Redis持久化--RDB和AOF

概述

Redis的强大性能很大程度上都是因为所有数据都是存储在内存中的，然而当Redis重启后，所有存储在内存中的数据将会丢失，在很多情况下是无法容忍这样的事情的。所以，我们需要将内存中的数据持久化！典型的需要持久化数据的场景如下：

• 将Redis作为数据库使用；
• 将Redis作为缓存服务器使用，但是缓存miss后会对性能造成很大影响，所有缓存同时失效时会造成服务雪崩，无法响应。

本文介绍Redis所支持的两种数据持久化方式。

Redis数据持久化

Redis支持两种数据持久化方式：RDB方式和AOF方式。前者会根据配置的规则定时将内存中的数据持久化到硬盘上，后者则是在每次执行写命令之后将命令记录下来。两种持久化方式可以单独使用，但是通常会将两者结合使用。

一、RDB方式

RDB方式的持久化是通过快照的方式完成的。所谓内存快照，顾名思义就是给内存拍个照，在某个时刻把内存中的数据记录下来，以文件的形式保存到硬盘上，这样即使宕机，数据依然存在。在服务器重启后只需要把“照片”中的数据恢复即可。

RDB持久化就是把当前进程的数据在某个时刻生成快照(一个压缩的二进制文件)保存到硬盘的过程，触发RDB持久化过程分为手动触发和自动触发。

1.1、生成快照

当符合某种规则时，会将内存中的数据全量生成一份副本存储到硬盘上，这个过程称作”快照”，Redis会在以下几种情况下对数据进行快照：

• 根据配置规则进行自动快照；
• 用户执行SAVE, BGSAVE命令；
• 执行FLUSHALL命令；
• 执行复制（replication）时。

1.1.1、手动触发

手动触发分别对应save和bgsave命令：

• save命令

save命令会阻塞当前Redis服务器，直到RDB过程完成为止。在服务器进程阻塞期间，服务器不能处理任何命令请求。因此，当save命令正在执行时，客户端发送的所有命令都会被拒绝，知道save命令执行完毕。

redis>save //等待，直到RDB文件创建完毕
ok

注意:

Redis的单线程模型就决定了，我们要尽量避免所有会阻塞主线程的操作，由于Save命令执行期间阻塞服务器进程，对于内存比较大的实例会造成长时间阻塞，因此线上环境不建议使用。

• bgsave命令

bgsave命令会派生出一个子进程(而不是线程)，由子进程进行RDB文件创建，而父进程继续处理命令。

redis>bgsave
Background saving started   //直接返回，由子进程进行RDB文件创建
redis>                          //继续处理其它命令

注意:

1. 在bgsave命令执行的时候，为了避免父进程与子进程同时执行两个rdbSave的调用而产生竞争条件，客户端发送的save命令会被服务器拒绝。
2. 如果bgsave命令正在执行，bgrewriteaof（aof重写）命令会被延迟到bgsave命令之后执行，如果bgrewriteaof命令正在执行，那么客户端发送的bgsave命令会被服务器拒绝。
3. 虽然bgsave命令是由子进程进行RDB文件的生成，但是fork()创建子进程的时候会阻塞父进程（详情请往下看）。

1.1.2 自动触发

因为bgsave命令可以在不阻塞服务器进程的情况下保存，所以redis可以通过设置服务器配置的save选项，让服务器每隔一段时间自动执行一次bgsave命令。如：我们向服务器设置如下配置(这也是redis默认的配置):

save 900 1
save 300 10
save 60 10000

那么只要满足如下条件中的一个bgsave命令就会被执行：

• 服务器在900秒内对数据库进行了至少1次修改
• 服务器在300秒内对数据库进行了至少10次修改
• 服务器在60秒内对数据库进行了至少10000次修改

1.1.3、执行FLUSHALL命令

当执行FLUSHALL命令时，Redis会清除数据库中的所有数据。需要注意的是：不论清空数据库的过程是否触发 了自动快照的条件，只要自动快照条件不为空，Redis就会执行一次快照操作，当没有定义自动快照条件时，执行FLUSHALL命令不会进行快照操作。

