本文将分享一文教您通过Docker快速搭建各种测试环境(Mysql,Redis,ES,MongoDB的详细内容,此外,我们还将为大家带来关于Docker+Nodejs+Kafka+Redis+MySQ
本文将分享一文教您通过 Docker 快速搭建各种测试环境(Mysql, Redis, ES, MongoDB的详细内容,此外,我们还将为大家带来关于Docker + Nodejs + Kafka + Redis + MySQL搭建简单秒杀环境、docker 入坑 4 搭建 mongoldb、redis、mysql、docker 入坑4 搭建mongoldb、redis、mysql、docker 安装 mongodb 和 redis的相关知识,希望对你有所帮助。
本文目录一览:- 一文教您通过 Docker 快速搭建各种测试环境(Mysql, Redis, ES, MongoDB
- Docker + Nodejs + Kafka + Redis + MySQL搭建简单秒杀环境
- docker 入坑 4 搭建 mongoldb、redis、mysql
- docker 入坑4 搭建mongoldb、redis、mysql
- docker 安装 mongodb 和 redis
一文教您通过 Docker 快速搭建各种测试环境(Mysql, Redis, ES, MongoDB
小哈今天给大家分享的主题是,如何通过 Docker 快速搭建各种测试环境,本文列举的,也是小哈在工作中经常用到的,包括 MysqL, Redis, Elasticsearch, MongoDB, 通过几行命令秒秒钟就能轻松搞定环境搭建问题,相信对小伙伴们也有所用处。
友情提示:搭建之前,你需要先安装 Docker 哟,本文基于您已经安装好 Docker 的基础之上!
废话少说,正文开始!
目录
一、镜像加速
二、快速安装&搭建 MysqL 环境
三、快速安装&搭建 Redis 环境
四、快速安装&搭建 MongDB 环境
五、快速安装&搭建 Elasticsearch 环境
六、总结
@H_301_38@首先你需要注册一个阿里云账号,没有的话,通过下面的连接跳转注册:
跳转镜像加速页 https://cr.console.aliyun.com/,获取加速配置信息:
一、镜像加速
Docker 默认是从官方镜像地址 Docker Hub 下下载镜像,由于服务器在国外的缘故,导致经常下载速度非常慢。为了提升镜像的下载速度,我们可以手动配置国内镜像加速器,让下载速度飚起来。
国内的镜像加速器选项较多,如:阿里云,DaoCloud 等。
本文主要说说如何配置阿里云的镜像加速器。
2.1 登录阿里云获取加速信息
https://dev.aliyun.com/
2.2 配置 Docker
2.2.1 确定 Docker Client 版本
在配置之前,首先需要确定 Docker Client 的版本,推荐是 1.10.0+:
2.2.2 配置镜像加速器
PS: 这里以 CentOS 系统为例,如果你是别的系统,可以参考阿里云配置加速器官方文档。
通过修改 daemon 配置文件 /etc/docker/daemon.json
来使用加速器:
执行下面命令:
sudo mkdir -p /etc/docker sudo tee /etc/docker/daemon.json <<-'EOF' { "registry-mirrors": ["https://bjtzu1jb.mirror.aliyuncs.com"] } EOF sudo systemctl daemon-reload sudo systemctl restart docker
2.3 验证一下速度
以下载 mongodb 为例,看下速度:
配置了加速器过后,速度终于飚起来了。
二、快速安装&搭建 MysqL 环境
本节中,我们将学习如何通过 Docker 快速安装与搭建 MysqL 环境。
2.1 下载 MysqL 镜像
这里以 MysqL 5.7 为例:
docker pull MysqL:5.7
下载完成后,通过 docker images
检查一下镜像是否下载成功:
2.2 先以最简单方式启动
先以简单的方式启动:
docker run -d \ --name MysqL \ -p 3306:3306 \ -e MysqL_ROOT_PASSWORD=123456 \ MysqL:5.7
-d
:以后台的方式运行;--name MysqL
:指定容器的名称为 MysqL;-p3306:3306
将容器的 3306 端口挂载到宿主机的 3306 端口上;-e MysqL_ROOT_PASSWORD=123456
:指定 root 的密码为 123456 @H_301_38@MysqL 配置文件;
数据存储目录,以便挂载(PS: 若不挂载到宿主机,每次启动容器数据都会丢失)
@H_301_38@
命令执行完成后,你也可以通过 docker ps
命令来确认下容器是否启动成功。若成功,我们需要将容器中的目录文件复制到宿主机中,分别包括:
docker run -d \ --name MysqL \ -p 3306:3306 \ -v /usr/local/docker/MysqL/config/MysqLd.cnf:/etc/MysqL/MysqL.conf.d/MysqLd.cnf \ -v /usr/local/docker/MysqL/data/MysqL:/var/lib/MysqL \ -e MysqL_ROOT_PASSWORD=123456 \ MysqL:5.7
完成这一切后,让我们将刚刚运行的容器删除掉。
docker rm -f MysqL
PS: MysqL 是我们运行容器时,指定的名称,当然,你也可以先执行
docker ps
, 通过容器 ID 来删除。
2.3 正式运行 MysqL 容器
接下来,正式运行 MysqL 容器:
docker run -d \ --name MysqL \ -p 3306:3306 \ -v /usr/local/docker/MysqL/config/MysqLd.cnf:/etc/MysqL/MysqL.conf.d/MysqLd.cnf \ -v /usr/local/docker/MysqL/data/MysqL:/var/lib/MysqL \ -e MysqL_ROOT_PASSWORD=123456 \ MysqL:5.7
其他不变,额外添加了两个挂载子命令:
-v/usr/local/docker/MysqL/config/MysqLd.cnf:/etc/MysqL/MysqL.conf.d/MysqLd.cnf
: 将容器中 /etc/MysqL/MysqL.conf.d/MysqLd.cnf 配置文件挂载到宿主机的 /usr/local/docker/MysqL/config/MysqLd.cnf 文件上;-v/usr/local/docker/MysqL/data:/var/lib/MysqL
: 将容器中 /var/lib/MysqL 数据目录挂载到宿主机的 /usr/local/docker/MysqL/data 目录下; @H_301_38@
执行命令完成后,查看下容器是否启动:
可以看到,容器运行成功
2.4 通过 MysqL 客户端连接一下试试
通过 MysqL 客户端连接刚刚创建的 MysqL, 看看能否连接成功:
连接成功了!
三、快速安装&搭建 Redis 环境
本节中,我们将学习如何利用 Docker 安装&搭建 Redis 环境。
3.1 下载 Redis 镜像
首先拉取 Redis 镜像, 这里我选择的是 redis:alpine
轻量级镜像版本:
docker pull redis:alpine
下载完成后,通过 docker images
确认镜像是否已经下载到本地:
3.2 运行 Redis 容器
docker run -p 6379:6379 --name redis -v /usr/local/docker/redis/redis.conf:/etc/redis/redis.conf -v /usr/local/docker/redis/data:/data -d redis:alpine redis-server /etc/redis/redis.conf --appendonly yes
命令说明:
-p6379:6379
: 将容器的 6379 端口映射到宿主机的 6379 端口;-v/usr/local/docker/redis/data:/data
: 将容器中的 /data 数据存储目录, 挂载到宿主机中 /usr/local/docker/redis/data 目录下;-v/usr/local/docker/redis/redis.conf:/etc/redis/redis.conf
: 将容器中 /etc/redis/redis.conf 配置文件,挂载到宿主机的 /usr/local/docker/redis/redis.conf 文件上;redis-server--appendonly yes
: 在容器执行 redis-server 启动命令,并打开 redis 持久化配置; @H_301_38@
命令运行完成后,查看容器是否启动成功:
可以看到 redis 容器已经启动成功了!
