使用Redis前必须了解的概念和配置

因前两天服务器挂掉了,导致项目使用的redis数据库异常,丢失了部分数据,为了能够更好的使用Redis,结合网上的资料以及个人整理,在使用Redis前有必要了解一些概念和配置,下面进入正题。

持久化(persistence)

这篇文章提供了 Redis 持久化的技术性描述,推荐所有 Redis 用户阅读。
要更广泛地了解 Redis 持久化,以及这种持久化所保证的耐久性(durability)。

Redis 持久化

Redis 提供了多种不同级别的持久化方式:

  • RDB 持久化可以在指定的时间间隔内生成数据集的时间点快照(point-in-time snapshot)。

  • AOF 持久化记录服务器执行的所有写操作命令,并在服务器启动时,通过重新执行这些命令来还原数据集。AOF 文件中的命令全部以 Redis 协议的格式来保存,新命令会被追加到文件的末尾。Redis 还可以在后台对 AOF 文件进行重写(rewrite),使得 AOF 文件的体积不会超出保存数据集状态所需的实际大小。

  • Redis 还可以同时使用 AOF 持久化和 RDB 持久化。在这种情况下,当 Redis 重启时,它会优先使用 AOF 文件来还原数据集,因为 AOF 文件保存的数据集通常比 RDB 文件所保存的数据集更完整。

  • 你甚至可以关闭持久化功能,让数据只在服务器运行时存在。

了解 RDB 持久化和 AOF 持久化之间的异同是非常重要的,以下几个小节将详细地介绍这这两种持久化功能,并对它们的相同和不同之处进行说明。

RDB 的优点

  • RDB 是一个非常紧凑(compact)的文件,它保存了 Redis 在某个时间点上的数据集。这种文件非常适合用于进行备份:比如说,你可以在最近的 24 小时内,每小时备份一次 RDB 文件,并且在每个月的每一天,也备份一个 RDB 文件。这样的话,即使遇上问题,也可以随时将数据集还原到不同的版本。

  • RDB 非常适用于灾难恢复(disaster recovery):它只有一个文件,并且内容都非常紧凑,可以(在加密后)将它传送到别的数据中心,或者亚马逊 S3 中。

  • RDB 可以最大化 Redis 的性能:父进程在保存 RDB 文件时唯一要做的就是fork出一个子进程,然后这个子进程就会处理接下来的所有保存工作,父进程无须执行任何磁盘 I/O 操作。

  • RDB 在恢复大数据集时的速度比 AOF 的恢复速度要快。

RDB 的缺点

  • 如果你需要尽量避免在服务器故障时丢失数据,那么 RDB 不适合你。虽然 Redis 允许你设置不同的保存点(save point)来控制保存 RDB 文件的频率,但是,因为RDB 文件需要保存整个数据集的状态,所以它并不是一个轻松的操作。因此你可能会至少 5 分钟才保存一次 RDB 文件。在这种情况下,一旦发生故障停机,你就可能会丢失好几分钟的数据。

  • 每次保存 RDB 的时候,Redis 都要fork()出一个子进程,并由子进程来进行实际的持久化工作。在数据集比较庞大时,fork()可能会非常耗时,造成服务器在某某毫秒内停止处理客户端;如果数据集非常巨大,并且 CPU 时间非常紧张的话,那么这种停止时间甚至可能会长达整整一秒。虽然 AOF 重写也需要进行fork(),但无论 AOF 重写的执行间隔有多长,数据的耐久性都不会有任何损失。

AOF 的优点

  • 使用 AOF 持久化会让 Redis 变得非常耐久(much more durable):你可以设置不同的fsync策略,比如无fsync,每秒钟一次fsync,或者每次执行写入命令时fsync。AOF 的默认策略为每秒钟fsync一次,在这种配置下,Redis 仍然可以保持良好的性能,并且就算发生故障停机,也最多只会丢失一秒钟的数据(fsync会在后台线程执行,所以主线程可以继续努力地处理命令请求)。

  • AOF 文件是一个只进行追加操作的日志文件(append only log),因此对 AOF 文件的写入不需要进行seek,即使日志因为某些原因而包含了未写入完整的命令(比如写入时磁盘已满,写入中途停机,等等),redis-check-aof工具也可以轻易地修复这种问题。