1.1.4、执行复制

当设置了主从模式时，Redis会在复制初始化是进行自动快照。

快照原理

Redis默认会将快照文件存储在Redis当前进程的工作目录的dump.rdb文件中，可以通过配置文件中的dir和dbfilename两个参数分别指定快照文件的存储路径和文件名，例如：

dbfilename dump.rdb
dir /opt/soft/redis-3.0.4/cache

Redis使用fork函数复制一份当前进程（父进程）的副本（子进程）；快照执行的过程如下：

1. 父进程继续处理来自客户端的请求，子进程开始将内存中的数据写入硬盘中的临时文件；
2. 当子进程写完所有的数据后，用该临时文件替换旧的RDB文件，至此，一次快照操作完成。

需要注意的是：

在执行fork是时候操作系统（类Unix操作系统）会使用写时复制（copy-on-write）策略，即fork函数发生的一刻，父进程和子进程共享同一块内存数据，当父进程需要修改其中的某片数据（如执行写命令）时，操作系统会将该片数据复制一份以保证子进程不受影响，所以RDB文件存储的是执行fork操作那一刻的内存数据。所以RDB方式理论上是会存在丢数据的情况的(fork之后修改的的那些没有写进RDB文件)。

通过上述的介绍可以知道，快照进行时时不会修改RDB文件的，只有完成的时候才会用临时文件替换老的RDB文件，所以就保证任何时候RDB文件的都是完整的。这使得我们可以通过定时备份RDB文件来实现Redis数据的备份。RDB文件是经过压缩处理的二进制文件，所以占用的空间会小于内存中数据的大小，更有利于传输。

Redis启动时会自动读取RDB快照文件，将数据从硬盘载入到内存，根据数量的不同，这个过程持续的时间也不尽相同，通常来讲，一个记录1000万个字符串类型键，大小为1GB的快照文件载入到内存需要20-30秒的时间。

示例

下面演示RDB方式持久化，首先使用配置有如下快照规则：

save 900 1
save 300 10
save 60 10000
dbfilename dump.rdb
dir /opt/soft/redis-3.0.4/cache

然后通过客户端设置一个键值：的配置文件/opt/soft/redis-3.0.4/conf/redis.conf启动Redis服务：

[qifuguang@Mac~]$ /opt/soft/redis-3.0.4/src/redis-cli -p 6379
127.0.0.1:6379> set test-rdb HelloWorld
OK
127.0.0.1:6379> get test-rdb
"HelloWorld"
127.0.0.1:6379>

现在重新启动Redis：现在强行kill Redis服务：

[qifuguang@Mac/opt/soft/redis-3.0.4/cache]$ ls
dump.rdb

现在到/opt/soft/redis-3.0.4/cache目录看，目录下出现了Redis的快照文件dump.rdb：

然后再用客户端连接，检查之前设置的key是否还存在：

[qifuguang@Mac~]$ /opt/soft/redis-3.0.4/src/redis-cli -p 6379
127.0.0.1:6379> get test-rdb
"HelloWorld"
127.0.0.1:6379>

 

 可以发现，之前设置的key在Redis重启之后又通过快照文件dump.rdb恢复了。

1.2、RDB文件的载入

在Redis启动的时候，只要检测到RDB文件的存在，就会自动加载RDB文件。需要注意的是

• 因为AOF文件的更新频率通常比RDB文件的更新频率高,所以口如果服务器开启了AOF持久化功能,那么服务器会优先使用AOF文件来还原数据库状态。

• 只有在AOF持久化功能处于关闭状态时,服务器才会使用RDB文件来还原数据库状态。

注意:服务器在载入RDB文件期间,会一直处于阻塞状态,直到载入工作完成为止

 

1.3、 内存快照的问题

了解了什么是Redis的RDB持久化，我们来思考两个问题。

1.3.1 快照的时候数据可以修改吗

Redis RDB持久化是对某一时刻的内存中的全量数据进行拍照。这让我们不得不思考，快照的时候数据可以修改吗？

首先，如果我们使用save命令做持久化，那么由于Redis单线程模型的原因，在持久化的过程中会阻塞，是不能执行其它命令的。也许有人会说可以使用bgave命令，但使用bgsave就没有问题了吗？

我们在拍照的时候，通常摄影师是不让我们动的，因为一动可能照片就模糊了。在Redis 进行内存快照的时候也会如此。如果我们持久化的过程中，有些数据被修改了。那么就会破坏快照的正确性与完整性。

