usr/sbin/sshd
    start-hbase.sh
else
       echo "--------------------------------------> RegionServer 正常 <---------------------------------------"
fi

#yarn  ResourceManager
ResourceManagerCount=`ps -ef |grep ResourceManager |grep -v "grep" |wc -l`
if [ $ResourceManagerCount == 0 ];then
         /usr/sbin/sshd
        echo "-------------------------------------> ResourceManager 启动 <------------------------------------"
     start-yarn.sh
else
        echo "-------------------------------------> ResourceManager 正常 <------------------------------------"
fi

#yarn  NodeManager
NodeManagerCount=`ps -ef |grep NodeManager |grep -v "grep" |wc -l`
if [ $NodeManagerCount == 0 ];then
         /usr/sbin/sshd
        echo "-------------------------------------> NodeManager 启动 <-----------------------------------------"
     start-yarn.sh
else
    echo "-------------------------------------> NodeManager 正常 <-----------------------------------------"
fi

#hive 
runJar=`ps -ef |grep RunJar |grep -v "grep" |wc -l`
if [ $runJar == 0 ];then
         /usr/sbin/sshd
        echo "-----------------------------------------> hive 启动 <-----------------------------------------"
         hive --service metastore &
else
        echo "------------------------------------------> hive 正常 <-----------------------------------------"
fi

2.3镜像构建

[root@offline-client winner-aio]# ll
total 1147020
-rw-r--r-- 1 root root       906 May 21 17:24 dockerfile-centos
-rw-r--r-- 1 root root      1700 May 20 18:44 dockerfile-hadoop
-rw-r--r-- 1 root root        42 May 18 16:23 dockerfile-mysql5.7
-rw-r--r-- 1 root root       971 May 19 15:00 dockerfile-ubuntu
-rw-r--r-- 1 root root 433428169 May 20 10:15 hadoop-2.6.0-cdh5.15.0.tar.gz
-rw-r--r-- 1 root root 266421606 May 20 10:15 hbase-1.2.0-cdh5.15.0.tar.gz
-rw-r--r-- 1 root root 129551278 May 20 10:15 hive-1.1.0-cdh5.15.0.tar.gz
-rw-r--r-- 1 root root 189815615 May 16 11:10 jdk-8u162-linux-x64.tar.gz
## 镜像构建
docker build -f dockerfile-ubuntu -t ubuntu22-ssh-base:v1.0  .
docker build -f dockerfile-hadoop -t hadoop-2.6.0-cdh5.15:v1.0  .

镜像结果输出

2.4桥接网络创建

docker network create  -d bridge hadoop-network

2.5CDH-yml

version: "3"
services:
  cdh:
    image: hadoop-cluster:v1.0
    container_name: hadoop-cluster
    hostname: hadoop
    networks:
      - hadoop-network
    ports:
      - 9000:9000
      - 8088:8088
      - 50070:50070 
      - 8188:8188
      - 8042:8042
      - 10000:10000 
      - 9083:9083
      - 8080:8080
      - 7077:7077
      - 8444:8444
    # 数据与日志路径映射到本地数据盘
    volumes:
      - /data/software/hadoop/data:/hadoop/software/hadoop/data
      - /data/software/hadoop/logs:/hadoop/software/hadoop/logs
      - /data/software/hadoop/conf:/hadoop/software/hadoop/etc/hadoop
      - /data/software/hbase/conf:/hadoop/software/hbase/conf
      - /data/software/hbase/logs:/hadoop/software/hbase/logs
      - /data/software/hive/conf:/hadoop/software/hive/conf  
networks:
  hadoop-network: {}

2.6CDH 启动

docker-compose  -f dockerfile-hadoop-cluster  up -d

使用JPS查看服务进程

访问hadoop-web

访问yarn-web

------------------------ 感谢点赞！-------------------------------------

标签： docker 容器运维

本文转载自: https://blog.csdn.net/qq_35995514/article/details/125468792
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Docker-compose教程（安装，使用，快速入门）

一、Docker-Compose概述

二、安装docker-compose

1.从github上下载docker-compose二进制文件安装

2.pip安装

三、Docker-compose实战

1.MySQL示例

1.1 MySQL run

1.2 mysql-compose.yml

2.CDH单机

2.1系统镜像DockerFile

2.2CDH镜像DockerFile

2.3镜像构建

2.4桥接网络创建

2.5CDH-yml

2.6CDH 启动

------------------------ 感谢点赞！-------------------------------------

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“Docker-compose教程（安装，使用，快速入门）”的评论:

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文章导航

Docker-compose教程（安装，使用， 快速入门）

一、Docker-Compose概述

二、安装docker-compose

1.从github上下载docker-compose二进制文件安装

2.pip安装

三、Docker-compose实战

1.MySQL示例

1.1 MySQL run

1.2 mysql-compose.yml

2.CDH单机

2.1系统镜像DockerFile

2.2CDH镜像DockerFile

2.3镜像构建

2.4桥接网络创建

2.5CDH-yml

2.6CDH 启动

------------------------ 感谢点赞！-------------------------------------

发表评论

“Docker-compose教程（安装，使用， 快速入门）”的评论:

关于作者

overfit同步小助手

相关阅读

文章导航

Docker-compose教程（安装，使用，快速入门）

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