  • Redis 可以在 AOF 文件体积变得过大时,自动地在后台对 AOF 进行重写:重写后的新 AOF 文件包含了恢复当前数据集所需的最小命令集合。整个重写操作是绝对安全的,因为 Redis 在创建新 AOF 文件的过程中,会继续将命令追加到现有的 AOF 文件里面,即使重写过程中发生停机,现有的 AOF 文件也不会丢失。而一旦新 AOF 文件创建完毕,Redis 就会从旧 AOF 文件切换到新 AOF 文件,并开始对新 AOF 文件进行追加操作。

  • AOF 文件有序地保存了对数据库执行的所有写入操作,这些写入操作以 Redis 协议的格式保存,因此 AOF 文件的内容非常容易被人读懂,对文件进行分析(parse)也很轻松。导出(export) AOF 文件也非常简单:举个例子,如果你不小心执行了FLUSHALL命令,但只要 AOF 文件未被重写,那么只要停止服务器,移除 AOF 文件末尾的FLUSHALL命令,并重启 Redis ,就可以将数据集恢复到FLUSHALL执行之前的状态。

AOF 的缺点

  • 对于相同的数据集来说,AOF 文件的体积通常要大于 RDB 文件的体积。

  • 根据所使用的fsync策略,AOF 的速度可能会慢于 RDB 。在一般情况下,每秒fsync的性能依然非常高,而关闭fsync可以让 AOF 的速度和 RDB 一样快,即使在高负荷之下也是如此。不过在处理巨大的写入载入时,RDB 可以提供更有保证的最大延迟时间(latency)。

  • AOF 在过去曾经发生过这样的 bug :因为个别命令的原因,导致 AOF 文件在重新载入时,无法将数据集恢复成保存时的原样。(举个例子,阻塞命令BRPOPLPUSH就曾经引起过这样的 bug 。)测试套件里为这种情况添加了测试:它们会自动生成随机的、复杂的数据集,并通过重新载入这些数据来确保一切正常。虽然这种 bug 在 AOF 文件中并不常见,但是对比来说,RDB 几乎是不可能出现这种 bug 的。

RDB 和 AOF ,我应该用哪一个?

一般来说,如果想达到足以媲美 PostgreSQL 的数据安全性,你应该同时使用两种持久化功能。
如果你非常关心你的数据,但仍然可以承受数分钟以内的数据丢失,那么你可以只使用 RDB 持久化。

有很多用户都只使用 AOF 持久化,但我们并不推荐这种方式:因为定时生成 RDB 快照(snapshot)非常便于进行数据库备份,并且 RDB 恢复数据集的速度也要比 AOF 恢复的速度要快,除此之外,使用 RDB 还可以避免之前提到的 AOF 程序的 bug 。

因为以上提到的种种原因,未来我们可能会将 AOF 和 RDB 整合成单个持久化模型。(这是一个长期计划。)
接下来的几个小节将介绍 RDB 和 AOF 的更多细节。

RDB 快照

在默认情况下,Redis 将数据库快照保存在名字为dump.rdb的二进制文件中。你可以对 Redis 进行设置,让它在“N秒内数据集至少有M个改动”这一条件被满足时,自动保存一次数据集。你也可以通过调用SAVE或者BGSAVE,手动让 Redis 进行数据集保存操作。比如说,以下设置会让 Redis 在满足“60秒内有至少有1000个键被改动”这一条件时,自动保存一次数据集:

save 60 1000

这种持久化方式被称为快照(snapshot)。

快照的运作方式

当 Redis 需要保存dump.rdb文件时,服务器执行以下操作:

1、Redis 调用fork(),同时拥有父进程和子进程。
2、子进程将数据集写入到一个临时 RDB 文件中。
3、当子进程完成对新 RDB 文件的写入时,Redis 用新 RDB 文件替换原来的 RDB 文件,并删除旧的 RDB 文件。

这种工作方式使得 Redis 可以从写时复制(copy-on-write)机制中获益。

只进行追加操作的文件(append-only file,AOF)

快照功能并不是非常耐久(durable):如果 Redis 因为某些原因而造成故障停机,那么服务器将丢失最近写入、且仍未保存到快照中的那些数据。

尽管对于某些程序来说,数据的耐久性并不是最重要的考虑因素,但是对于那些追求完全耐久能力(full durability)的程序来说,快照功能就不太适用了。从 1.1 版本开始,Redis 增加了一种完全耐久的持久化方式:AOF 持久化。你可以通过修改配置文件来打开 AOF 功能:

appendonly yes

从现在开始,每当 Redis 执行一个改变数据集的命令时(比如SET),这个命令就会被追加到 AOF 文件的末尾。这样的话,当 Redis 重新启时,程序就可以通过重新执行 AOF 文件中的命令来达到重建数据集的目的。