比如在t时刻,我们对内存进行快照，此时我们希望的是记录下来t时刻内存中所有的数据，假设我们的RDB操作需要10s的时间，而t+2s我们执行了一个修改操作把Key1的值由A修改成了B，而此时RDB操作却还没有把Key1的值写入磁盘。在t+5s的时候读取到key1的值写入磁盘。那么此次快照记录的Key1的值就是B，而不是t时刻的A。这样就破坏了RDB文件的正确性。

RDB文件的生成是需要时间的，如果快照执行期间数据不能被修改，对于业务系统来说不能接受的。那么Redis 是如何解决这个问题的呢？

Redis 借助了操作系统提供的写时复制技术（Copy-On-Write, COW），可以让在执行快照的同时，正常处理写操作。简单来说，bgsave fork子进程的时候，并不会完全复制主进程的内存数据，而是只复制必要的虚拟数据结构，并不为其分配真实的物理空间，它与父进程共享同一个物理内存空间。bgsave 子进程运行后，开始读取主线程的内存数据，并把它们写入 RDB 文件。此时，如果主线程对这些数据也都是读操作，那么，主线程和 bgsave 子进程相互不影响。但是，如果主线程要修改一块数据，此时会给子进程分配一块物理内存空间，把要修改的数据复制一份，生成该数据的副本到子进程的物理内存空间。然后，bgsave 子进程会把这个副本数据写入 RDB 文件，而在这个过程中，主线程仍然可以直接修改原来的数据。

1.3.2 可以频繁进行快照操作吗

假设我们在t 时刻做了一次快照，然后又在 t+n 时刻做了一次快照，而在这期间，发生了数据修改。而此时宕机了，那么，只能按照 t 时刻的快照进行恢复。那么这n秒的数据就彻底丢失无法恢复了。

所以，要想尽可能恢复数据，就只能缩短快照执行的时间间隔，间隔的时间越小，丢失数据也就越少。那么可以频繁的执行快照操作吗？

我们知道bgsave 执行时并不阻塞主线程，但是这不代表可以频繁执行快照操作。

一方面，持久化是一个写入磁盘的过程，频繁将全量数据写入磁盘，会给磁盘带来很大压力，频繁执行快照也容易导致前一个快照还没有执行完，后一个又开始了，这样多个快照竞争有限的磁盘带宽，容易造成恶性循环。

再者，bgsave所fork出来的子进程执行操作虽然并不会阻塞父进程的操作，但是fork出子进程的操作却是由主进程完成的，会阻塞主进程，fork子进程需要拷贝进程必要的数据结构，其中有一项就是拷贝内存页表（虚拟内存和物理内存的映射索引表），这个拷贝过程会消耗大量CPU资源，拷贝完成之前整个进程是会阻塞的，阻塞时间取决于整个实例的内存大小，实例越大，内存页表越大，fork阻塞时间也就越久。

也许有人会想到是否可以做增量快照呢？也就是只对上一次快照之后的数据做快照。

首先思路肯定是可以，但是增量快照要求记住哪些数据上一次快照之后产生的。这就需要额外的元数据来记录这些信息，会引入额外的空间消耗。这对于内存资源宝贵的 Redis 来说，并不是一个很好的方案。

如果不能频繁执行快照操作，那么该如何解决两次快照之间的数据丢失的问题呢？Redis 还提供了另外一种持久化方式——AOF(append to file)日志。

二、AOF方式

 

　　上面我们总结到使用Redis内存快照进行持久化，在t 时刻做了一次快照，然后又在 t+n 时刻做了一次快照，此时如果宕机，则会丢失在此期间内修改的数据。但又不能频繁的进行内存快照，那么有什么办法能够尽可能的减少这种数据丢失呢？Redis提供了另一种持久化的方式——AOF日志（Append Only File）。

2.1、什么是AOF日志持久化

2.1.1 执行后写日志

与内存快照保存当前内存中的数据所不同，AOF持久化是通过保存Redis服务器所执行的写命令来记录数据库状态的。即每执行一个命令，就会把该命令写到日志文件里。需要注意的是写日志的操作在Redis执行命令将数据写入内存之后，如下图所示：

 