3.3 连接刚刚创建好的容器
执行如下命令,连接 redis:
docker run -it redis:alpine redis-cli -h 172.17.0.1
四、快速安装&搭建 MongDB 环境
本节中,我们将学习如何通过 Docker 快速安装与搭建 MongoDB 环境。
4.1 下载 MongoDB 镜像
这里以 mongo 4 版本为例,下载镜像:
docker pull mongo:4
下载完成后,确认一下镜像是否下载成功:
4.2 运行 MongoDB 镜像
下载成功后,运行 mongoDB 镜像:
docker run -d \ --name mongo \ -v /usr/local/docker/mongo/configdb:/data/configdb \ -v /usr/local/docker/mongo/data:/data/db \ -p 27017:27017 \ mongo:4 \ --auth
-d
: 以后台的方式运行;--name mongo
: 指定容器名称为 mongo;-v/usr/local/docker/mongo/configdb:/data/configdb
: 将容器中 /data/configdb 目录挂载到宿主机的 /usr/local/docker/mongo/configdb 目录下;-v/usr/local/docker/mongo/data:/data/db
: 将容器中 /data/db 数据目录挂载到宿主机的 /usr/local/docker/mongo/data 目录下;-p27017:27017
: 将容器的 27017 端口映射到宿主机的 27017 端口; @H_301_38@
执行命令完成后,查看下容器是否启动:
4.3 添加管理员账号
执行命令:
docker exec -it mongo mongo admin
然后,创建一个拥有最高权限 root 账号:
db.createuser({ user: 'admin', pwd: '123456', roles: [ { role: "root", db: "admin" } ] });
创建成功后,你会看到 Successfullyadded user
:
4.4 用新创建的 root 账户连接,测试一下
docker run -it --rm --link mongo:mongo mongo mongo -u admin -p 123456 --authenticationDatabase admin mongo/admin
连接成功后,我们可以执行相关 sql:
显示所有的数据库:
show dbs
使用某个数据库:
use admin
输入命令 exit
,退出连接!
五、快速安装&搭建 Elasticsearch 环境
本节中,我们将学习如何通过 Docker 快速安装与搭建 Elasticsearch 环境。
5.1 下载 Elasticsearch 镜像
这里以 Elasticsearch 6.5.0 为快速安装&搭建 Elasticsearch 环境例:
docker pull elasticsearch:6.5.0
下载完成后,通过 docker images
检查一下镜像是否下载成功:
5.2 先简单运行 Elasticsearch 镜像
下载成功后,简单运行 Elasticsearch 镜像:
docker run -d \ --name es \ -p 9200:9200 -p 9300:9300 \ -e "discovery.type=single-node" -e ES_JAVA_OPTS="-xms200m -Xmx200m" \ elasticsearch:6.5.0
-d
:以后台的方式运行;--name es
:指定容器的名称为 es;-p9200:9200-p9300:9300
将容器的 9200、9300 端口挂载到宿主机的 9200、9300 端口上;-e"discovery.type=single-node"-e ES_JAVA_OPTS="-xms200m -Xmx200m"
:指定为单节点模式,JVM 内存占用 200m @H_301_38@
命令执行完成后,你也可以通过 docker ps
命令来确认下容器是否启动成功。
可以看到 es 容器运行成功了,接下来,进入容器中:
docker exec -it es /bin/bash
安装 analysis-ik 中文分词插件:
./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.5.0/elasticsearch-analysis-ik-6.5.0.zip
PS: es 从 v5.5.1 版本开始支持自带的 es 插件命令来安装,如果你安装的版本不是 6.5.0,需要将命令中的版本号修改一下,具体参考 https://github.com/medcl/elasticsearch-analysis-ik
安装成功后,退出容器:
exit
删除刚刚运行的容器:
docker rm -f es
PS: 当然了,你也可以通过容器的 ID 来删除。
5.3 复制相关文件
# 复制 es 配置文件目录到宿主机指定目录,目标目录你可以根据需要,自行修改 docker cp es:/usr/share/elasticsearch/config /usr/local/docker/es # 复制 es 持久化数据目录到宿主机指定目录 docker cp es:/usr/share/elasticsearch/data /usr/local/docker/es # 复制 es 插件目录到宿主机指定目录 docker cp es:/usr/share/elasticsearch/plugins /usr/local/docker/e
5.4 修改 es 相关配置
进入我们刚刚指定的 config 配置目录,修改 jvm.options
文件:
-xms300m -Xmx300m
PS: 因为小哈测试服务器就 2G 内存,这里我改成了 JVM 内存占用 300m, 如果你的内存够用,可不用改。
修改 elasticsearch.yml
文件, 添加如下配置:
node.name: master http.cors.enabled: true http.cors.allow-origin: "*"
解释一下添加的配置,设置节点为 master 节点,并允许跨域访问,以便后面使用 head 插件图形化界面访问。
5.5 运行 Elasticsearch 容器
docker run -d \ --name es \ -p 9200:9200 -p 9300:9300 \ -v /usr/local/docker/es/config:/usr/share/elasticsearch/config \ -v /usr/local/docker/es/data:/usr/share/elasticsearch/data \ -v /usr/local/docker/es/plugins:/usr/share/elasticsearch/plugins \ elasticsearch:6.5.0
这次,我们额外添加了相关挂载命令:
-v/usr/local/docker/es/config:/usr/share/elasticsearch/config
: 将容器中的 /usr/share/elasticsearch/config 配置目录挂载到宿主机的 /usr/local/docker/es/config 目录下;-v/usr/local/docker/es/data:/usr/share/elasticsearch/data
: 将容器中的 /usr/share/elasticsearch/data 数据目录挂载到宿主机的 /usr/local/docker/es/data 目录下;-v/usr/local/docker/es/plugins:/usr/share/elasticsearch/plugins
:将容器中的 /usr/share/elasticsearch/plugins 插件目录挂载到宿主机的 /usr/local/docker/es/plugins 目录下; @H_301_38@
5.6 测试一下,瞅瞅 es 是否能够正常访问
测试一下,看 es 是否启动成功:
curl http://localhost:9200
OK, 到此 es 的单节点环境就搭建好了!
六、总结
好了,到这里,小哈就已经把常用的测试环境搭建介绍完毕了。如果你还有啥疑问,不妨后台私信我!哈哈,祝您看完本文有所收获!
