Installation Docker, commandes courantes, déploiement de MySQL, Tomcat, nginx, redis

Introduction à Docker

Docker est un projet cloud open source basé sur le langage Go.
L'objectif principal de Docker est de « créer, expédier et exécuter n'importe quelle application, n'importe où », c'est-à-dire, grâce à la gestion du cycle de vie des composants d'application tels que l'encapsulation, la distribution, le déploiement et l'exploitation, l'application de l'utilisateur (qui peut être une application WEB ou une application de base de données, etc.) et son environnement d'exploitation peuvent réaliser "une image une fois, s'exécuter n'importe où".

Conteneurs logiciels qui résolvent les problèmes d'environnement d'exécution et de configuration, technologie de virtualisation de conteneurs qui facilite l'intégration continue et contribue à la version globale.

1.Installation de Docker

1.1. Prérequis

Actuellement, seul le noyau des versions CentOS prend en charge Docker. Docker fonctionne sur CentOS 7 (64 bits), ce qui
nécessite que le système soit 64 bits et que la version du noyau du système Linux soit 3.8 ou supérieure. Centos7.x est sélectionné ici.

Afficher votre propre noyau
La commande uname est utilisée pour imprimer les informations actuelles relatives au système (numéro de version du noyau, architecture matérielle, nom d'hôte, type de système d'exploitation, etc.)
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1.2. Composition de base de Docker

  1. Image : l'image Docker est un modèle en lecture seule. Les images peuvent être utilisées pour créer des conteneurs Docker, et une image peut créer plusieurs conteneurs.
  2. Conteneur (conteneur) : Docker utilise un conteneur (Conteneur) pour exécuter une application ou un groupe d'applications de manière indépendante. L'application ou le service s'exécute dans le conteneur. Le conteneur est similaire à un environnement d'exploitation virtualisé. Le conteneur est une instance en cours d'exécution créée avec une image. Tout comme les objets de classe et d'instance en Java, l'image est une définition statique et le conteneur est l'entité lors de l'exécution de l'image.
  3. Entrepôt (dépôt) : C'est un endroit où les fichiers image sont stockés de manière centralisée.
    Semblable à l'entrepôt Maven, où sont stockés divers packages jar ;
    à l'entrepôt github, où sont stockés divers projets git ; le
    registre officiel fourni par Docker s'appelle Docker Hub, où sont stockés divers modèles d'images.

1.3. Étapes d'installation

  1. Assurez-vous qu'il s'agit de CentOS7 ou supérieur
cat /etc/redhat-release

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  1. Yum installation liée à gcc
yum -y install gcc
yum -y install gcc-c++

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  1. Installer les packages requis
yum install -y yum-utils

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  1. Mettre en place un entrepôt miroir stable

Utilisez l'accélération d'image aliyun, il n'est pas recommandé d'utiliser celle recommandée par le site officiel. Car il est bien connu que la connexion aux réseaux étrangers sera plus lente.

yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo

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  1. Mettre à jour l'index du paquet Yum
yum makecache fast
  1. Installer DOCKERCE

Cette étape consiste à installer réellement Docker. Les conditions ci-dessus sont requises pour l'installation.

yum -y install docker-ce docker-ce-cli containerd.io

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  1. Démarrer le menu fixe
systemctl start docker

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  1. test
docker version

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  1. désinstaller
systemctl stop docker
yum remove docker-ce docker-ce-cli containerd.io
rm -rf /var/lib/docker
rm -rf /var/lib/containerd

1.4 Accélération des images Alibaba Cloud

https://promotion.aliyun.com/ntms/act/kubernetes.html

Connectez-vous à votre compte Alibaba Cloud, cliquez sur Container Image Service
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pour autoriser l'instance de version personnelle, puis entrez l'accélérateur d'image
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CentOS et exécutez la commande suivante sous Linux
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mkdir -p /etc/docker
tee /etc/docker/daemon.json <<-'EOF'
{
  "registry-mirrors": ["https://93gohnsz.mirror.aliyuncs.com"]
}
EOF
systemctl daemon-reload
systemctl restart docker

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2. Commandes Docker courantes

2.1. Commandes liées au service Docker

  1. Démarrer le service Docker
systemctl start docker
  1. Arrêter le service Docker
systemctl stop docker
  1. Redémarrer le service Docker
systemctl restart docker
  1. Vérifier l'état du service Docker
systemctl status docker
  1. Démarrez le service dockeh au démarrage
systemctl enable docker

2.2. Commandes liées à l'image Docker

  1. Afficher le référentiel d'images local
docker images
docker images -a  --查询所有镜像
  1. Rechercher un entrepôt distant par image

nom de l'image de recherche Docker

docker search redis
  1. Extraire l'image

Les deux points sont suivis du numéro de version, s'ils ne sont pas suivis de la dernière version par défaut (dernière version)

nom de l'image Docker Pull : numéro de version

docker pull redis:6.0
  1. Supprimer le miroir local

nom de l'image docker rmi : numéro de version [identifiant de l'image]

docker rmi redis:6.0

2.3. Commandes liées au conteneur Docker

  1. Créer une commande de conteneur
docker run -it --name=c_centos centos:7 /bin/bash

-i : interactif, laissez le conteneur fonctionner
-t : fournissez une page interactive, si vous utilisez exit pour quitter le conteneur, le conteneur sera fermé
- -name : le nom du conteneur .
L'utilisation de -t ci-dessus entrera à l'intérieur de le conteneur.使用exit则退出容器并关闭容器

docker run -id --name=c_centos2 centos:7 /bin/bash

-d : Exécuté en arrière-plan. Coopérer avec moi.