这样做的好处就是不会阻塞当前操作，也可以避免额外的检查开销，如果是在命令执行前进行写日志的操作，一旦命令语法是错误的，不进行检查的话就会导致写入到日志文件中的命令是错误的，在使用日志文件恢复数据的时候就会出错。而在命令执行后在进行日志的写入则不会有这个问题。但是也存在两个问题，

1. AOF 虽然避免了对当前命令的阻塞，但却可能会给下一个操作带来阻塞风险。因为，AOF 日志是在主进程中执行的，如果在把日志文件写入磁盘时，磁盘写压力大，就会导致写盘很慢，进而导致后续的操作也无法执行了
2. 如果刚执行完一个命令，还没有来得及记日志就宕机了，那么这个命令和相应的数据就有丢失的风险。如果此时 Redis 是用作缓存，还可以从后端数据库重新读入数据进行恢复，但是，如果 Redis 是直接用作数据库的话，此时，因为命令没有记入日志，所以就无法用日志进行恢复了。

 

2.1.2 AOF 缓冲区

针对上面两个问题，Redis提供了缓冲区的方式进行AOF日志的记录，以达到尽可能的避免阻塞和数据丢失的问题。即Redis在执行完命令进行持久化的时候，并非直接写入磁盘日志文件，而是先写入AOF缓冲区内，之后再通过某种策略写到磁盘。

 

 

使用缓存区的方式进行AOF日志的记录，上面提到的两个问题其实就和日志从缓冲区写入磁盘的时机有关系。

 

 

2.1.3 三种回写策略

Redis AOF 机制提供了三种回写磁盘的策略。

• Always(同步写回): 命令写入 AOF缓冲区后调用系统 fsync操作同步到AOF文件, fsync完成后线程返回
• Everysec(每秒写回): 命令写人 AOF缓冲区后调用系统 write操作, write完成后线程返回。fsync同步文件操作由专门线程每秒调用一次
• No(操作系统自动写回): 命令写入 AOF缓冲区后调用系统 write操作,不对AOF文件做 fsync同步,同步硬盘操作由操作系统负责,通常同步周期最长30秒

但其实可以看出这三种回写策略都并不能完美的解决问题，配置为 always时,每次写入都要同步AOF文件,硬盘的写入速度无法与内存相提并论,显然与 Redis髙性能特性背道而驰配置为no,由于操作系统每次同步AOF文件的周期不可控,而且会加大每次同步硬盘的数据量,虽然提升了性能,但数据安全性无法保证。配置为 everysec,是建议的同步策略,也是默认配置,虽然能做到兼顾性能和数据安全性。但极端情况下会造成1秒内的数据丢失。在真正使用中，我们可以根据具体对性能和数据完整性的要求，分析这三种回写策略，选择适合的策略来进行持久化。

回写策略	优点	缺点
Always(同步写回)	可靠性高、数据基本不丢失	性能较差
Everysec(每秒写回)	性能适中	宕机时丢失1秒内的数据
No(操作系统自动写回)	性能好	宕机时丢失数据较多

 

2.2、 AOF重写

2.2.1 日志文件越来越大怎么办

选择了合适的回写策略，AOF这种持久化的方式还有其它问题吗？因为AOF持久化是通过保存被执行的写命令来记录数据库状态的,所以随着时间的流逝,AOF文件中的内容会越来越多,文件的体积也会越来越大,过大的AOF文件不仅追加命令会变慢，而且可能对Redis服务器、甚至整个宿主计算机造成影响,并且AOF文件的体积越大,使用AOF文件来进行数据还原所需的时间就越多。这个时候就要用到AOF重写机制了

redis> set testKey testValueOKredis> set testKey testValue1OKredis> del testKeyOKredis> set testKey helloOKredis> set testKey worldOK

AOF 文件是以追加的方式，逐一记录接收到的写命令的。当一个键值对被多条写命令反复修改时，AOF 文件会记录相应的多条命令。如上示例，我们执行完命令后，Redis会在AOF里面追加5条命令。但实际上只需要set testKey world一条命令就够了。AOF 重写机制就是在重写时，Redis 根据数据库的现状创建一个新的 AOF 文件，也就是说，读取数据库中的所有键值对，然后对每一个键值对用一条命令记录它的写入。比如说，当读取了键值对“testkey”: “world”之后，重写机制会记录 set testkey world这条命令。这样，当需要恢复时，可以重新执行该命令，实现“testkey”: “world”的写入。这样，重写后的日志，从5条变成了1条，而对于可能被修改过成百上千次的键值对来说，重写能节省的空间就更大了。虽然 AOF重写后，日志文件会缩小，但是，要把整个数据库的最新数据的操作日志都写回磁盘，仍然是一个非常耗时的过程。这时，我们不得不关注：重写会不会导致阻塞？这就要看看AOF重写的过程是怎么样的

