Redis的配置文件详解：

　　原文参考：https://www.jianshu.com/p/16013dbb137e

　　　　　　　　https://juejin.im/post/5d674ac2e51d4557ca7fdd70

# 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 ###################################
################################## 包含     ###################################

# 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.
#
# 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
# include /path/to/local.conf
# include /path/to/other.conf

################################ GENERAL  #####################################
################################ 常用     #####################################

# 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.
# 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 yes

# When running daemonized, Redis writes a pid file in /var/run/redis.pid by
# default. You can specify a custom pid file location here.
# 当 Redis 以守护进程的方式运行的时候，Redis 默认会把 pid 文件放在/var/run/redis.pid
# 可配置到其他地址，当运行多个 redis 服务时，需要指定不同的 pid 文件和端口
# 指定存储Redis进程号的文件路径
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.
# 端口，默认端口是6379，生产环境中建议更改端口号，安全性更高
# 如果你设为 0 ，redis 将不在 socket 上监听任何客户端连接。
port 9966

# 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 监听的最大容纳数量
# 此参数确定了TCP连接中已完成队列(完成三次握手之后)的长度，
# 当系统并发量大并且客户端速度缓慢的时候，你需要把这个值调高以避免客户端连接缓慢的问题。
# 虽然这里指定了队列长度是511，但是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：128。
# 所以可以将这二个参数一起参考设定，你以便达到你的预期。
#
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
# 有时候为了安全起见，redis一般都是监听127.0.0.1 但是有时候又有同网段能连接的需求，当然可以绑定0.0.0.0 用iptables来控制访问权限，或者设置redis访问密码来保证数据安全

# 不设置将处理所有请求,建议生产环境中设置，有个误区：bind是用来限制外网IP访问的，其实不是，限制外网ip访问可以通过iptables；如：-A INPUT -s 10.10.1.0/24 -p tcp -m state --state NEW -m tcp --dport 9966 -j ACCEPT ；
# 实际上，bind ip 绑定的是redis所在服务器网卡的ip，当然127.0.0.1也是可以的
#如果绑定一个外网ip，就会报错：Creating Server TCP listening socket xxx.xxx.xxx.xxx:9966: bind: Cannot assign requested address

# bind 127.0.0.1
bind 127.0.0.1 10.10.1.3

# 假设绑定是以上ip，使用 netstat -anp|grep 9966 会发现，这两个ip被bind，其中10.10.1.3是服务器网卡的ip
# tcp        0      0 10.10.1.3:9966         0.0.0.0:*                   LISTEN      11188/redis-server
# tcp        0      0 127.0.0.1:9966         0.0.0.0:*                   LISTEN      11188/redis-server 

# 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)
# 客户端和Redis服务端的连接超时时间，默认是0，表示永不超时。
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 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.
#
# 推荐一个合理的值就是60秒
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)
# 日志记录等级，4个可选值debug,verbose,notice,warning
# 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

# 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
#配置 log 文件地址,默认打印在命令行终端的窗口上，也可设为/dev/null屏蔽日志、
logfile "/data/logs/redis/redis.log"

# To enable logging to the system logger, just set ‘syslog-enabled‘ to yes,
# and optionally update the other syslog parameters to suit your needs.
# 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

# Specify the syslog identity.
# 设置 syslog 的 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
# 可用的数据库数，默认值为16，默认数据库为0，数据库范围在0-（database-1）之间
databases 16

################################ SNAPSHOTTING  ################################
################################ 快照          ################################
#
# 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 ""
# 在 900 秒内最少有 1 个 key 被改动，或者 300 秒内最少有 10 个 key 被改动，又或者 60 秒内最少有 1000 个 key 被改动，以上三个条件随便满足一个，就触发一次保存操作。

#    if(在60秒之内有10000个keys发生变化时){
#      进行镜像备份
#    }else if(在300秒之内有10个keys发生了变化){
#      进行镜像备份
#    }else if(在900秒之内有1个keys发生了变化){
#      进行镜像备份
#    }

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.
# 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
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.
# 在进行备份时,是否进行压缩
# 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

# 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.
# 读取和写入的时候是否支持CRC64校验，默认是开启的
rdbchecksum yes

# The filename where to dump the DB
# 备份文件的文件名
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.
# 数据库备份的文件放置的路径
# 路径跟文件名分开配置是因为 Redis 备份时，先会将当前数据库的状态写入到一个临时文件
# 等备份完成时，再把该临时文件替换为上面所指定的文件
# 而临时文件和上面所配置的备份文件都会放在这个指定的路径当中
# 默认值为 ./
dir /data/data/redis/