  1. Vérifiez les conteneurs actuels
docker ps
  1. Entrez dans un conteneur ouvert
docker exec -it 容器名称 /bin/bash

Remarque : L’utilisation de exit ne fermera pas le conteneur, elle le quittera uniquement.

  1. Démarrer le conteneur
docker start [容器名称|容器id]
  1. Fermer le conteneur
docker stop [容器名称|容器id]
  1. Supprimer le conteneur
docker rm [容器名称|容器id]

REMARQUE : Seuls les conteneurs fermés peuvent être supprimés

  1. Afficher les informations sur le conteneur
docker inspect [容器名称|容器id]

3. Volume de données du conteneur

Réflexion :
une fois le conteneur Dockers supprimé, les données générées dans le conteneur sont-elles toujours présentes ? Les fichiers peuvent-ils
être échangés directement entre un conteneur Docker et une machine externe ?Non. Souhaitez-vous
échanger des données entre conteneurs ? via le volume de données

数据卷是宿主机中的一个目录或文件,当容器目录和数据卷目录绑定后对方的修改会立即同步。
Un volume de données peut être monté par plusieurs conteneurs en même temps. Un conteneur peut également être monté par plusieurs volumes de données.


effet:

1. Résoudre le problème de la persistance des données
2. Résoudre le problème de la communication indirecte entre les machines externes et les conteneurs
3. Résoudre l'échange de données entre les conteneurs

  1. Lorsque le contenu du volume du conteneur hôte change, le répertoire correspondant dans le conteneur change également.
  2. Si le répertoire du conteneur change, le contenu du volume du conteneur hôte changera également.
  3. Après avoir supprimé le conteneur, ouvrez-le à nouveau et montez le volume du conteneur. les données existent toujours
  4. Un conteneur monte plusieurs volumes de conteneur
  5. Plusieurs conteneurs montent un volume de conteneur

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docker run -id --name=容器名 -v /宿主机目录:/容器中的目录 镜像名:版本号 /bin/bash

-v : monter le volume de données路径必须为绝对路径

4. Déploiement de l'application Docker

4.1. Docker déploie MySQL

  1. Extrayez l'image mysql1docker pull mysql:5.7
  2. Créez un répertoire mysql.mkdir /root/mysql
  3. Entrercd /root/mysql
  4. Créer un conteneur MySQL
docker run -id \
-p 3307:3306 \
--name=c_mysql \
-v $PWD/conf:/etc/mysql/conf.d \
-v $PWD/logs:/logs \
-v $PWD/data:/var/lib/mysql \
-e MYSQL_ROOT_PASSWORD=123456 \
mysql:5.7

Description du paramètre :
$PWD : répertoire courant,À l'étape 3, vous avez entré le répertoire /root/mysql
-p 3307:3306 : Mappez le port 3306 du conteneur au port 3307 de l'hôte.
-v $PWD/conf:/etc/mysql/conf.d : Montez conf/my.cnf dans le répertoire actuel de l'hôte vers /etc/mysql/my.cnf dans le conteneur. Configurer le répertoire
-v $PWD/logs:/logs : Montez le répertoire des journaux dans le répertoire actuel de l'hôte sur /logs du conteneur. Log directory
-v $PWD/data:/var/lib/mysql : Montez le répertoire de données dans le répertoire actuel de l'hôte sur /var/lib/mysql du conteneur. Répertoire de données
-e MYSQL_ROOT_PASSWORD=123456 : Initialise le mot de passe de l'utilisateur root.

  1. Désactivez le pare-feu Linux et utilisez Navicat pour vous connecter à la base de données.
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4.2. Docker déploie Tomcat

Voici un enregistrement des méthodes disponibles pour la pratique.

  1. Télécharger Tomcat 9.0 image
docker pull tomcat:9.0
  1. Créer et démarrer le conteneur
docker run -p 8081:8080  --name tomcat9 -d tomcat:9.0
  1. Copiez les dossiers conf, log, webapps, work et temp du fichier de configuration.
    Les commandes suivantes sont exécutées dans l'ordre. Créer un volume de données entre le conteneur et l'hôte
docker cp tomcat9:/usr/local/tomcat/conf/ /root/tomcat/conf/
docker cp tomcat9:/usr/local/tomcat/logs/  /root/tomcat/logs/
docker cp tomcat9:/usr/local/tomcat/webapps/  /root/tomcat/webapps/
docker cp tomcat9:/usr/local/tomcat/work/ /root/tomcat/work/
docker cp tomcat9:/usr/local/tomcat/temp/ /root/tomcat/temp/
  1. Arrêter le conteneur
docker stop tomcat9
  1. Supprimer le conteneur
docker rm tomcat9
  1. Créez à nouveau le conteneur de démarrage et montez le répertoire
docker run -p 8081:8080  --name tomcat9  \
-v /root/tomcat/conf/:/usr/local/tomcat/conf \
-v /root/tomcat/logs/:/usr/local/tomcat/logs \
-v /root/tomcat/webapps/:/usr/local/tomcat/webapps \
-v /root/tomcat/work/:/usr/local/tomcat/work \
-v /root/tomcat/temp/:/usr/local/tomcat/temp \
-d tomcat:9.0
  1. Désactivez le pare-feu et accédez au port 8081 de Tomcat
    Insérer la description de l'image ici