AOF 重写

因为 AOF 的运作方式是不断地将命令追加到文件的末尾,所以随着写入命令的不断增加,AOF 文件的体积也会变得越来越大。

举个例子,如果你对一个计数器调用了 100 次INCR,那么仅仅是为了保存这个计数器的当前值,AOF 文件就需要使用 100 条记录(entry)。然而在实际上,只使用一条SET命令已经足以保存计数器的当前值了,其余 99 条记录实际上都是多余的。

为了处理这种情况,Redis 支持一种有趣的特性:可以在不打断服务客户端的情况下,对 AOF 文件进行重建(rebuild)。执行BGREWRITEAOF命令,Redis 将生成一个新的 AOF 文件,这个文件包含重建当前数据集所需的最少命令。Redis 2.2 需要自己手动执行BGREWRITEAOF命令;Redis 2.4 则可以自动触发 AOF 重写,具体信息请查看 2.4 的示例配置文件。

AOF 有多耐久?

你可以配置 Redis 多久才将数据fsync到磁盘一次。

有三个选项:

  • 每次有新命令追加到 AOF 文件时就执行一次fsync:非常慢,也非常安全。

  • 每秒fsync一次:足够快(和使用 RDB 持久化差不多),并且在故障时只会丢失 1 秒钟的数据。

  • 从不fsync:将数据交给操作系统来处理。更快,也更不安全的选择。

推荐(并且也是默认)的措施为每秒fsync一次,这种fsync策略可以兼顾速度和安全性。总是fsync的策略在实际使用中非常慢,即使在 Redis 2.0 对相关的程序进行了改进之后仍是如此 ——频繁调用fsync注定了这种策略不可能快得起来。

如果 AOF 文件出错了,怎么办?

服务器可能在程序正在对 AOF 文件进行写入时停机,如果停机造成了 AOF 文件出错(corrupt),那么 Redis 在重启时会拒绝载入这个 AOF 文件,从而确保数据的一致性不会被破坏。

当发生这种情况时,可以用以下方法来修复出错的 AOF 文件:
1、为现有的 AOF 文件创建一个备份。
2、使用 Redis 附带的redis-check-aof程序,对原来的 AOF 文件进行修复。

$ redis-check-aof --fix

1、(可选)使用diff -u对比修复后的 AOF 文件和原始 AOF 文件的备份,查看两个文件之间的不同之处。

2、重启 Redis 服务器,等待服务器载入修复后的 AOF 文件,并进行数据恢复。

AOF 的运作方式

AOF 重写和 RDB 创建快照一样,都巧妙地利用了写时复制机制。

以下是 AOF 重写的执行步骤:

1、Redis 执行fork(),现在同时拥有父进程和子进程。
2、子进程开始将新 AOF 文件的内容写入到临时文件。
3、对于所有新执行的写入命令,父进程一边将它们累积到一个内存缓存中,一边将这些改动追加到现有 AOF 文件的末尾:这样即使在重写的中途发生停机,现有的 AOF 文件也还是安全的。
4、当子进程完成重写工作时,它给父进程发送一个信号,父进程在接收到信号之后,将内存缓存中的所有数据追加到新 AOF 文件的末尾。
5、搞定!现在 Redis 原子地用新文件替换旧文件,之后所有命令都会直接追加到新 AOF 文件的末尾。

怎么从 RDB 持久化切换到 AOF 持久化

在 Redis 2.2 或以上版本,可以在不重启的情况下,从 RDB 切换到 AOF :

1、为最新的dump.rdb文件创建一个备份。
2、将备份放到一个安全的地方。
3、执行以下两条命令:

> redis-cli> CONFIG SET appendonly yes
> 
> redis-cli> CONFIG SET save ""
> 

4、确保命令执行之后,数据库的键的数量没有改变。
5、确保写命令会被正确地追加到 AOF 文件的末尾。

步骤 3 执行的第一条命令开启了 AOF 功能:Redis 会阻塞直到初始 AOF 文件创建完成为止,之后 Redis 会继续处理命令请求,并开始将写入命令追加到 AOF 文件末尾。

