Docker-經常使用基建的安裝與部署

時間 2021-01-20

標籤 mysql linux c++ git github sql docker shell 數據庫 json 欄目 Docker 简体版

原文原文鏈接

一：Docker安裝

　　1：經過yum安裝dockermysql

yum -y install gcc
yum -y install gcc-c++
yum remove docker \
                  docker-client \
                  docker-client-latest \
                  docker-common \
                  docker-latest \
                  docker-latest-logrotate \
                  docker-logrotate \
                  docker-engine
yum install -y yum-utils device-mapper-persistent-data lvm2
yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo
yum list docker-ce --showduplicates | sort -r
yum -y install docker-ce-18.06.3.ce

2：爲docker設置源linux

vim /etc/docker/daemon.json

{
  "registry-mirrors": ["https://r5yuqwmu.mirror.aliyuncs.com"],
  "data-root": "/home/data/docker",
  "log-driver": "json-file",
  "log-opts": {"max-size":"50m", "max-file":"1"}
}

啓動docker：systemctl start dockerc++

二：docker鏡像

https://docs.docker.com/engine/git

獲取docker鏡像的兩種方式：（以mysql爲例）github

1：docker pull mysql:5.7 sql

從dockerhub中去拉取網上公開的可用的鏡像，能夠本身去搜索本身想要的：https://hub.docker.com/search?q=&type=image&category=databasedocker

2：docker build -t mysql_self .shell

自定義Dockerfile，能夠基於公開的鏡像，自定義本身的鏡像。數據庫

#基礎鏡像使用 mysql:5.7
FROM mysql:5.7

#做者
MAINTAINER author

ENV WORK_PATH /usr/local/work

#定義會被容器自動執行的目錄
ENV AUTO_RUN_DIR /docker-entrypoint-initdb.d

#定義sql文件名
ENV FILE_0 myself.sql
ENV LANG en_GB.utf8

#配置文件複製進去
COPY my.cnf /etc

RUN yes|cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime

#定義shell文件名
ENV INSTALL_DB_SHELL install_db.sh

#建立文件夾
RUN mkdir -p $WORK_PATH

#把數據庫初始化數據的文件複製到工做目錄下
COPY ./$FILE_0 $WORK_PATH/

#把要執行的shell文件放到/docker-entrypoint-initdb.d/目錄下，容器會自動執行這個shell
COPY ./$INSTALL_DB_SHELL $AUTO_RUN_DIR/
WORKDIR $WORK_PATH


#給執行文件增長可執行權限
RUN chmod a+x $AUTO_RUN_DIR/$INSTALL_DB_SHELL

三：docker容器

當鏡像都下載完成後，就能夠建立docker容器並運行使用，下面就以實例測試mysql、canal、kafka和zookeeper這幾個基建的部署。json

# 建立自定義network
docker network create --subnet=172.18.0.0/16 mynetwork

docker run options 能夠參考：https://docs.docker.com/engine/reference/commandline/run/

1：運行mysql容器

docker run -p 3306:3306 --name mysql_self --net mynetwork --ip 172.18.0.36  -v /home/data/docker/mysql/logs:/logs -v /home/data/docker/mysql/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=Abcd12345 -d --restart=always mysql_self:latest

2：canal

docker run -d --name canal -p 11111:11111 --net mynetwork --ip 172.18.0.41 -e canal.destinations=self -e canal.instance.mysql.slaveId=12 -e  canal.auto.scan=false -e canal.instance.master.address=172.18.0.36:3306 -e canal.instance.dbUsername=canal -e canal.instance.dbPassword=canal -e  canal.instance.filter.regex=esen_approval.apt_approval --restart=always canal/canal-server:v1.1.4

canal要想搭配好mysql，其中有幾點須要注意；
1：canal.instance.master.address的地址必須指向mysql容器的ip和port

2：canal.instance.mysql.slaveId 不能與mysql的一致，mysql的log_bin要開啓，查看命令爲：show variables like 'log_bin'