2.2.2 AOF 重写过程

因为AOF重写也是一个非常耗时的过程，又因为Redis单线程的特性，同内存快照一样，AOF重写的过程也是由父进程fork出bgrewriteaof子进程来完成的.使用子进程（而不是开启一个线程）进行AOF重写虽然可以避免使用锁的情况下，保证数据安全性，但是会带来子进程和父进程一致性问题。
例如在开始重写之后父进程又接收了新的键值对此时子进程是无法知晓的，当子进程重写完成后的数据库和父进程的数据库状态是不一致的。如下表：

时间	服务器进程（父进程）	子进程
T1	执行命令 SET K1 V1
T2	执行命令 SET K1 V1
T3	创建子进程，执行AOF文件重写	开始AOF重写
T4	执行命令 SET K2 V2	执行重写
T5	执行命令 SET K3 V3	执行重写
T6	执行命令 SET K4 V4	完成AOF重写

 

在T6时刻服务器进程有了4个键，而子进程却只有1个键为了解决这种不一致性，Redis设置了一个AOF重写缓冲区。

 

 

在子进程执行AOF重写期间。服务器进程需要执行以下3个动作：

1. 执行客户端命令
2. 执行后追加到AOF缓冲区
3. 执行后追加到AOF重写缓冲区

子进程完成AOF重写后，它向父进程发送一个信号，父进程收到信号后会调用一个信号处理函数，该函数把AOF重写缓冲区的命令追加到新AOF文件中然后替换掉现有AOF文件。父进程处理完毕后可以继续接受客户端命令调用，可以看出在AOF后台重写过程中只有这个信号处理函数会阻塞服务器进程。
下表是完整的AOF后台重写过程：

时间	子进程服务器进程（父进程）	子进程
T1	执行命令 SET K1 V1
T2	执行命令 SET K1 V1
T3	创建子进程，执行AOF文件重写	开始AOF重写
T4	执行命令 SET K2 V2	执行重写
T5	执行命令 SET K3 V3	执行重写
T6	执行命令 SET K4 V4	完成AOF重写，向父进程发送信号
T7	接收到信号，将T5 T6 T7 服务器的写命令追加到新的AOF文件末尾
T8	用新的AOF替换旧的AOF

 

这样就可以保证重写日志期间的所有操作也都会写入新的AOF文件。需要注意的是， T7 T8执行的任务会阻塞服务器处理命令。总的来说，就是每次 AOF 重写时，Redis 会先fork出一个子进程用于重写；然后，使用两个日志保证在重写过程中，新写入的数据不会丢失。

2.3 AOF文件恢复

在Redis 服务器重启后，会优先去载入AOF日志文件。因为AOF文件里面包含了重建数据库状态所需的所有写命令,所以服务器重新执行一遍AOF文件里面保存的写命令,就可以还原服务器关闭之前的数据库状态。而由于Redis命令只能在客户端上下文中执行，Redis会创建一个没有网络连接的伪客户端来执行AOF文件中的内容。

数据恢复：

• 如果只配置AOF,重启时加载AOF文件恢复数据；
• 如果同时 配置了RBD和AOF,启动是只加载AOF文件恢复数据;
• 如果只配置RBD,启动是讲加载dump文件恢复数据。

2.4 开启AOF

默认情况下，Redis没有开启AOF（append only file）持久化功能，可以通过在配置文件中作如下配置启用：

appendonly yes

 

开启之后，Redis每执行一条写命令就会将该命令写入硬盘中的AOF文件。AOF文件保存路径和RDB文件路径是一致的，都是通过dir参数配置，默认文件名是：appendonly.aof，可以通过配置appendonlyfilename参数修改，例如： 

appendonlyfilename appendonly.aof

2.5 AOF持久化的实现

AOF纯文本的形式记录了Redis执行的写命令，例如在开启AOF持久化的情况下执行如下命令：

1 2 3 4 5 6 7 8 9

[qifuguang@Mac/opt/soft/redis-3.0.4]$ ./src/redis-cli 127.0.0.1:6379> 127.0.0.1:6379> 127.0.0.1:6379> 127.0.0.1:6379> set aof1 value1 OK 127.0.0.1:6379> set aof2 value2 OK 127.0.0.1:6379>