步骤 3 执行的第二条命令用于关闭 RDB 功能。这一步是可选的,如果你愿意的话,也可以同时使用 RDB 和 AOF 这两种持久化功能。

别忘了在redis.conf中打开 AOF 功能!否则的话,服务器重启之后,之前通过CONFIG SET设置的配置就会被遗忘,程序会按原来的配置来启动服务器。

译注:原文这里还有介绍 2.0 版本的切换方式,考虑到 2.0 已经很老旧了,这里省略了对那部分文档的翻译,有需要的请参考原文。

RDB 和 AOF 之间的相互作用

在版本号大于等于 2.4 的 Redis 中,BGSAVE执行的过程中,不可以执行
BGREWRITEAOF。反过来说,在BGREWRITEAOF执行的过程中,也不可以执行BGSAVE。这可以防止两个 Redis 后台进程同时对磁盘进行大量的 I/O 操作。如果BGSAVE正在执行,并且用户显示地调用BGREWRITEAOF命令,那么服务器将向用户回复一个OK状态,并告知用户,BGREWRITEAOF已经被预定执行:一旦BGSAVE执行完毕,BGREWRITEAOF就会正式开始。

当 Redis 启动时,如果 RDB 持久化和 AOF 持久化都被打开了,那么程序会优先使用 AOF 文件来恢复数据集,因为 AOF 文件所保存的数据通常是最完整的。

备份 Redis 数据

在阅读这个小节前,先将下面这句话铭记于心:一定要备份你的数据库!

磁盘故障,节点失效,诸如此类的问题都可能让你的数据消失不见,不进行备份是非常危险的。

Redis 对于数据备份是非常友好的,因为你可以在服务器运行的时候对 RDB 文件进行复制:RDB 文件一旦被创建,就不会进行任何修改。当服务器要创建一个新的 RDB 文件时,它先将文件的内容保存在一个临时文件里面,当临时文件写入完毕时,程序才使用rename(2)原子地用临时文件替换原来的 RDB 文件。

这也就是说,无论何时,复制 RDB 文件都是绝对安全的。

以下是我们的建议:

  • 创建一个定期任务(cron job),每小时将一个 RDB 文件备份到一个文件夹,并且每天将一个 RDB 文件备份到另一个文件夹。

  • 确保快照的备份都带有相应的日期和时间信息,每次执行定期任务脚本时,使用find命令来删除过期的快照:比如说,你可以保留最近 48 小时内的每小时快照,还可以保留最近一两个月的每日快照。

  • 至少每天一次,将 RDB 备份到你的数据中心之外,或者至少是备份到你运行 Redis 服务器的物理机器之外。

容灾备份

Redis 的容灾备份基本上就是对数据进行备份,并将这些备份传送到多个不同的外部数据中心。

容灾备份可以在 Redis 运行并产生快照的主数据中心发生严重的问题时,仍然让数据处于安全状态。

因为很多 Redis 用户都是创业者,他们没有大把大把的钱可以浪费,所以下面介绍的都是一些实用又便宜的容债备份方法:

  • Amazon S3 ,以及其他类似 S3 的服务,是一个构建灾难备份系统的好地方。最简单的方法就是将你的每小时或者每日 RDB 备份加密并传送到 S3 。对数据的加密可以通过gpg -c命令来完成(对称加密模式)。记得把你的密码放到几个不同的、安全的地方去(比如你可以把密码复制给你组织里最重要的人物)。同时使用多个储存服务来保存数据文件,可以提升数据的安全性。

  • 传送快照可以使用 SCP 来完成(SSH 的组件)。以下是简单并且安全的传送方法:买一个离你的数据中心非常远的 VPS ,装上 SSH ,创建一个无口令的 SSH 客户端 key ,并将这个 key 添加到 VPS 的 authorized_keys 文件中,这样就可以向这个 VPS 传送快照备份文件了。为了达到最好的数据安全性,至少要从两个不同的提供商那里各购买一个 VPS 来进行数据容灾备份。

需要注意的是,这类容灾系统如果没有小心地进行处理的话,是很容易失效的。

最低限度下,你应该在文件传送完毕之后,检查所传送备份文件的体积和原始快照文件的体积是否相同。如果你使用的是 VPS ,那么还可以通过比对文件的 SHA1 校验和来确认文件是否传送完整。

另外,你还需要一个独立的警报系统,让它在负责传送备份文件的传送器(transfer)失灵时通知你。

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 /var/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
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