Après la pratique, cette méthode ne peut plus être utilisée. Le problème spécifique est qu'il n'y a pas de contenu dans le volume de données après la création et qu'il n'y a pas de contenu dans le fichier correspondant dans le conteneur Docker.

  1. Extraire l'image de Tomcatdocker pull tomcat
  2. Créer un répertoire Tomcatmkdir /root/tomcat
  3. Entrez le répertoire Tomcatcd /root/tomcat
  4. Créer un conteneur Tomcat
docker run -id --name=c_tomcat \
-p 8080:8080 \
-v $PWD/webapps:/usr/local/tomcat/webapps \
-v $PWD/conf:/usr/local/tomcat/conf \ 
tomcat /bin/bash

4.3. Docker déployer nginx

  1. Extraire l'image nginx
docker pull nginx
  1. Créer un répertoire

Créez un répertoire nginx sous le répertoire /root pour stocker les informations sur les données nginx

mkdir nginx

Créer des répertoires conf, log, html dans nginx

mkdir -p /root/nginx/conf
mkdir -p /root/nginx/log
mkdir -p /root/nginx/html
  1. Créer un conteneur

Le but de la création d'un conteneur est de copier le fichier de configuration

docker run -p80:80 --name=nginx  nginx /bin/bash
  1. Copiez le fichier nginx.conf, le dossier conf.d et le dossier html du conteneur sur la machine hôte
docker cp nginx:/etc/nginx/nginx.conf /root/nginx/conf/nginx.conf
docker cp nginx:/etc/nginx/conf.d /root/nginx/conf/conf.d
docker cp nginx:/usr/share/nginx/html /root/nginx/
  1. Supprimer le conteneur

fermer le conteneur

docker stop nginx

Supprimer le conteneur

docker rm nginx
  1. Générez un conteneur et montez le volume de données
docker run \
-p 80:80 \
--name c_nginx \
-v /root/nginx/conf/nginx.conf:/etc/nginx/nginx.conf \
-v /root/nginx/conf/conf.d:/etc/nginx/conf.d \
-v /root/nginx/log:/var/log/nginx \
-v /root/nginx/html:/usr/share/nginx/html \
-d nginx
  1. Après avoir désactivé le pare-feu, accédez à nginx
    Insérer la description de l'image ici

4.4. Docker déploie Redis

  1. Extraire l'image
docker pull redis:6.0
  1. Créez le répertoire et le fichier de configuration à monter

Créez un répertoire redis dans le répertoire /root

mkdir -p /root/redis/data

Entrez le répertoire redis

cd /root/redis

Créer le fichier de configuration redis.conf

vim redis.conf

Copiez le contenu suivant dans le fichier redis.conf

# redis 配置文件示例
# 当你需要为某个配置项指定内存大小的时候,必须要带上单位,
# 通常的格式就是 1k 5gb 4m 等酱紫:
#
# 1k  => 1000 bytes
# 1kb => 1024 bytes
# 1m  => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g  => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# 单位是不区分大小写的,你写 1K 5GB 4M 也行
 
################################## INCLUDES ###################################
 
# 假如说你有一个可用于所有的 redis server 的标准配置模板,
# 但针对某些 server 又需要一些个性化的设置,
# 你可以使用 include 来包含一些其他的配置文件,这对你来说是非常有用的。
#
# 但是要注意哦,include 是不能被 config rewrite 命令改写的
# 由于 redis 总是以最后的加工线作为一个配置指令值,所以你最好是把 include 放在这个文件的最前面,
# 以避免在运行时覆盖配置的改变,相反,你就把它放在后面(外国人真啰嗦)。
#
# include /path/to/local.conf
# include /path/to/other.conf
 
################################ 常用 #####################################
 
# 默认情况下 redis 不是作为守护进程运行的,如果你想让它在后台运行,你就把它改成 yes。
# 当redis作为守护进程运行的时候,它会写一个 pid 到 /var/run/redis.pid 文件里面。
daemonize no
 
# 当redis作为守护进程运行的时候,它会把 pid 默认写到 /var/run/redis.pid 文件里面,
# 但是你可以在这里自己制定它的文件位置。
pidfile /usr/local/nodn/docker/redis/run/redis.pid
 
# 监听端口号,默认为 6379,如果你设为 0 ,redis 将不在 socket 上监听任何客户端连接。
port 6379
 
# TCP 监听的最大容纳数量
#
# 在高并发的环境下,你需要把这个值调高以避免客户端连接缓慢的问题。
# Linux 内核会一声不响的把这个值缩小成 /proc/sys/net/core/somaxconn 对应的值,
# 所以你要修改这两个值才能达到你的预期。
tcp-backlog 511
 