然后查看/opt/soft/redis-3.0.4/cache/appendonly.aof文件：

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

[qifuguang@Mac/opt/soft/redis-3.0.4/cache]$ cat appendonly.aof *2 $6 SELECT $1 0 *3 $3 set $4 aof1 $6 value1 *3 $3 set $4 aof2 $6 value2

文件中的内容正是Redis刚才执行的命令的内容，内容的格式就先不展开叙述了。

同步硬盘数据

虽然每次执行更改数据库的内容时，AOF都会记录执行的命令，但是由于操作系统本身的硬盘缓存的缘故，AOF文件的内容并没有真正地写入硬盘，在默认情况下，操作系统会每隔30s将硬盘缓存中的数据同步到硬盘，但是为了防止系统异常退出而导致丢数据的情况发生，我们还可以在Redis的配置文件中配置这个同步的频率：

1 2 3

# appendfsync always appendfsync everysec # appendfsync no

第一行表示每次AOF写入一个命令都会执行同步操作，这是最安全也是最慢的方式；
第二行表示每秒钟进行一次同步操作，一般来说使用这种方式已经足够；
第三行表示不主动进行同步操作，这是最不安全的方式。

=========================================================================

1、快照（snapshots）

　　缺省情况情况下，Redis把数据快照存放在磁盘上的二进制文件中，文件名为dump.rdb。你可以配置Redis的持久化策略，例如数据集中每N秒钟有超过M次更新，就将数据写入磁盘；或者你可以手工调用命令SAVE或BGSAVE。

数据保存的目录：

 

工作原理

• Redis forks.
• 子进程开始将数据写到临时RDB文件中。
• 当子进程完成写RDB文件，用新文件替换老文件。
• 这种方式可以使Redis使用copy-on-write技术。

 

2、APPEND ONLY MODE（AOF）

快照模式并不十分健壮，当系统停止，或者无意中Redis被kill掉，最后写入Redis的数据就会丢失。这对某些应用也许不是大问题，但对于要求高可靠性的应用来说，Redis就不是一个合适的选择。
Append-only文件模式是另一种选择。
你可以在配置文件中打开AOF模式：

 

选项：

　　1、appendfsync no

　　当设置appendfsync为no的时候，Redis不会主动调用fsync去将AOF日志内容同步到磁盘，所以这一切就完全依赖于操作系统的调试了。对大多数Linux操作系统，是每30秒进行一次fsync，将缓冲区中的数据写到磁盘上。

　　2、appendfsync everysec

当设置appendfsync为everysec的时候，Redis会默认每隔一秒进行一次fsync调用，将缓冲区中的数据写到磁盘。但是当这一 次的fsync调用时长超过1秒时。Redis会采取延迟fsync的策略，再等一秒钟。也就是在两秒后再进行fsync，这一次的fsync就不管会执行多长时间都会进行。这时候由于在fsync时文件描述符会被阻塞，所以当前的写操作就会阻塞。

所以，结论就是：在绝大多数情况下，Redis会每隔一秒进行一次fsync。在最坏的情况下，两秒钟会进行一次fsync操作。

这一操作在大多数数据库系统中被称为group commit，就是组合多次写操作的数据，一次性将日志写到磁盘。

　　3、appednfsync always

当设置appendfsync为always时，每一次写操作都会调用一次fsync，这时数据是最安全的，当然，由于每次都会执行fsync，所以其性能也会受到影响

 　　建议采用 appendfsync everysec（缺省方式）

　　快照模式可以和AOF模式同时开启，互补影响

 三、RDB-AOF混合持久化

这里补充一个知识点，在Redis4.0之后，既上一篇文章介绍的RDB和这篇文章介绍的AOF两种持久化方式，又新增了RDB-AOF混合持久化方式。

　　这种方式结合了RDB和AOF的优点，既能快速加载又能避免丢失过多的数据。

　　具体配置为：

aof-use-rdb-preamble

　　设置为yes表示开启，设置为no表示禁用。

　　当开启混合持久化时，主进程先fork出子进程将现有内存副本全量以RDB方式写入aof文件中，然后将缓冲区中的增量命令以AOF方式写入aof文件中，写入完成后通知主进程更新相关信息，并将新的含有 RDB和AOF两种格式的aof文件替换旧的aof文件。