Docker + Nodejs + Kafka + Redis + MySQL搭建简单秒杀环境
秒杀活动可以说在互联网上随处可见,从12306抢票,到聚划算抢购,我们生活的方方面面都可以看到秒杀的身影。秒杀的架构设计也是对于一个架构师架构设计能力的一次考验。本文的目的并不在于提供一个可以直接落地的设计方案,而是意在提供一个简单的方法,一个思路,使大家能够对于秒杀背后的一些设计有更感性的认识, 并且可以自己亲自动手实践一下。所有的配置及源码都在本文最后的GitHub repository中可以找到。
首先,先简单介绍下本文中会涉及到的一些组件,如下图所示:
JMeter:用JMeter来模拟秒杀活动中大量并发的用户请求
Seckill Service:基于Nodejs使用Express实现的秒杀service,图中的步骤2,3,4都是在这个service中处理的
Redis:一个Redis的docker container,在其中保存一个名为counter的数据来表示当前剩余的库存大小
Kafka: 一个Kafka的docker container,其实这里还有一个zookeeper的docker container,Kafka用zookeeper来存放一些元数据,在程序中并没有涉及到,所以也就不单独列出来说了。Seckill service在更新完Redis之后,会发送一条消息给Kafka表示一次成功的秒杀
Seckill Kafka Consumer: 基于Nodejs的Kafka consumer,会从Kafka中去获取秒杀成功的消息,处理并且存储到MySQL中
MySQL:一个MySQL的docker container,最终秒杀成功的请求都会对应着数据库表中的一条记录
环境搭建
1 . 安装JMeter
从官网下载一个JMeter的binary包,执行bin目录下的jmeter即可启动,启动后如下图新建一个名为Seckill的Thread Group,并且设置在5s内发起2000次并发请求。
在这个Thread Group下新建一个Http Request的Sampler并命名为Seckill,按下图配置host name,port number,http request method以及request path
2 . 安装Redis,Kafka, Zookeeper和MySQL
为了方便搭建环境,这几个组件会以docker container的形式启动。在此之前需要去Docker官网下载并安装Docker Engine,Docker Machine和Docker Compose。如果是在Windows或者Mac上,Docker官网提供Docker For Windows/Docker For Mac安装程序,可以很方便的把这3个组件安装好。
3 . 编写Docker Compose文件
创建一个Seckill项目文件夹,新建一个docker-compose.yml文件,内容如下:
配置文件中一共配置了4个services对应4个docker container,分别是zookeeper,kafka,redis以及mysql。这里有两个地方需要设置成你实际环境的值,一个是kafka配置下面的KAFKA_ADVERTISED_HOST_NAME字段,这个需要设置成本地机器的IP。另一个是MYSQL配置下面的MYSQL_ROOT_PASSWORD,你可以设置成你想要的任何值。
创建好这个文件之后,就可以去命令行项目根目录中执行docker-compose up,docker engine就会把上面配置的这4个组件全部启动起来。
注意:在启动完之后,需要去Kafka容器中创建一个名为CAR_NUMBER的topic,去Redis容器中创建一个名为counter的计数器(设置值为100,代表库存初始值为100),去MySQL容器中创建一个名为seckill的数据表(包含一个自增长的id自段和一个timestamp格式的date字段)。
代码片段
1 . Seckill Service
第1-8行,引入了程序需要用到的对象,nodejs的mvc框架express, redis, kafka等
第10行,利用express提供的方法暴露出一个path为/seckill的POST方法
第12行,定义了一个方法,在54行会调用
第13-22行,新建了一个redis client并且监听error事件
第23行,这行代码非常关键,它的作用是让redis cilent监视redis中的counter值,之后会启动一个事务,如果在事务提交的时候发现有其它client修改了counter值的话,就会放弃这个事务。
第24行,通过redis client的异步方法获取counter的值,因为redis的get操作是原子的,所以在这里不用担心有并发读写的问题。
第25-28行,判断返回的库存值是否大于0,如果大于0,通过client.multi()启动一个事务,通过decr()方法将counter值减1,最后通过exec()方法提交事务;如果小于0,则执行第47行,打印卖完了并且关闭redis client。
第29-46行,这里我们看一下multi.exec()中的这个回调方法。在前面我们已经使用watch对counter进行了监视。如果在事务提交过程中有其它client修改了counter值的话,回调方法中的replies参数就会是null,可以看到第29-31行,程序会打印“可能有冲突”并且再次调用fn方法重试。
如果replies的值不为null,就会使用kafka的producer发送一条message到CAR_NUMBER topic。
2 . seckill_kafka_consumer
这里的代码就比较简单了,会初始化一个kafka consumer监听CAR_NUMBER topic,对于新获取的消息会去MySQL的seckill表里插入一条记录。
操作步骤
启动docker container
启动Seckill_Service
启动seckill_kafka_consumer
启动JMeter发送2000个并发请求
结果 JMeter request results
Redis counter field
MySQL seckill table
可以看到,最后redis中的counter变成0,seckill数据表中会插入100条记录,没有发生超卖或者少卖的情况。当然在实际生产环境场景中,还有许多其它需要考虑的地方,希望此文可以起到一个抛砖引玉的作用,帮助大家更好的理解秒杀场景。
项目GitHub地址: MockSecKill
- 教你在docker 中搭建 PHP8 + Apache 环境的过程
- docker搭建kafka集群的方法实现
- Docker容器搭建Kafka集群的详细过程
- Docker搭建Zookeeper&Kafka集群的实现
- 详解使用docker搭建kafka环境
- 使用Docker搭建Apache Kafka环境的详细过程
docker 入坑 4 搭建 mongoldb、redis、mysql
搭建 mongodb
$ docker run --name mongo -it -d -p 27017:27017 -v ~/docker-data/mongo:/data/db -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=123456 mongo
$ docker exec -it mongo /bin/bash
# mongo -u admin -p 123456
然后我们添加一个用户:
db.createUser({
{
user: "spring",
pwd: "123456",
roles: [
role: "readWrite", db: "demo"
]
}
})
在 java 的配置文件:
spring.data.mongodb.uri=mongodb://spring:123456@localhost:27017/demo
搭建 redis
$ docker run --name redis-server -it -d -p 6379:6379 -v ~/docker-data/redis:/data/db redis redis-server --appendonly yes
$ docker exec -it redis-server redis-cli
搭建 mysql
1、拉取官方镜像(我们这里选择 5.7,如果不写后面的版本号则会自动拉取最新版)
docker pull mysql:5.7 # 拉取 mysql 5.7
docker pull mysql # 拉取最新版mysql镜像
2、一般来说数据库容器不需要建立目录映射
sudo docker run -p 3306:3306 --name mysql -e MYSQL_ROOT_PASSWORD=123456 -d mysql:5.7
- –name:容器名,此处命名为
mysql
- -e:配置信息,此处配置 mysql 的 root 用户的登陆密码
- -p:端口映射,此处映射 主机 3306 端口 到 容器的 3306 端口
- -d:源镜像名,此处为 mysql:5.7
3、如果要建立目录映射
duso docker run -p 3306:3306 --name mysql \
-v /usr/local/docker/mysql/conf:/etc/mysql \
-v /usr/local/docker/mysql/logs:/var/log/mysql \
-v /usr/local/docker/mysql/data:/var/lib/mysql \
-e MYSQL_ROOT_PASSWORD=123456 \
-d mysql:5.7
- -v:主机和容器的目录映射关系,":" 前为主机目录,之后为容器目录
4、连接 mysql
sudo docker exec -it mysql /bin/bash
mysql -uroot -p123456
5、使用 java 的 jdbc 测试
1 import java.sql.*;
2
3 public class JdbcTest {
4 public static void main(String[] args) {
5 Connection connection = null;
6 PreparedStatement preparedStatement = null;
7 ResultSet resultSet = null;
8 try
9 {
10 //加载数据驱动
11 Class.forName("com.mysql.jdbc.Driver");
12 //通过驱动管理类获取数据库连接
13 connection = DriverManager.getConnection("jdbc:mysql://127.0.0.1:3306/test?characterEncoding=utf-8","root","123456");
14 System.out.println("创建数据库连接成功");
15 //定义sql语句?表示占位符
16 String sql = "select * from user where username = ?";
17 //获取预处理statement
18 preparedStatement = connection.prepareStatement(sql);