# 默认情况下,redis 在 server 上所有有效的网络接口上监听客户端连接。
# 你如果只想让它在一个网络接口上监听,那你就绑定一个IP或者多个IP。
#
# 示例,多个IP用空格隔开:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1
 
# 指定 unix socket 的路径。
#
# unixsocket /tmp/redis.sock
# unixsocketperm 755
 
# 指定在一个 client 空闲多少秒之后关闭连接(0 就是不管它)
timeout 0
 
# tcp 心跳包。
#
# 如果设置为非零,则在与客户端缺乏通讯的时候使用 SO_KEEPALIVE 发送 tcp acks 给客户端。
# 这个之所有有用,主要由两个原因:
#
# 1) 防止死的 peers
# 2) Take the connection alive from the point of view of network
#    equipment in the middle.
#
# On Linux, the specified value (in seconds) is the period used to send ACKs.
# Note that to close the connection the double of the time is needed.
# On other kernels the period depends on the kernel configuration.
#
# A reasonable value for this option is 60 seconds.
# 推荐一个合理的值就是60秒
tcp-keepalive 0
 
# 定义日志级别。
# 可以是下面的这些值:
# debug (适用于开发或测试阶段)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (适用于生产环境)
# warning (仅仅一些重要的消息被记录)
loglevel notice
 
# 指定日志文件的位置
logfile ""
 
# 要想把日志记录到系统日志,就把它改成 yes,
# 也可以可选择性的更新其他的syslog 参数以达到你的要求
# syslog-enabled no
 
# 设置 syslog 的 identity。
# syslog-ident redis
 
# 设置 syslog 的 facility,必须是 USER 或者是 LOCAL0-LOCAL7 之间的值。
# syslog-facility local0
 
# 设置数据库的数目。
# 默认数据库是 DB 0,你可以在每个连接上使用 select <dbid> 命令选择一个不同的数据库,
# 但是 dbid 必须是一个介于 0 到 databasees - 1 之间的值
databases 16
 
################################ 快照 ################################
#
# 存 DB 到磁盘:
#
#   格式:save <间隔时间(秒)> <写入次数>
#
#   根据给定的时间间隔和写入次数将数据保存到磁盘
#
#   下面的例子的意思是:
#   900 秒内如果至少有 1 个 key 的值变化,则保存
#   300 秒内如果至少有 10 个 key 的值变化,则保存
#   60 秒内如果至少有 10000 个 key 的值变化,则保存
#  
#   注意:你可以注释掉所有的 save 行来停用保存功能。
#   也可以直接一个空字符串来实现停用:
#   save ""

save 900 1
save 300 10
save 60 10000
 
# 默认情况下,如果 redis 最后一次的后台保存失败,redis 将停止接受写操作,
# 这样以一种强硬的方式让用户知道数据不能正确的持久化到磁盘,
# 否则就会没人注意到灾难的发生。
#
# 如果后台保存进程重新启动工作了,redis 也将自动的允许写操作。
#
# 然而你要是安装了靠谱的监控,你可能不希望 redis 这样做,那你就改成 no 好了。
stop-writes-on-bgsave-error yes
 
# 是否在 dump .rdb 数据库的时候使用 LZF 压缩字符串
# 默认都设为 yes
# 如果你希望保存子进程节省点 cpu ,你就设置它为 no ,
# 不过这个数据集可能就会比较大
rdbcompression yes
 
# 是否校验rdb文件
rdbchecksum yes
 
# 设置 dump 的文件位置
dbfilename dump.rdb
 
# 工作目录
# 例如上面的 dbfilename 只指定了文件名,
# 但是它会写入到这个目录下。这个配置项一定是个目录,而不能是文件名。
dir ./
 
################################# 主从复制 #################################
 
# 主从复制。使用 slaveof 来让一个 redis 实例成为另一个reids 实例的副本。
# 注意这个只需要在 slave 上配置。
#
# slaveof <masterip> <masterport>
 
# 如果 master 需要密码认证,就在这里设置
# masterauth <master-password>
 
# 当一个 slave 与 master 失去联系,或者复制正在进行的时候,
# slave 可能会有两种表现:
#
# 1) 如果为 yes ,slave 仍然会应答客户端请求,但返回的数据可能是过时,
#    或者数据可能是空的在第一次同步的时候
#
# 2) 如果为 no ,在你执行除了 info he salveof 之外的其他命令时,
#    slave 都将返回一个 "SYNC with master in progress" 的错误,
#
slave-serve-stale-data yes
 
# 你可以配置一个 slave 实体是否接受写入操作。
# 通过写入操作来存储一些短暂的数据对于一个 slave 实例来说可能是有用的,
# 因为相对从 master 重新同步数而言,据数据写入到 slave 会更容易被删除。
# 但是如果客户端因为一个错误的配置写入,也可能会导致一些问题。
#
# 从 redis 2.6 版起,默认 slaves 都是只读的。
#
# Note: read only slaves are not designed to be exposed to untrusted clients
# on the internet. It's just a protection layer against misuse of the instance.
# Still a read only slave exports by default all the administrative commands
# such as CONFIG, DEBUG, and so forth. To a limited extent you can improve
# security of read only slaves using 'rename-command' to shadow all the
# administrative / dangerous commands.
# 注意:只读的 slaves 没有被设计成在 internet 上暴露给不受信任的客户端。
# 它仅仅是一个针对误用实例的一个保护层。
slave-read-only yes
 