　　简单来说：混合持久化方式产生的文件一部分是RDB格式，一部分是AOF格式。

　　这种方式优点我们很好理解，缺点就是不能兼容Redis4.0之前版本的备份文件了。

四、附录

redis默认配置文件

# Redis configuration file example

# 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

################################ 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

# When running daemonized, Redis writes a pid file in /var/run/redis.pid by
# default. You can specify a custom pid file location here.
pidfile /var/run/redis.pid

# Accept connections on the specified port, default is 6379.
# 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

# By default Redis listens for connections from all the network interfaces
# available on the server. It is possible to listen to just one or multiple
# 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

# 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 60 seconds.
tcp-keepalive 0

# 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

################################ 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-Slave replication. Use slaveof to make a Redis instance a copy of
# another Redis server. A few things to understand ASAP about Redis replication.
#
# 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 slaves.
# 2) Redis slaves 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 slaves automatically try to reconnect to masters
#    and resynchronize with them.
#
# slaveof <masterip> <masterport>

# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the slave to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the slave request.
#
# masterauth <master-password>

# When a slave loses its connection with the master, or when the replication
# is still in progress, the slave can act in two different ways:
#
# 1) if slave-serve-stale-data is set to 'yes' (the default) the slave 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 slave-serve-stale-data is set to 'no' the slave will reply with
#    an error "SYNC with master in progress" to all the kind of commands
#    but to INFO and SLAVEOF.
#
slave-serve-stale-data yes

# You can configure a slave instance to accept writes or not. Writing against
# a slave instance may be useful to store some ephemeral data (because data
# written on a slave 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 slaves are read-only.
#
# 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.
slave-read-only yes

# Replication SYNC strategy: disk or socket.
#
# -------------------------------------------------------
# WARNING: DISKLESS REPLICATION IS EXPERIMENTAL CURRENTLY
# -------------------------------------------------------
#
# New slaves and reconnecting slaves 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 slaves.
# 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 slaves incrementally.
# 2) Diskless: The Redis master creates a new process that directly writes the
#              RDB file to slave sockets, without touching the disk at all.
#
# With disk-backed replication, while the RDB file is generated, more slaves
# 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 slaves 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 slaves
# 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 trnasfers the RDB via socket
# to the slaves.
#
# This is important since once the transfer starts, it is not possible to serve
# new slaves arriving, that will be queued for the next RDB transfer, so the server
# waits a delay in order to let more slaves 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

# Slaves send PINGs to server in a predefined interval. It's possible to change
# this interval with the repl_ping_slave_period option. The default value is 10
# seconds.
#
# repl-ping-slave-period 10

# The following option sets the replication timeout for:
#
# 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.
#
# 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

# Set the replication backlog size. The backlog is a buffer that accumulates
# slave data when slaves are disconnected for some time, so that when a slave
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the slave missed while
# disconnected.
#
# The bigger the replication backlog, the longer the time the slave can be
# disconnected and later be able to perform a partial resynchronization.
#
# 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.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600

# The slave priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a slave to promote into a
# master if the master is no longer working correctly.
#
# A slave with a low priority number is considered better for promotion, so
# for instance if there are three slaves 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 slave as not able to perform the
# role of master, so a slave with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 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 GUARANTEE 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.

################################## 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 slaves may cause problems.

################################### LIMITS ####################################

# 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

# Don't use more memory than 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 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').
#
# maxmemory <bytes>

# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# allkeys-lru -> remove any key according to the LRU algorithm
# 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
#
# 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 volatile-lru

# LRU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can select as well the sample
# size to check. For instance for default Redis will check three keys and
# pick the one that was used less recently, you can change the sample size
# using the following configuration directive.
#
# maxmemory-samples 3

############################## 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

################################ 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

################################## 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 enalbed 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

# 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 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

# 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
# slave  -> slave 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 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

# 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

 

转自：https://mp.weixin.qq.com/s/VSbF-K-Dc7dEj6tnka8cbA