################################# REPLICATION #################################
################################# 主从复制    #################################
# 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.
#
# 设置该数据库为其他数据库的从数据库
# slaveof <masterip> <masterport> 当本机为从服务时，设置主服务的IP及端口
# 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.
#
# 指定与主数据库连接时需要的密码验证
# masterauth <master-password> 当本机为从服务时，设置访问master服务器的密码
# 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.
#
# 当slave服务器和master服务器失去连接后，或者当数据正在复制传输的时候，如果此参数值设置“yes”，slave服务器可以继续接受客户端的请求，否则，会返回给请求的客户端如下信息“SYNC with master in progress”,除了INFO，SLAVEOF这两个命令
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.
# 是否允许slave服务器节点只提供读服务
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 transfers 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.
#
# 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:
#
# 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.
#
# 设置主从复制过期时间
# 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.
# 指定向slave同步数据时，是否禁用socket的NO_DELAY选 项。若配置为“yes”，则禁用NO_DELAY，则TCP协议栈会合并小包统一发送，这样可以减少主从节点间的包数量并节省带宽，但会增加数据同步到 slave的时间。若配置为“no”，表明启用NO_DELAY，则TCP协议栈不会延迟小包的发送时机，这样数据同步的延时会减少，但需要更大的带宽。 通常情况下，应该配置为no以降低同步延时，但在主从节点间网络负载已经很高的情况下，可以配置为yes。
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.
#
# 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。

# 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.
#
# 在某些时候，master 不再连接 slaves，backlog 将被释放。
# 如果设置为 0 ，意味着绝不释放 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.
# 指定slave的优先级。在不只1个slave存在的部署环境下，当master宕机时，Redis
# Sentinel会将priority值最小的slave提升为master。
# 这个值越小，就越会被优先选中，需要注意的是，
# 若该配置项为0，则对应的slave永远不会自动提升为master。
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 ###################################
################################## 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.
#
# 设置连接redis的密码
# redis速度相当快，一个外部用户在一秒钟进行150K次密码尝试，需指定强大的密码来防止暴力破解
requirepass set_enough_strong_passwd

# 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.
# 重命名一些高危命令，用来禁止高危命令
rename-command FLUSHALL ZYzv6FOBdwflW2nX
rename-command CONFIG aI7zwm1GDzMMrEi
rename-command EVAL S9UHPKEpSvUJMM
rename-command FLUSHDB D60FPVDJuip7gy6l

################################### LIMITS ####################################
################################### 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).
#
# Once the limit is reached Redis will close all the new connections sending
# an error ‘max number of clients reached‘.
#
# 限制同时连接的客户数量,默认是10000
# 当连接数超过这个值时，redis 将不再接收其他连接请求，客户端尝试连接时将收到 error 信息
# 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‘).
#
# 设置redis能够使用的最大内存。
# 达到最大内存设置后，Redis会先尝试清除已到期或即将到期的Key（设置过expire信息的key）
# 在删除时,按照过期时间进行删除，最早将要被过期的key将最先被删除
# 如果已到期或即将到期的key删光，仍进行set操作，那么将返回错误
# 此时redis将不再接收写请求,只接收get请求。
# maxmemory的设置比较适合于把redis当作于类似memcached 的缓存来使用
# 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 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.

# redis 默认每次更新操作后会在后台异步的把数据库镜像备份到磁盘，但该备份非常耗时，且备份不宜太频繁
# redis 同步数据文件是按上面save条件来同步的
# 如果发生诸如拉闸限电、拔插头等状况,那么将造成比较大范围的数据丢失
# 所以redis提供了另外一种更加高效的数据库备份及灾难恢复方式
# 开启append only 模式后,redis 将每一次写操作请求都追加到appendonly.aof 文件中
# redis重新启动时,会从该文件恢复出之前的状态。
# 但可能会造成 appendonly.aof 文件过大，所以redis支持BGREWRITEAOF 指令，对appendonly.aof重新整理,默认是不开启的。

appendonly no

# The name of the append only file (default: "appendonly.aof")
# 默认为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".