3：canal.instance.dbUsername和canal.instance.dbPassword 要在啓動前設置好。

3：zookeeper

docker run -d --name zookeeper -p 2181:2181 --net mynetwork --ip 172.18.0.37 -v /home/data/docker/zookeeper/logs:/datalog -v /home/data/docker/zookeeper/data:/data --restart=always -t  zookeeper:3.4.14

4：kafka

docker run -d --name kafka -p 9092:9092 -p 19092:19092 --net mynetwork --ip 172.18.0.38  -e KAFKA_BROKER_ID=0 -e KAFKA_ZOOKEEPER_CONNECT=172.18.0.37:2181 -e KAFKA_INTER_BROKER_LISTENER_NAME=INTERNAL -e KAFKA_LISTENER_SECURITY_PROTOCOL_MAP=INTERNAL:PLAINTEXT,EXTERNAL:PLAINTEXT -e KAFKA_ADVERTISED_LISTENERS=INTERNAL://172.18.0.38:19092,EXTERNAL://外網IP:9092 -e KAFKA_LISTENERS=INTERNAL://0.0.0.0:19092,EXTERNAL://0.0.0.0:9092 --restart=always -t wurstmeister/kafka

四：docker-compose

1：docker-compose安裝

sudo curl -L "https://get.daocloud.io/docker/compose/releases/download/1.26.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo curl -L "https://github.com/docker/compose/releases/download/1.26.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
chmod +x /usr/local/bin/docker-compose

docker-compose file 和docker版本之間的對照關係：https://docs.docker.com/compose/compose-file/

2：docker-compose.yml

version: '3.7'
services:
  mysql_hermes:
    build: /root/data/docker/mysql/mysql_hermes
    container_name: mysql_hermes
    environment:
      - "MYSQL_ROOT_PASSWORD=Abcd12345"
    ports:
      - "3306:3306"
    restart: always
    volumes:
        - "/root/data/docker/mysql/logs:/logs"
        - "/root/data/docker/mysql/data:/var/lib/mysql"
  zookeeper:
    image: zookeeper:3.4.14
    container_name: zookeeper
    restart: always
    hostname: zookeeper
    ports:
      - 2181:2181
    volumes:
      - /root/data/docker/zookeeper/logs:/datalog
      - /root/data/docker/zookeeper/data:/data
    networks: 
        default:
            ipv4_address: 172.18.0.37
  kafka:
    image: wurstmeister/kafka:latest
    container_name: kafka
    restart: always
    ports:
      - 9092:9092
      - 19092:19092
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: 172.18.0.37:2181
      KAFKA_INTER_BROKER_LISTENER_NAME: INTERNAL
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: INTERNAL:PLAINTEXT,EXTERNAL:PLAINTEXT
      KAFKA_ADVERTISED_LISTENERS: INTERNAL://172.18.0.38:19092,EXTERNAL://47.99.72.114:9092
      KAFKA_LISTENERS: INTERNAL://0.0.0.0:19092,EXTERNAL://0.0.0.0:9092
    volumes:
      - /root/data/docker/kafka/data:/kafka
    depends_on:
      - zookeeper
    networks: 
        default:
            ipv4_address: 172.18.0.38
  canal:
    image: canal/canal-server:v1.1.4
    restart: always
    container_name: canal
    depends_on: 
      - mysql_hermes
    ports: 
      - 11111:11111
    environment: 
      - canal.instance.mysql.slaveId=12
      - canal.auto.scan=false
      - canal.destinations=hermes
      - canal.instance.master.address=mysql_hermes:3306
      - canal.instance.dbUsername=canal
      - canal.instance.dbPassword=canal
      - canal.instance.filter.regex=esen_approval.apt_approval
networks:
   default:
      ipam:
         config:
         - subnet: 172.18.0.0/16