19 //设置参数,第一个参数为sql语句中参数的序号(从1开始),第二个参数为设置的参数值
20 preparedStatement.setString(1,"zhangsan");
21 //向数据库发出sql查询,查询出结果集
22 resultSet = preparedStatement.executeQuery();
23 //遍历查找结果集
24 while (resultSet.next()){
25 System.out.println(resultSet.getString("id") + ""
26 + resultSet.getString("username"));
27 }
28 } catch (Exception e) {
29 e.printStackTrace();
30 }finally {
31 //释放资源
32 if(resultSet != null){
33 try{
34 preparedStatement.close();
35 }catch (SQLException e){
36 e.printStackTrace();
37 }
38 }
39 if(connection != null){
40 try{
41 connection.close();
42 }catch (SQLException e){
43 e.printStackTrace();
44 }
45 }
46 }
47 }
48 }
5、数据库:
6、驱动
mysql-connector-java-5.1.36
7、在 idea 中添加 lib 文件夹,在文件夹 lib 中添加驱动的 jar 包,然后
下面的方式待验证:
1、在宿主机上创建 /mysql/data 和 /mysql/conf
2、docker run --name mysql -d --rm -v /home/mantishell/mysql/conf:/etc/mysql/conf.d -v /home/mantishell/mysql/data:/var/lib/mysql -p 3306:3306 -e MYSQL_ROOT_PASSWORD=123456 mysql
3、ALTER USER ''root''@''%'' IDENTIFIED WITH mysql_native_password BY ''123456'';
docker 入坑4 搭建mongoldb、redis、mysql
搭建mongodb
$ docker run --name mongo -it -d -p 27017:27017 -v ~/docker-data/mongo:/data/db -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=123456 mongo
$ docker exec -it mongo /bin/bash
# mongo -u admin -p 123456
然后我们添加一个用户:
db.createUser({
{
user: "spring",
pwd: "123456",
roles: [
role: "readWrite", db: "demo"
]
}
})
在java的配置文件:
spring.data.mongodb.uri=mongodb://spring:123456@localhost:27017/demo
搭建redis
$ docker run --name redis-server -it -d -p 6379:6379 -v ~/docker-data/redis:/data/db redis redis-server --appendonly yes
$ docker exec -it redis-server redis-cli
搭建mysql
1、拉取官方镜像(我们这里选择5.7,如果不写后面的版本号则会自动拉取最新版)
docker pull mysql:5.7 # 拉取 mysql 5.7
docker pull mysql # 拉取最新版mysql镜像
2、一般来说数据库容器不需要建立目录映射
sudo docker run -p 3306:3306 --name mysql -e MYSQL_ROOT_PASSWORD=123456 -d mysql:5.7
- –name:容器名,此处命名为
mysql
- -e:配置信息,此处配置mysql的root用户的登陆密码
- -p:端口映射,此处映射 主机3306端口 到 容器的3306端口
- -d:源镜像名,此处为 mysql:5.7
3、如果要建立目录映射
duso docker run -p 3306:3306 --name mysql \
-v /usr/local/docker/mysql/conf:/etc/mysql \
-v /usr/local/docker/mysql/logs:/var/log/mysql \
-v /usr/local/docker/mysql/data:/var/lib/mysql \
-e MYSQL_ROOT_PASSWORD=123456 \
-d mysql:5.7
- -v:主机和容器的目录映射关系,":"前为主机目录,之后为容器目录
4、连接mysql
sudo docker exec -it mysql /bin/bash
mysql -uroot -p123456
5、使用java的jdbc测试
1 import java.sql.*;
2
3 public class JdbcTest {
4 public static void main(String[] args) {
5 Connection connection = null;
6 PreparedStatement preparedStatement = null;
7 ResultSet resultSet = null;
8 try
9 {
10 //加载数据驱动
11 Class.forName("com.mysql.jdbc.Driver");
12 //通过驱动管理类获取数据库连接
13 connection = DriverManager.getConnection("jdbc:mysql://127.0.0.1:3306/test?characterEncoding=utf-8","root","123456");
14 System.out.println("创建数据库连接成功");
15 //定义sql语句?表示占位符
16 String sql = "select * from user where username = ?";
17 //获取预处理statement
18 preparedStatement = connection.prepareStatement(sql);
19 //设置参数,第一个参数为sql语句中参数的序号(从1开始),第二个参数为设置的参数值
20 preparedStatement.setString(1,"zhangsan");
21 //向数据库发出sql查询,查询出结果集
22 resultSet = preparedStatement.executeQuery();
23 //遍历查找结果集
24 while (resultSet.next()){
25 System.out.println(resultSet.getString("id") + ""
26 + resultSet.getString("username"));
27 }
28 } catch (Exception e) {
29 e.printStackTrace();
30 }finally {
31 //释放资源
32 if(resultSet != null){
33 try{
34 preparedStatement.close();
35 }catch (SQLException e){
36 e.printStackTrace();
37 }
38 }
39 if(connection != null){
40 try{
41 connection.close();
42 }catch (SQLException e){
43 e.printStackTrace();
44 }
45 }
46 }
47 }
48 }
5、数据库:
6、驱动
mysql-connector-java-5.1.36
7、在idea中添加lib文件夹,在文件夹lib中添加驱动的jar包,然后
下面的方式待验证:
1、在宿主机上创建/mysql/data和/mysql/conf
2、docker run --name mysql -d --rm -v /home/mantishell/mysql/conf:/etc/mysql/conf.d -v /home/mantishell/mysql/data:/var/lib/mysql -p 3306:3306 -e MYSQL_ROOT_PASSWORD=123456 mysql
3、ALTER USER ''root''@''%'' IDENTIFIED WITH mysql_native_password BY ''123456'';
docker 安装 mongodb 和 redis
一、安装 mongodb
docker pull mongo
docker run -p 27017:27017 -d --name mongodb01 mongo
docker run -p 27017:27017 -v ~/docker/mongo/config:/data/configdb -v ~/docker/mongo/data/db:/data/db -d --name mongodb01 mongo : -v ~/docker/mongo/data:/data/db : 将主机中当前目录下的 db 挂载到容器的 /data/db,作为 mongo 数据存储目录
最后可以使用 Robo 3T 客户端来链接 mongodb
二、安装 redis
docker pull redis
mkdir -p ~/docker/redis/data ~/docker/redis/conf
cd ~/docker/redis/conf
vim redis.conf
# Redis configuration file example.
#
# Note that in order to read the configuration file, Redis must be
# started with the file path as first argument:
#
# ./redis-server /path/to/redis.conf
# Note on units: when memory size is needed, it is possible to specify
# it in the usual form of 1k 5GB 4M and so forth:
#
# 1k => 1000 bytes
# 1kb => 1024 bytes
# 1m => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# units are case insensitive so 1GB 1Gb 1gB are all the same.