# Slaves 在一个预定义的时间间隔内发送 ping 命令到 server 。
# 你可以改变这个时间间隔。默认为 10 秒。
#
# repl-ping-slave-period 10
 
# The following option sets the replication timeout for:
# 设置主从复制过期时间
#
# 1) Bulk transfer I/O during SYNC, from the point of view of slave.
# 2) Master timeout from the point of view of slaves (data, pings).
# 3) Slave timeout from the point of view of masters (REPLCONF ACK pings).
#
# It is important to make sure that this value is greater than the value
# specified for repl-ping-slave-period otherwise a timeout will be detected
# every time there is low traffic between the master and the slave.
# 这个值一定要比 repl-ping-slave-period 大
#
# repl-timeout 60
 
# Disable TCP_NODELAY on the slave socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to slaves. But this can add a delay for
# the data to appear on the slave side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the slave side will
# be reduced but more bandwidth will be used for replication.
#
# By default we optimize for low latency, but in very high traffic conditions
# or when the master and slaves are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
 
# 设置主从复制容量大小。这个 backlog 是一个用来在 slaves 被断开连接时
# 存放 slave 数据的 buffer,所以当一个 slave 想要重新连接,通常不希望全部重新同步,
# 只是部分同步就够了,仅仅传递 slave 在断开连接时丢失的这部分数据。
#
# The biggest the replication backlog, the longer the time the slave can be
# disconnected and later be able to perform a partial resynchronization.
# 这个值越大,salve 可以断开连接的时间就越长。
#
# The backlog is only allocated once there is at least a slave connected.
#
# repl-backlog-size 1mb
 
# After a master has no longer connected slaves for some time, the backlog
# will be freed. The following option configures the amount of seconds that
# need to elapse, starting from the time the last slave disconnected, for
# the backlog buffer to be freed.
# 在某些时候,master 不再连接 slaves,backlog 将被释放。
#
# A value of 0 means to never release the backlog.
# 如果设置为 0 ,意味着绝不释放 backlog 。
#
# repl-backlog-ttl 3600
 
# 当 master 不能正常工作的时候,Redis Sentinel 会从 slaves 中选出一个新的 master,
# 这个值越小,就越会被优先选中,但是如果是 0 , 那是意味着这个 slave 不可能被选中。
#
# 默认优先级为 100。
slave-priority 100
 
# It is possible for a master to stop accepting writes if there are less than
# N slaves connected, having a lag less or equal than M seconds.
#
# The N slaves need to be in "online" state.
#
# The lag in seconds, that must be <= the specified value, is calculated from
# the last ping received from the slave, that is usually sent every second.
#
# This option does not GUARANTEES that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough slaves
# are available, to the specified number of seconds.
#
# For example to require at least 3 slaves with a lag <= 10 seconds use:
#
# min-slaves-to-write 3
# min-slaves-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-slaves-to-write is set to 0 (feature disabled) and
# min-slaves-max-lag is set to 10.
 
################################## 安全 ###################################
 
# Require clients to issue AUTH <PASSWORD> before processing any other
# commands.  This might be useful in environments in which you do not trust
# others with access to the host running redis-server.
#
# This should stay commented out for backward compatibility and because most
# people do not need auth (e.g. they run their own servers).
# 
# Warning: since Redis is pretty fast an outside user can try up to
# 150k passwords per second against a good box. This means that you should
# use a very strong password otherwise it will be very easy to break.
# 
# 设置认证密码
# requirepass foobared
 
# Command renaming.
#
# It is possible to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# hard to guess so that it will still be available for internal-use tools
# but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possible to completely kill a command by renaming it into
# an empty string:
#
# rename-command CONFIG ""
#
# Please note that changing the name of commands that are logged into the
# AOF file or transmitted to slaves may cause problems.
 
################################### 限制 ####################################
 
# Set the max number of connected clients at the same time. By default
# this limit is set to 10000 clients, however if the Redis server is not
# able to configure the process file limit to allow for the specified limit
# the max number of allowed clients is set to the current file limit
# minus 32 (as Redis reserves a few file descriptors for internal uses).
#
# 一旦达到最大限制,redis 将关闭所有的新连接
# 并发送一个‘max number of clients reached’的错误。
#
# maxclients 10000
 
# 如果你设置了这个值,当缓存的数据容量达到这个值, redis 将根据你选择的
# eviction 策略来移除一些 keys。
#
# 如果 redis 不能根据策略移除 keys ,或者是策略被设置为 ‘noeviction’,
# redis 将开始响应错误给命令,如 set,lpush 等等,
# 并继续响应只读的命令,如 get
#
# This option is usually useful when using Redis as an LRU cache, or to set
# a hard memory limit for an instance (using the 'noeviction' policy).
#
# WARNING: If you have slaves attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the slaves are subtracted
# from the used memory count, so that network problems / resyncs will
# not trigger a loop where keys are evicted, and in turn the output
# buffer of slaves is full with DELs of keys evicted triggering the deletion
# of more keys, and so forth until the database is completely emptied.
#
# In short... if you have slaves attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for slave
# output buffers (but this is not needed if the policy is 'noeviction').
#
# 最大使用内存
# maxmemory <bytes>
 
# 最大内存策略,你有 5 个选择。
# 
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# volatile-lru -> 使用 LRU 算法移除包含过期设置的 key 。
# allkeys-lru -> remove any key accordingly to the LRU algorithm
# allkeys-lru -> 根据 LRU 算法移除所有的 key 。
# volatile-random -> remove a random key with an expire set
# allkeys-random -> remove a random key, any key
# volatile-ttl -> remove the key with the nearest expire time (minor TTL)
# noeviction -> don't expire at all, just return an error on write operations
# noeviction -> 不让任何 key 过期,只是给写入操作返回一个错误
# 
# Note: with any of the above policies, Redis will return an error on write
#       operations, when there are not suitable keys for eviction.
#
#       At the date of writing this commands are: set setnx setex append
#       incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
#       sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
#       zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
#       getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy noeviction
 
# LRU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can tune it for speed or
# accuracy. For default Redis will check five keys and pick the one that was
# used less recently, you can change the sample size using the following
# configuration directive.
#
# The default of 5 produces good enough results. 10 Approximates very closely
# true LRU but costs a bit more CPU. 3 is very fast but not very accurate.
#
# maxmemory-samples 5
 
############################## APPEND ONLY MODE ###############################
 
# By default Redis asynchronously dumps the dataset on disk. This mode is
# good enough in many applications, but an issue with the Redis process or
# a power outage may result into a few minutes of writes lost (depending on
# the configured save points).
#
# The Append Only File is an alternative persistence mode that provides
# much better durability. For instance using the default data fsync policy
# (see later in the config file) Redis can lose just one second of writes in a
# dramatic event like a server power outage, or a single write if something
# wrong with the Redis process itself happens, but the operating system is
# still running correctly.
#
# AOF and RDB persistence can be enabled at the same time without problems.
# If the AOF is enabled on startup Redis will load the AOF, that is the file
# with the better durability guarantees.
#
# Please check http://redis.io/topics/persistence for more information.
 
appendonly no
 
# The name of the append only file (default: "appendonly.aof")
 
appendfilename "appendonly.aof"
 
# The fsync() call tells the Operating System to actually write data on disk
# instead to wait for more data in the output buffer. Some OS will really flush 
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log . Slow, Safest.
# everysec: fsync only one time every second. Compromise.
#
# The default is "everysec", as that's usually the right compromise between
# speed and data safety. It's up to you to understand if you can relax this to
# "no" that will let the operating system flush the output buffer when
# it wants, for better performances (but if you can live with the idea of
# some data loss consider the default persistence mode that's snapshotting),
# or on the contrary, use "always" that's very slow but a bit safer than
# everysec.
#
# More details please check the following article:
# http://antirez.com/post/redis-persistence-demystified.html
#
# If unsure, use "everysec".
 
# appendfsync always
appendfsync everysec
# appendfsync no
 
# When the AOF fsync policy is set to always or everysec, and a background
# saving process (a background save or AOF log background rewriting) is
# performing a lot of I/O against the disk, in some Linux configurations
# Redis may block too long on the fsync() call. Note that there is no fix for
# this currently, as even performing fsync in a different thread will block
# our synchronous write(2) call.
#
# In order to mitigate this problem it's possible to use the following option
# that will prevent fsync() from being called in the main process while a
# BGSAVE or BGREWRITEAOF is in progress.
#
# This means that while another child is saving, the durability of Redis is
# the same as "appendfsync none". In practical terms, this means that it is
# possible to lose up to 30 seconds of log in the worst scenario (with the
# default Linux settings).
# 
# If you have latency problems turn this to "yes". Otherwise leave it as
# "no" that is the safest pick from the point of view of durability.
 
no-appendfsync-on-rewrite no
 
# Automatic rewrite of the append only file.
# Redis is able to automatically rewrite the log file implicitly calling
# BGREWRITEAOF when the AOF log size grows by the specified percentage.
# 
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (if no rewrite has happened since the restart, the size of
# the AOF at startup is used).
#
# This base size is compared to the current size. If the current size is
# bigger than the specified percentage, the rewrite is triggered. Also
# you need to specify a minimal size for the AOF file to be rewritten, this
# is useful to avoid rewriting the AOF file even if the percentage increase
# is reached but it is still pretty small.
#
# Specify a percentage of zero in order to disable the automatic AOF
# rewrite feature.
 