################################## INCLUDES ###################################
# Include one or more other config files here. This is useful if you
# have a standard template that goes to all Redis servers but also need
# to customize a few per-server settings. Include files can include
# other files, so use this wisely.
#
# Notice option "include" won''t be rewritten by command "CONFIG REWRITE"
# from admin or Redis Sentinel. Since Redis always uses the last processed
# line as value of a configuration directive, you''d better put includes
# at the beginning of this file to avoid overwriting config change at runtime.
#
# If instead you are interested in using includes to override configuration
# options, it is better to use include as the last line.
#
# include /path/to/local.conf
# include /path/to/other.conf
################################## MODULES #####################################
# Load modules at startup. If the server is not able to load modules
# it will abort. It is possible to use multiple loadmodule directives.
#
# loadmodule /path/to/my_module.so
# loadmodule /path/to/other_module.so
################################## NETWORK #####################################
# By default, if no "bind" configuration directive is specified, Redis listens
# for connections from all the network interfaces available on the server.
# It is possible to listen to just one or multiple selected interfaces using
# the "bind" configuration directive, followed by one or more IP addresses.
#
# Examples:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1 ::1
#
# ~~~ WARNING ~~~ If the computer running Redis is directly exposed to the
# internet, binding to all the interfaces is dangerous and will expose the
# instance to everybody on the internet. So by default we uncomment the
# following bind directive, that will force Redis to listen only into
# the IPv4 loopback interface address (this means Redis will be able to
# accept connections only from clients running into the same computer it
# is running).
#
# IF YOU ARE SURE YOU WANT YOUR INSTANCE TO LISTEN TO ALL THE INTERFACES
# JUST COMMENT THE FOLLOWING LINE.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
bind 127.0.0.1
# Protected mode is a layer of security protection, in order to avoid that
# Redis instances left open on the internet are accessed and exploited.
#
# When protected mode is on and if:
#
# 1) The server is not binding explicitly to a set of addresses using the
# "bind" directive.
# 2) No password is configured.
#
# The server only accepts connections from clients connecting from the
# IPv4 and IPv6 loopback addresses 127.0.0.1 and ::1, and from Unix domain
# sockets.
#
# By default protected mode is enabled. You should disable it only if
# you are sure you want clients from other hosts to connect to Redis
# even if no authentication is configured, nor a specific set of interfaces
# are explicitly listed using the "bind" directive.
protected-mode yes
# Accept connections on the specified port, default is 6379 (IANA #815344).
# If port 0 is specified Redis will not listen on a TCP socket.
port 6379
# TCP listen() backlog.
#
# In high requests-per-second environments you need an high backlog in order
# to avoid slow clients connections issues. Note that the Linux kernel
# will silently truncate it to the value of /proc/sys/net/core/somaxconn so
# make sure to raise both the value of somaxconn and tcp_max_syn_backlog
# in order to get the desired effect.
tcp-backlog 511
# Unix socket.
#
# Specify the path for the Unix socket that will be used to listen for
# incoming connections. There is no default, so Redis will not listen
# on a unix socket when not specified.
#
# unixsocket /tmp/redis.sock
# unixsocketperm 700
# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
# TCP keepalive.
#
# If non-zero, use SO_KEEPALIVE to send TCP ACKs to clients in absence
# of communication. This is useful for two reasons:
#
# 1) Detect dead 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 300 seconds, which is the new
# Redis default starting with Redis 3.2.1.
tcp-keepalive 300
################################# GENERAL #####################################
# By default Redis does not run as a daemon. Use ''yes'' if you need it.
# Note that Redis will write a pid file in /var/run/redis.pid when daemonized.
daemonize no
# If you run Redis from upstart or systemd, Redis can interact with your
# supervision tree. Options:
# supervised no - no supervision interaction
# supervised upstart - signal upstart by putting Redis into SIGSTOP mode
# supervised systemd - signal systemd by writing READY=1 to $NOTIFY_SOCKET
# supervised auto - detect upstart or systemd method based on
# UPSTART_JOB or NOTIFY_SOCKET environment variables
# Note: these supervision methods only signal "process is ready."
# They do not enable continuous liveness pings back to your supervisor.
supervised no
# If a pid file is specified, Redis writes it where specified at startup
# and removes it at exit.
#
# When the server runs non daemonized, no pid file is created if none is
# specified in the configuration. When the server is daemonized, the pid file
# is used even if not specified, defaulting to "/var/run/redis.pid".
#
# Creating a pid file is best effort: if Redis is not able to create it
# nothing bad happens, the server will start and run normally.
pidfile /var/run/redis_6379.pid
# Specify the server verbosity level.
# This can be one of:
# debug (a lot of information, useful for development/testing)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (moderately verbose, what you want in production probably)
# warning (only very important / critical messages are logged)
loglevel notice
# Specify the log file name. Also the empty string can be used to force
# Redis to log on the standard output. Note that if you use standard
# output for logging but daemonize, logs will be sent to /dev/null
logfile ""
# To enable logging to the system logger, just set ''syslog-enabled'' to yes,
# and optionally update the other syslog parameters to suit your needs.
# syslog-enabled no
# Specify the syslog identity.
# syslog-ident redis
# Specify the syslog facility. Must be USER or between LOCAL0-LOCAL7.
# syslog-facility local0
# Set the number of databases. The default database is DB 0, you can select
# a different one on a per-connection basis using SELECT <dbid> where
# dbid is a number between 0 and ''databases''-1
databases 16
# By default Redis shows an ASCII art logo only when started to log to the
# standard output and if the standard output is a TTY. Basically this means
# that normally a logo is displayed only in interactive sessions.
#
# However it is possible to force the pre-4.0 behavior and always show a
# ASCII art logo in startup logs by setting the following option to yes.
always-show-logo yes
################################ SNAPSHOTTING ################################
#
# Save the DB on disk:
#
# save <seconds> <changes>
#
# Will save the DB if both the given number of seconds and the given
# number of write operations against the DB occurred.
#
# In the example below the behaviour will be to save:
# after 900 sec (15 min) if at least 1 key changed
# after 300 sec (5 min) if at least 10 keys changed
# after 60 sec if at least 10000 keys changed
#
# Note: you can disable saving completely by commenting out all "save" lines.
#
# It is also possible to remove all the previously configured save
# points by adding a save directive with a single empty string argument
# like in the following example:
#
# save ""
save 900 1
save 300 10
save 60 10000
# By default Redis will stop accepting writes if RDB snapshots are enabled
# (at least one save point) and the latest background save failed.
# This will make the user aware (in a hard way) that data is not persisting
# on disk properly, otherwise chances are that no one will notice and some
# disaster will happen.
#
# If the background saving process will start working again Redis will
# automatically allow writes again.
#
# However if you have setup your proper monitoring of the Redis server
# and persistence, you may want to disable this feature so that Redis will
# continue to work as usual even if there are problems with disk,
# permissions, and so forth.
stop-writes-on-bgsave-error yes
# Compress string objects using LZF when dump .rdb databases?
# For default that''s set to ''yes'' as it''s almost always a win.
# If you want to save some CPU in the saving child set it to ''no'' but
# the dataset will likely be bigger if you have compressible values or keys.
rdbcompression yes
# Since version 5 of RDB a CRC64 checksum is placed at the end of the file.
# This makes the format more resistant to corruption but there is a performance
# hit to pay (around 10%) when saving and loading RDB files, so you can disable it
# for maximum performances.
#
# RDB files created with checksum disabled have a checksum of zero that will
# tell the loading code to skip the check.
rdbchecksum yes
# The filename where to dump the DB
dbfilename dump.rdb
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the ''dbfilename'' configuration directive.
#
# The Append Only File will also be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir ./
################################# REPLICATION #################################
# Master-Replica replication. Use replicaof to make a Redis instance a copy of
# another Redis server. A few things to understand ASAP about Redis replication.
#
# +------------------+ +---------------+
# | Master | ---> | Replica |
# | (receive writes) | | (exact copy) |
# +------------------+ +---------------+
#
# 1) Redis replication is asynchronous, but you can configure a master to
# stop accepting writes if it appears to be not connected with at least
# a given number of replicas.
# 2) Redis replicas are able to perform a partial resynchronization with the
# master if the replication link is lost for a relatively small amount of
# time. You may want to configure the replication backlog size (see the next
# sections of this file) with a sensible value depending on your needs.
# 3) Replication is automatic and does not need user intervention. After a
# network partition replicas automatically try to reconnect to masters
# and resynchronize with them.
#
# replicaof <masterip> <masterport>
# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the replica to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the replica request.
#
# masterauth <master-password>
# When a replica loses its connection with the master, or when the replication
# is still in progress, the replica can act in two different ways:
#
# 1) if replica-serve-stale-data is set to ''yes'' (the default) the replica will
# still reply to client requests, possibly with out of date data, or the
# data set may just be empty if this is the first synchronization.
#
# 2) if replica-serve-stale-data is set to ''no'' the replica will reply with
# an error "SYNC with master in progress" to all the kind of commands
# but to INFO, replicaOF, AUTH, PING, SHUTDOWN, REPLCONF, ROLE, CONFIG,
# SUBSCRIBE, UNSUBSCRIBE, PSUBSCRIBE, PUNSUBSCRIBE, PUBLISH, PUBSUB,
# COMMAND, POST, HOST: and LATENCY.
#
replica-serve-stale-data yes
# You can configure a replica instance to accept writes or not. Writing against
# a replica instance may be useful to store some ephemeral data (because data
# written on a replica will be easily deleted after resync with the master) but
# may also cause problems if clients are writing to it because of a
# misconfiguration.
#
# Since Redis 2.6 by default replicas are read-only.
#
# Note: read only replicas 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 replica 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 replicas using ''rename-command'' to shadow all the