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb
 
################################ LUA SCRIPTING  ###############################
 
# Max execution time of a Lua script in milliseconds.
#
# If the maximum execution time is reached Redis will log that a script is
# still in execution after the maximum allowed time and will start to
# reply to queries with an error.
#
# When a long running script exceed the maximum execution time only the
# SCRIPT KILL and SHUTDOWN NOSAVE commands are available. The first can be
# used to stop a script that did not yet called write commands. The second
# is the only way to shut down the server in the case a write commands was
# already issue by the script but the user don't want to wait for the natural
# termination of the script.
#
# Set it to 0 or a negative value for unlimited execution without warnings.
lua-time-limit 5000
 
################################ REDIS 集群  ###############################
#
# 启用或停用集群
# cluster-enabled yes
 
# Every cluster node has a cluster configuration file. This file is not
# intended to be edited by hand. It is created and updated by Redis nodes.
# Every Redis Cluster node requires a different cluster configuration file.
# Make sure that instances running in the same system does not have
# overlapping cluster configuration file names.
#
# cluster-config-file nodes-6379.conf
 
# Cluster node timeout is the amount of milliseconds a node must be unreachable 
# for it to be considered in failure state.
# Most other internal time limits are multiple of the node timeout.
#
# cluster-node-timeout 15000
 
# A slave of a failing master will avoid to start a failover if its data
# looks too old.
#
# There is no simple way for a slave to actually have a exact measure of
# its "data age", so the following two checks are performed:
#
# 1) If there are multiple slaves able to failover, they exchange messages
#    in order to try to give an advantage to the slave with the best
#    replication offset (more data from the master processed).
#    Slaves will try to get their rank by offset, and apply to the start
#    of the failover a delay proportional to their rank.
#
# 2) Every single slave computes the time of the last interaction with
#    its master. This can be the last ping or command received (if the master
#    is still in the "connected" state), or the time that elapsed since the
#    disconnection with the master (if the replication link is currently down).
#    If the last interaction is too old, the slave will not try to failover
#    at all.
#
# The point "2" can be tuned by user. Specifically a slave will not perform
# the failover if, since the last interaction with the master, the time
# elapsed is greater than:
#
#   (node-timeout * slave-validity-factor) + repl-ping-slave-period
#
# So for example if node-timeout is 30 seconds, and the slave-validity-factor
# is 10, and assuming a default repl-ping-slave-period of 10 seconds, the
# slave will not try to failover if it was not able to talk with the master
# for longer than 310 seconds.
#
# A large slave-validity-factor may allow slaves with too old data to failover
# a master, while a too small value may prevent the cluster from being able to
# elect a slave at all.
#
# For maximum availability, it is possible to set the slave-validity-factor
# to a value of 0, which means, that slaves will always try to failover the
# master regardless of the last time they interacted with the master.
# (However they'll always try to apply a delay proportional to their
# offset rank).
#
# Zero is the only value able to guarantee that when all the partitions heal
# the cluster will always be able to continue.
#
# cluster-slave-validity-factor 10
 
# Cluster slaves are able to migrate to orphaned masters, that are masters
# that are left without working slaves. This improves the cluster ability
# to resist to failures as otherwise an orphaned master can't be failed over
# in case of failure if it has no working slaves.
#
# Slaves migrate to orphaned masters only if there are still at least a
# given number of other working slaves for their old master. This number
# is the "migration barrier". A migration barrier of 1 means that a slave
# will migrate only if there is at least 1 other working slave for its master
# and so forth. It usually reflects the number of slaves you want for every
# master in your cluster.
#
# Default is 1 (slaves migrate only if their masters remain with at least
# one slave). To disable migration just set it to a very large value.
# A value of 0 can be set but is useful only for debugging and dangerous
# in production.
#
# cluster-migration-barrier 1
 
# In order to setup your cluster make sure to read the documentation
# available at http://redis.io web site.
 
################################## SLOW LOG ###################################
 
# The Redis Slow Log is a system to log queries that exceeded a specified
# execution time. The execution time does not include the I/O operations
# like talking with the client, sending the reply and so forth,
# but just the time needed to actually execute the command (this is the only
# stage of command execution where the thread is blocked and can not serve
# other requests in the meantime).
# 
# You can configure the slow log with two parameters: one tells Redis
# what is the execution time, in microseconds, to exceed in order for the
# command to get logged, and the other parameter is the length of the
# slow log. When a new command is logged the oldest one is removed from the
# queue of logged commands.
 
# The following time is expressed in microseconds, so 1000000 is equivalent
# to one second. Note that a negative number disables the slow log, while
# a value of zero forces the logging of every command.
slowlog-log-slower-than 10000
 
# There is no limit to this length. Just be aware that it will consume memory.
# You can reclaim memory used by the slow log with SLOWLOG RESET.
slowlog-max-len 128
 
############################# Event notification ##############################
 
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/keyspace-events
# 
# For instance if keyspace events notification is enabled, and a client
# performs a DEL operation on key "foo" stored in the Database 0, two
# messages will be published via Pub/Sub:
#
# PUBLISH __keyspace@0__:foo del
# PUBLISH __keyevent@0__:del foo
#
# It is possible to select the events that Redis will notify among a set
# of classes. Every class is identified by a single character:
#
#  K     Keyspace events, published with __keyspace@<db>__ prefix.
#  E     Keyevent events, published with __keyevent@<db>__ prefix.
#  g     Generic commands (non-type specific) like DEL, EXPIRE, RENAME, ...
#  $     String commands
#  l     List commands
#  s     Set commands
#  h     Hash commands
#  z     Sorted set commands
#  x     Expired events (events generated every time a key expires)
#  e     Evicted events (events generated when a key is evicted for maxmemory)
#  A     Alias for g$lshzxe, so that the "AKE" string means all the events.
#
#  The "notify-keyspace-events" takes as argument a string that is composed
#  by zero or multiple characters. The empty string means that notifications
#  are disabled at all.
#
#  Example: to enable list and generic events, from the point of view of the
#           event name, use:
#
#  notify-keyspace-events Elg
#
#  Example 2: to get the stream of the expired keys subscribing to channel
#             name __keyevent@0__:expired use:
#
#  notify-keyspace-events Ex
#
#  By default all notifications are disabled because most users don't need
#  this feature and the feature has some overhead. Note that if you don't
#  specify at least one of K or E, no events will be delivered.
notify-keyspace-events ""
 
############################### ADVANCED CONFIG ###############################
 
# Hashes are encoded using a memory efficient data structure when they have a
# small number of entries, and the biggest entry does not exceed a given
# threshold. These thresholds can be configured using the following directives.
hash-max-ziplist-entries 512
hash-max-ziplist-value 64
 
# Similarly to hashes, small lists are also encoded in a special way in order
# to save a lot of space. The special representation is only used when
# you are under the following limits:
list-max-ziplist-entries 512
list-max-ziplist-value 64
 
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happens to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512
 
# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64
 
# HyperLogLog sparse representation bytes limit. The limit includes the
# 16 bytes header. When an HyperLogLog using the sparse representation crosses
# this limit, it is converted into the dense representation.
#
# A value greater than 16000 is totally useless, since at that point the
# dense representation is more memory efficient.
# 
# The suggested value is ~ 3000 in order to have the benefits of
# the space efficient encoding without slowing down too much PFADD,
# which is O(N) with the sparse encoding. The value can be raised to
# ~ 10000 when CPU is not a concern, but space is, and the data set is
# composed of many HyperLogLogs with cardinality in the 0 - 15000 range.
hll-sparse-max-bytes 3000
 
# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
# order to help rehashing the main Redis hash table (the one mapping top-level
# keys to values). The hash table implementation Redis uses (see dict.c)
# performs a lazy rehashing: the more operation you run into a hash table
# that is rehashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
# 
# The default is to use this millisecond 10 times every second in order to
# active rehashing the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply form time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes
 
# The client output buffer limits can be used to force disconnection of clients
# that are not reading data from the server fast enough for some reason (a
# common reason is that a Pub/Sub client can't consume messages as fast as the
# publisher can produce them).
#
# The limit can be set differently for the three different classes of clients:
#
# normal -> normal clients
# slave  -> slave clients and MONITOR clients
# pubsub -> clients subscribed to at least one pubsub channel or pattern
#
# The syntax of every client-output-buffer-limit directive is the following:
#
# client-output-buffer-limit <class> <hard limit> <soft limit> <soft seconds>
#
# A client is immediately disconnected once the hard limit is reached, or if
# the soft limit is reached and remains reached for the specified number of
# seconds (continuously).
# So for instance if the hard limit is 32 megabytes and the soft limit is
# 16 megabytes / 10 seconds, the client will get disconnected immediately
# if the size of the output buffers reach 32 megabytes, but will also get
# disconnected if the client reaches 16 megabytes and continuously overcomes
# the limit for 10 seconds.
#
# By default normal clients are not limited because they don't receive data
# without asking (in a push way), but just after a request, so only
# asynchronous clients may create a scenario where data is requested faster
# than it can read.
#
# Instead there is a default limit for pubsub and slave clients, since
# subscribers and slaves receive data in a push fashion.
#
# Both the hard or the soft limit can be disabled by setting them to zero.
client-output-buffer-limit normal 0 0 0
client-output-buffer-limit slave 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
 
# Redis calls an internal function to perform many background tasks, like
# closing connections of clients in timeout, purging expired keys that are
# never requested, and so forth.
#
# Not all tasks are performed with the same frequency, but Redis checks for
# tasks to perform accordingly to the specified "hz" value.
#
# By default "hz" is set to 10. Raising the value will use more CPU when
# Redis is idle, but at the same time will make Redis more responsive when
# there are many keys expiring at the same time, and timeouts may be
# handled with more precision.
#
# The range is between 1 and 500, however a value over 100 is usually not
# a good idea. Most users should use the default of 10 and raise this up to
# 100 only in environments where very low latency is required.
hz 10
 
# When a child rewrites the AOF file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
aof-rewrite-incremental-fsync yes

Le contenu du répertoire redis :
Insérer la description de l'image ici

  1. Créer un conteneur
docker run -d \
--name c_redis \
-p 6379:6379 \
--privileged=true \
--restart always \
-v /root/redis/redis.conf:/etc/redis/redis.conf \
-v /root/redis/data:/data redis:6.0 redis-server /etc/redis/redis.conf \
--appendonly yes 
  1. Tester Redis
    Insérer la description de l'image ici

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Origine blog.csdn.net/qq_60969145/article/details/131413109
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