# administrative / dangerous commands.
replica-read-only yes
# Replication SYNC strategy: disk or socket.
#
# -------------------------------------------------------
# WARNING: DISKLESS REPLICATION IS EXPERIMENTAL CURRENTLY
# -------------------------------------------------------
#
# New replicas and reconnecting replicas that are not able to continue the replication
# process just receiving differences, need to do what is called a "full
# synchronization". An RDB file is transmitted from the master to the replicas.
# The transmission can happen in two different ways:
#
# 1) Disk-backed: The Redis master creates a new process that writes the RDB
# file on disk. Later the file is transferred by the parent
# process to the replicas incrementally.
# 2) Diskless: The Redis master creates a new process that directly writes the
# RDB file to replica sockets, without touching the disk at all.
#
# With disk-backed replication, while the RDB file is generated, more replicas
# can be queued and served with the RDB file as soon as the current child producing
# the RDB file finishes its work. With diskless replication instead once
# the transfer starts, new replicas arriving will be queued and a new transfer
# will start when the current one terminates.
#
# When diskless replication is used, the master waits a configurable amount of
# time (in seconds) before starting the transfer in the hope that multiple replicas
# will arrive and the transfer can be parallelized.
#
# With slow disks and fast (large bandwidth) networks, diskless replication
# works better.
repl-diskless-sync no
# When diskless replication is enabled, it is possible to configure the delay
# the server waits in order to spawn the child that transfers the RDB via socket
# to the replicas.
#
# This is important since once the transfer starts, it is not possible to serve
# new replicas arriving, that will be queued for the next RDB transfer, so the server
# waits a delay in order to let more replicas arrive.
#
# The delay is specified in seconds, and by default is 5 seconds. To disable
# it entirely just set it to 0 seconds and the transfer will start ASAP.
repl-diskless-sync-delay 5
# Replicas send PINGs to server in a predefined interval. It''s possible to change
# this interval with the repl_ping_replica_period option. The default value is 10
# seconds.
#
# repl-ping-replica-period 10
# The following option sets the replication timeout for:
#
# 1) Bulk transfer I/O during SYNC, from the point of view of replica.
# 2) Master timeout from the point of view of replicas (data, pings).
# 3) Replica 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-replica-period otherwise a timeout will be detected
# every time there is low traffic between the master and the replica.
#
# repl-timeout 60
# Disable TCP_NODELAY on the replica socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to replicas. But this can add a delay for
# the data to appear on the replica side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the replica 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 replicas are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
# Set the replication backlog size. The backlog is a buffer that accumulates
# replica data when replicas are disconnected for some time, so that when a replica
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the replica missed while
# disconnected.
#
# The bigger the replication backlog, the longer the time the replica can be
# disconnected and later be able to perform a partial resynchronization.
#
# The backlog is only allocated once there is at least a replica connected.
#
# repl-backlog-size 1mb
# After a master has no longer connected replicas 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 replica disconnected, for
# the backlog buffer to be freed.
#
# Note that replicas never free the backlog for timeout, since they may be
# promoted to masters later, and should be able to correctly "partially
# resynchronize" with the replicas: hence they should always accumulate backlog.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600
# The replica priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a replica to promote into a
# master if the master is no longer working correctly.
#
# A replica with a low priority number is considered better for promotion, so
# for instance if there are three replicas with priority 10, 100, 25 Sentinel will
# pick the one with priority 10, that is the lowest.
#
# However a special priority of 0 marks the replica as not able to perform the
# role of master, so a replica with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 100.
replica-priority 100
# It is possible for a master to stop accepting writes if there are less than
# N replicas connected, having a lag less or equal than M seconds.
#
# The N replicas 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 replica, that is usually sent every second.
#
# This option does not GUARANTEE that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough replicas
# are available, to the specified number of seconds.
#
# For example to require at least 3 replicas with a lag <= 10 seconds use:
#
# min-replicas-to-write 3
# min-replicas-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-replicas-to-write is set to 0 (feature disabled) and
# min-replicas-max-lag is set to 10.
# A Redis master is able to list the address and port of the attached
# replicas in different ways. For example the "INFO replication" section
# offers this information, which is used, among other tools, by
# Redis Sentinel in order to discover replica instances.
# Another place where this info is available is in the output of the
# "ROLE" command of a master.
#
# The listed IP and address normally reported by a replica is obtained
# in the following way:
#
# IP: The address is auto detected by checking the peer address
# of the socket used by the replica to connect with the master.
#
# Port: The port is communicated by the replica during the replication
# handshake, and is normally the port that the replica is using to
# listen for connections.
#
# However when port forwarding or Network Address Translation (NAT) is
# used, the replica may be actually reachable via different IP and port
# pairs. The following two options can be used by a replica in order to
# report to its master a specific set of IP and port, so that both INFO
# and ROLE will report those values.
#
# There is no need to use both the options if you need to override just
# the port or the IP address.
#
# replica-announce-ip 5.5.5.5
# replica-announce-port 1234
################################## SECURITY ###################################
# 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.
#
# 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 replicas may cause problems.
################################### CLIENTS ####################################
# 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).
#
# Once the limit is reached Redis will close all the new connections sending
# an error ''max number of clients reached''.
#
# maxclients 10000
############################## MEMORY MANAGEMENT ################################
# Set a memory usage limit to the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys
# according to the eviction policy selected (see maxmemory-policy).
#
# If Redis can''t remove keys according to the policy, or if the policy is
# set to ''noeviction'', Redis will start to reply with errors to commands
# that would use more memory, like SET, LPUSH, and so on, and will continue
# to reply to read-only commands like GET.
#
# This option is usually useful when using Redis as an LRU or LFU cache, or to
# set a hard memory limit for an instance (using the ''noeviction'' policy).
#
# WARNING: If you have replicas attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the replicas 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 replicas 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 replicas attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for replica
# output buffers (but this is not needed if the policy is ''noeviction'').
#
# maxmemory <bytes>
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> Evict using approximated LRU among the keys with an expire set.
# allkeys-lru -> Evict any key using approximated LRU.
# volatile-lfu -> Evict using approximated LFU among the keys with an expire set.
# allkeys-lfu -> Evict any key using approximated LFU.
# volatile-random -> Remove a random key among the ones 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 evict anything, just return an error on write operations.
#
# LRU means Least Recently Used
# LFU means Least Frequently Used
#
# Both LRU, LFU and volatile-ttl are implemented using approximated
# randomized algorithms.
#
# Note: with any of the above policies, Redis will return an error on write
# operations, when there are no suitable keys for eviction.
#
# At the date of writing these 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, LFU 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 more CPU. 3 is faster but not very accurate.
#
# maxmemory-samples 5
# Starting from Redis 5, by default a replica will ignore its maxmemory setting
# (unless it is promoted to master after a failover or manually). It means
# that the eviction of keys will be just handled by the master, sending the
# DEL commands to the replica as keys evict in the master side.
#
# This behavior ensures that masters and replicas stay consistent, and is usually
# what you want, however if your replica is writable, or you want the replica to have
# a different memory setting, and you are sure all the writes performed to the
# replica are idempotent, then you may change this default (but be sure to understand
# what you are doing).
#
# Note that since the replica by default does not evict, it may end using more
# memory than the one set via maxmemory (there are certain buffers that may
# be larger on the replica, or data structures may sometimes take more memory and so
# forth). So make sure you monitor your replicas and make sure they have enough
# memory to never hit a real out-of-memory condition before the master hits
# the configured maxmemory setting.
#
# replica-ignore-maxmemory yes
############################# LAZY FREEING ####################################
# Redis has two primitives to delete keys. One is called DEL and is a blocking
# deletion of the object. It means that the server stops processing new commands
# in order to reclaim all the memory associated with an object in a synchronous
# way. If the key deleted is associated with a small object, the time needed
# in order to execute the DEL command is very small and comparable to most other
# O(1) or O(log_N) commands in Redis. However if the key is associated with an
# aggregated value containing millions of elements, the server can block for
# a long time (even seconds) in order to complete the operation.
#
# For the above reasons Redis also offers non blocking deletion primitives
# such as UNLINK (non blocking DEL) and the ASYNC option of FLUSHALL and
# FLUSHDB commands, in order to reclaim memory in background. Those commands
# are executed in constant time. Another thread will incrementally free the
# object in the background as fast as possible.
#
# DEL, UNLINK and ASYNC option of FLUSHALL and FLUSHDB are user-controlled.
# It''s up to the design of the application to understand when it is a good
# idea to use one or the other. However the Redis server sometimes has to
# delete keys or flush the whole database as a side effect of other operations.
# Specifically Redis deletes objects independently of a user call in the
# following scenarios:
#
# 1) On eviction, because of the maxmemory and maxmemory policy configurations,
# in order to make room for new data, without going over the specified
# memory limit.
# 2) Because of expire: when a key with an associated time to live (see the
# EXPIRE command) must be deleted from memory.
# 3) Because of a side effect of a command that stores data on a key that may
# already exist. For example the RENAME command may delete the old key
# content when it is replaced with another one. Similarly SUNIONSTORE
# or SORT with STORE option may delete existing keys. The SET command
# itself removes any old content of the specified key in order to replace
# it with the specified string.
# 4) During replication, when a replica performs a full resynchronization with
# its master, the content of the whole database is removed in order to
# load the RDB file just transferred.
#
# In all the above cases the default is to delete objects in a blocking way,
# like if DEL was called. However you can configure each case specifically
# in order to instead release memory in a non-blocking way like if UNLINK
# was called, using the following configuration directives:
lazyfree-lazy-eviction no
lazyfree-lazy-expire no
lazyfree-lazy-server-del no
replica-lazy-flush no
############################## 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 of waiting 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
# An AOF file may be found to be truncated at the end during the Redis
# startup process, when the AOF data gets loaded back into memory.
# This may happen when the system where Redis is running
# crashes, especially when an ext4 filesystem is mounted without the
# data=ordered option (however this can''t happen when Redis itself
# crashes or aborts but the operating system still works correctly).
#
# Redis can either exit with an error when this happens, or load as much
# data as possible (the default now) and start if the AOF file is found
# to be truncated at the end. The following option controls this behavior.
#
# If aof-load-truncated is set to yes, a truncated AOF file is loaded and
# the Redis server starts emitting a log to inform the user of the event.
# Otherwise if the option is set to no, the server aborts with an error
# and refuses to start. When the option is set to no, the user requires
# to fix the AOF file using the "redis-check-aof" utility before to restart
# the server.
#
# Note that if the AOF file will be found to be corrupted in the middle
# the server will still exit with an error. This option only applies when
# Redis will try to read more data from the AOF file but not enough bytes
# will be found.
aof-load-truncated yes
# When rewriting the AOF file, Redis is able to use an RDB preamble in the
# AOF file for faster rewrites and recoveries. When this option is turned
# on the rewritten AOF file is composed of two different stanzas:
#
# [RDB file][AOF tail]
#
# When loading Redis recognizes that the AOF file starts with the "REDIS"
# string and loads the prefixed RDB file, and continues loading the AOF
# tail.
aof-use-rdb-preamble yes
################################ 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 exceeds 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 command was
# already issued by the script but the user doesn''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 CLUSTER ###############################
#
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# WARNING EXPERIMENTAL: Redis Cluster is considered to be stable code, however
# in order to mark it as "mature" we need to wait for a non trivial percentage
# of users to deploy it in production.
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
#
# Normal Redis instances can''t be part of a Redis Cluster; only nodes that are
# started as cluster nodes can. In order to start a Redis instance as a
# cluster node enable the cluster support uncommenting the following:
#
# 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 do 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 replica of a failing master will avoid to start a failover if its data
# looks too old.
#
# There is no simple way for a replica to actually have an exact measure of
# its "data age", so the following two checks are performed:
#
# 1) If there are multiple replicas able to failover, they exchange messages
# in order to try to give an advantage to the replica with the best
# replication offset (more data from the master processed).
# Replicas 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 replica 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 replica will not try to failover
# at all.
#
# The point "2" can be tuned by user. Specifically a replica will not perform
# the failover if, since the last interaction with the master, the time
# elapsed is greater than:
#
# (node-timeout * replica-validity-factor) + repl-ping-replica-period
#
# So for example if node-timeout is 30 seconds, and the replica-validity-factor
# is 10, and assuming a default repl-ping-replica-period of 10 seconds, the
# replica will not try to failover if it was not able to talk with the master
# for longer than 310 seconds.
#
# A large replica-validity-factor may allow replicas with too old data to failover
# a master, while a too small value may prevent the cluster from being able to
# elect a replica at all.
#
# For maximum availability, it is possible to set the replica-validity-factor
# to a value of 0, which means, that replicas 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-replica-validity-factor 10
# Cluster replicas are able to migrate to orphaned masters, that are masters
# that are left without working replicas. 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 replicas.
#
# Replicas migrate to orphaned masters only if there are still at least a
# given number of other working replicas for their old master. This number
# is the "migration barrier". A migration barrier of 1 means that a replica
# will migrate only if there is at least 1 other working replica for its master
# and so forth. It usually reflects the number of replicas you want for every
# master in your cluster.
#
# Default is 1 (replicas migrate only if their masters remain with at least
# one replica). 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
# By default Redis Cluster nodes stop accepting queries if they detect there
# is at least an hash slot uncovered (no available node is serving it).
# This way if the cluster is partially down (for example a range of hash slots
# are no longer covered) all the cluster becomes, eventually, unavailable.
# It automatically returns available as soon as all the slots are covered again.
#
# However sometimes you want the subset of the cluster which is working,
# to continue to accept queries for the part of the key space that is still
# covered. In order to do so, just set the cluster-require-full-coverage
# option to no.
#
# cluster-require-full-coverage yes
# This option, when set to yes, prevents replicas from trying to failover its
# master during master failures. However the master can still perform a
# manual failover, if forced to do so.
#
# This is useful in different scenarios, especially in the case of multiple
# data center operations, where we want one side to never be promoted if not
# in the case of a total DC failure.
#
# cluster-replica-no-failover no
# In order to setup your cluster make sure to read the documentation
# available at http://redis.io web site.
########################## CLUSTER DOCKER/NAT support ########################
# In certain deployments, Redis Cluster nodes address discovery fails, because
# addresses are NAT-ted or because ports are forwarded (the typical case is
# Docker and other containers).
#
# In order to make Redis Cluster working in such environments, a static
# configuration where each node knows its public address is needed. The
# following two options are used for this scope, and are:
#
# * cluster-announce-ip
# * cluster-announce-port
# * cluster-announce-bus-port
#
# Each instruct the node about its address, client port, and cluster message
# bus port. The information is then published in the header of the bus packets
# so that other nodes will be able to correctly map the address of the node
# publishing the information.
#
# If the above options are not used, the normal Redis Cluster auto-detection
# will be used instead.
#
# Note that when remapped, the bus port may not be at the fixed offset of
# clients port + 10000, so you can specify any port and bus-port depending
# on how they get remapped. If the bus-port is not set, a fixed offset of
# 10000 will be used as usually.
#
# Example:
#
# cluster-announce-ip 10.1.1.5
# cluster-announce-port 6379
# cluster-announce-bus-port 6380
################################## 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
################################ LATENCY MONITOR ##############################
# The Redis latency monitoring subsystem samples different operations
# at runtime in order to collect data related to possible sources of
# latency of a Redis instance.
#
# Via the LATENCY command this information is available to the user that can
# print graphs and obtain reports.
#
# The system only logs operations that were performed in a time equal or
# greater than the amount of milliseconds specified via the
# latency-monitor-threshold configuration directive. When its value is set
# to zero, the latency monitor is turned off.
#
# By default latency monitoring is disabled since it is mostly not needed
# if you don''t have latency issues, and collecting data has a performance
# impact, that while very small, can be measured under big load. Latency
# monitoring can easily be enabled at runtime using the command
# "CONFIG SET latency-monitor-threshold <milliseconds>" if needed.
latency-monitor-threshold 0
############################# EVENT NOTIFICATION ##############################
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/notifications
#
# 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
# of zero or multiple characters. The empty string means that notifications
# are disabled.
#
# 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
# Lists are also encoded in a special way to save a lot of space.
# The number of entries allowed per internal list node can be specified
# as a fixed maximum size or a maximum number of elements.
# For a fixed maximum size, use -5 through -1, meaning:
# -5: max size: 64 Kb <-- not recommended for normal workloads
# -4: max size: 32 Kb <-- not recommended
# -3: max size: 16 Kb <-- probably not recommended
# -2: max size: 8 Kb <-- good
# -1: max size: 4 Kb <-- good
# Positive numbers mean store up to _exactly_ that number of elements
# per list node.
# The highest performing option is usually -2 (8 Kb size) or -1 (4 Kb size),
# but if your use case is unique, adjust the settings as necessary.
list-max-ziplist-size -2
# Lists may also be compressed.
# Compress depth is the number of quicklist ziplist nodes from *each* side of
# the list to *exclude* from compression. The head and tail of the list
# are always uncompressed for fast push/pop operations. Settings are:
# 0: disable all list compression
# 1: depth 1 means "don''t start compressing until after 1 node into the list,
# going from either the head or tail"
# So: [head]->node->node->...->node->[tail]
# [head], [tail] will always be uncompressed; inner nodes will compress.
# 2: [head]->[next]->node->node->...->node->[prev]->[tail]
# 2 here means: don''t compress head or head->next or tail->prev or tail,
# but compress all nodes between them.
# 3: [head]->[next]->[next]->node->node->...->node->[prev]->[prev]->[tail]
# etc.
list-compress-depth 0
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happen 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
# Streams macro node max size / items. The stream data structure is a radix
# tree of big nodes that encode multiple items inside. Using this configuration
# it is possible to configure how big a single node can be in bytes, and the
# maximum number of items it may contain before switching to a new node when
# appending new stream entries. If any of the following settings are set to
# zero, the limit is ignored, so for instance it is possible to set just a
# max entires limit by setting max-bytes to 0 and max-entries to the desired
# value.
stream-node-max-bytes 4096
stream-node-max-entries 100
# 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
# actively rehash 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 from 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 including MONITOR clients
# replica -> replica 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 replica clients, since
# subscribers and replicas 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 replica 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
# Client query buffers accumulate new commands. They are limited to a fixed
# amount by default in order to avoid that a protocol desynchronization (for
# instance due to a bug in the client) will lead to unbound memory usage in
# the query buffer. However you can configure it here if you have very special
# needs, such us huge multi/exec requests or alike.
#
# client-query-buffer-limit 1gb
# In the Redis protocol, bulk requests, that are, elements representing single
# strings, are normally limited ot 512 mb. However you can change this limit
# here.
#
# proto-max-bulk-len 512mb
# 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 according 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
# Normally it is useful to have an HZ value which is proportional to the
# number of clients connected. This is useful in order, for instance, to
# avoid too many clients are processed for each background task invocation
# in order to avoid latency spikes.
#
# Since the default HZ value by default is conservatively set to 10, Redis
# offers, and enables by default, the ability to use an adaptive HZ value
# which will temporary raise when there are many connected clients.
#
# When dynamic HZ is enabled, the actual configured HZ will be used as
# as a baseline, but multiples of the configured HZ value will be actually
# used as needed once more clients are connected. In this way an idle
# instance will use very little CPU time while a busy instance will be
# more responsive.
dynamic-hz yes
# 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
# When redis saves RDB 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.
rdb-save-incremental-fsync yes
# Redis LFU eviction (see maxmemory setting) can be tuned. However it is a good
# idea to start with the default settings and only change them after investigating
# how to improve the performances and how the keys LFU change over time, which
# is possible to inspect via the OBJECT FREQ command.
#
# There are two tunable parameters in the Redis LFU implementation: the
# counter logarithm factor and the counter decay time. It is important to
# understand what the two parameters mean before changing them.
#
# The LFU counter is just 8 bits per key, it''s maximum value is 255, so Redis
# uses a probabilistic increment with logarithmic behavior. Given the value
# of the old counter, when a key is accessed, the counter is incremented in
# this way:
#
# 1. A random number R between 0 and 1 is extracted.
# 2. A probability P is calculated as 1/(old_value*lfu_log_factor+1).
# 3. The counter is incremented only if R < P.
#
# The default lfu-log-factor is 10. This is a table of how the frequency
# counter changes with a different number of accesses with different
# logarithmic factors:
#
# +--------+------------+------------+------------+------------+------------+
# | factor | 100 hits | 1000 hits | 100K hits | 1M hits | 10M hits |
# +--------+------------+------------+------------+------------+------------+
# | 0 | 104 | 255 | 255 | 255 | 255 |
# +--------+------------+------------+------------+------------+------------+
# | 1 | 18 | 49 | 255 | 255 | 255 |
# +--------+------------+------------+------------+------------+------------+
# | 10 | 10 | 18 | 142 | 255 | 255 |
# +--------+------------+------------+------------+------------+------------+
# | 100 | 8 | 11 | 49 | 143 | 255 |
# +--------+------------+------------+------------+------------+------------+
#
# NOTE: The above table was obtained by running the following commands:
#
# redis-benchmark -n 1000000 incr foo
# redis-cli object freq foo
#
# NOTE 2: The counter initial value is 5 in order to give new objects a chance
# to accumulate hits.
#
# The counter decay time is the time, in minutes, that must elapse in order
# for the key counter to be divided by two (or decremented if it has a value
# less <= 10).
#
# The default value for the lfu-decay-time is 1. A Special value of 0 means to
# decay the counter every time it happens to be scanned.
#
# lfu-log-factor 10
# lfu-decay-time 1
########################### ACTIVE DEFRAGMENTATION #######################
#
# WARNING THIS FEATURE IS EXPERIMENTAL. However it was stress tested
# even in production and manually tested by multiple engineers for some
# time.
#
# What is active defragmentation?
# -------------------------------
#
# Active (online) defragmentation allows a Redis server to compact the
# spaces left between small allocations and deallocations of data in memory,
# thus allowing to reclaim back memory.
#
# Fragmentation is a natural process that happens with every allocator (but
# less so with Jemalloc, fortunately) and certain workloads. Normally a server
# restart is needed in order to lower the fragmentation, or at least to flush
# away all the data and create it again. However thanks to this feature
# implemented by Oran Agra for Redis 4.0 this process can happen at runtime
# in an "hot" way, while the server is running.
#
# Basically when the fragmentation is over a certain level (see the
# configuration options below) Redis will start to create new copies of the
# values in contiguous memory regions by exploiting certain specific Jemalloc
# features (in order to understand if an allocation is causing fragmentation
# and to allocate it in a better place), and at the same time, will release the
# old copies of the data. This process, repeated incrementally for all the keys
# will cause the fragmentation to drop back to normal values.
#
# Important things to understand:
#
# 1. This feature is disabled by default, and only works if you compiled Redis
# to use the copy of Jemalloc we ship with the source code of Redis.
# This is the default with Linux builds.
#
# 2. You never need to enable this feature if you don''t have fragmentation
# issues.
#
# 3. Once you experience fragmentation, you can enable this feature when
# needed with the command "CONFIG SET activedefrag yes".
#
# The configuration parameters are able to fine tune the behavior of the
# defragmentation process. If you are not sure about what they mean it is
# a good idea to leave the defaults untouched.
# Enabled active defragmentation
# activedefrag yes
# Minimum amount of fragmentation waste to start active defrag
# active-defrag-ignore-bytes 100mb
# Minimum percentage of fragmentation to start active defrag
# active-defrag-threshold-lower 10
# Maximum percentage of fragmentation at which we use maximum effort
# active-defrag-threshold-upper 100
# Minimal effort for defrag in CPU percentage
# active-defrag-cycle-min 5
# Maximal effort for defrag in CPU percentage
# active-defrag-cycle-max 75
# Maximum number of set/hash/zset/list fields that will be processed from
# the main dictionary scan
# active-defrag-max-scan-fields 1000
docker run -p 6379:6379 -v ~/docker/redis/data:/data -v ~/docker/redis/conf/redis.conf:/etc/redis/redis.conf --privileged=true --name redis01 -d redis:latest redis-server /etc/redis/redis.conf
使用 redis-cli 测试是否成功:
docker exec -it redis01 redis-cli
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