# 设置对 appendonly.aof 文件进行同步的频率,有三种选择always、everysec、no，默认是everysec表示每秒同步一次。
# always 表示每次有写操作都进行同步,everysec 表示对写操作进行累积,每秒同步一次。
# no表示等操作系统进行数据缓存同步到磁盘，都进行同步,everysec 表示对写操作进行累积,每秒同步一次
# 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.
# 指定是否在后台aof文件rewrite期间调用fsync，默认为no，表示要调用fsync（无论后台是否有子进程在刷盘）。Redis在后台写RDB文件或重写afo文件期间会存在大量磁盘IO，此时，在某些linux系统中，调用fsync可能会阻塞。
no-appendfsync-on-rewrite yes

# 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.
# 指定Redis重写aof文件的条件，默认为100，表示与上次rewrite的aof文件大小相比，当前aof文件增长量超过上次afo文件大小的100%时，就会触发background rewrite。若配置为0，则会禁用自动rewrite
auto-aof-rewrite-percentage 100

# 指定触发rewrite的aof文件大小。若aof文件小于该值，即使当前文件的增量比例达到auto-aof-rewrite-percentage的配置值，也不会触发自动rewrite。即这两个配置项同时满足时，才会触发rewrite。
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.
# 一个Lua脚本最长的执行时间，单位为毫秒，如果为0或负数表示无限执行时间，默认为5000
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 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

# 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

# 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

################################ 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 [email protected]__:foo del
# PUBLISH [email protected]__: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 [email protected]<db>__ prefix.
#  E     Keyevent events, published with [email protected]<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 [email protected]__: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.
# 当hash中包含超过指定元素个数并且最大的元素没有超过临界时，
# hash将以一种特殊的编码方式（大大减少内存使用）来存储，这里可以设置这两个临界值
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数据类型多少节点以下会采用去指针的紧凑存储格式。
# list数据类型节点值大小小于多少字节会采用紧凑存储格式。
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数据类型内部数据如果全部是数值型，且包含多少节点以下会采用紧凑格式存储。
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:

# zsort数据类型多少节点以下会采用去指针的紧凑存储格式。
# zsort数据类型节点值大小小于多少字节会采用紧凑存储格式。
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.

# Redis将在每100毫秒时使用1毫秒的CPU时间来对redis的hash表进行重新hash，可以降低内存的使用
# 当你的使用场景中，有非常严格的实时性需要，不能够接受Redis时不时的对请求有2毫秒的延迟的话，把这项配置为no。
# 如果没有这么严格的实时性要求，可以设置为yes，以便能够尽可能快的释放内存
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过程中,是否采取增量文件同步策略,默认为“yes”。 rewrite过程中,每32M数据进行一次文件同步,这样可以减少aof大文件写入对磁盘的操作次数
aof-rewrite-incremental-fsync yes

# redis数据存储
redis的存储分为内存存储、磁盘存储和log文件三部分，配置文件中有三个参数对其进行配置。
save seconds updates，save配置，指出在多长时间内，有多少次更新操作，就将数据同步到数据文件。可多个条件配合，默认配置了三个条件。
appendonly yes/no ，appendonly配置，指出是否在每次更新操作后进行日志记录，如果不开启，可能会在断电时导致一段时间内的数据丢失。因为redis本身同步数据文件是按上面的save条件来同步的，所以有的数据会在一段时间内只存在于内存中。
appendfsync no/always/everysec ，appendfsync配置，no表示等操作系统进行数据缓存同步到磁盘，always表示每次更新操作后手动调用fsync()将数据写到磁盘，everysec表示每秒同步一次。

Redis的内存淘汰策略

Redis占用内存大小

我们知道Redis是基于内存的key-value数据库，因为系统的内存大小有限，所以我们在使用Redis的时候可以配置Redis能使用的最大的内存大小。

1、通过配置文件配置

通过在Redis安装目录下面的redis.conf配置文件中添加以下配置设置内存大小

//设置Redis最大占用内存大小为100M
maxmemory 100mb
复制代码

redis的配置文件不一定使用的是安装目录下面的redis.conf文件，启动redis服务的时候是可以传一个参数指定redis的配置文件的

2、通过命令修改

Redis支持运行时通过命令动态修改内存大小

//设置Redis最大占用内存大小为100M
127.0.0.1:6379> config set maxmemory 100mb
//获取设置的Redis能使用的最大内存大小
127.0.0.1:6379> config get maxmemory
复制代码

如果不设置最大内存大小或者设置最大内存大小为0，在64位操作系统下不限制内存大小，在32位操作系统下最多使用3GB内存

Redis的内存淘汰

既然可以设置Redis最大占用内存大小，那么配置的内存就有用完的时候。那在内存用完的时候，还继续往Redis里面添加数据不就没内存可用了吗？

实际上Redis定义了几种策略用来处理这种情况：

noeviction(默认策略)：对于写请求不再提供服务，直接返回错误（DEL请求和部分特殊请求除外）

allkeys-lru：从所有key中使用LRU算法进行淘汰

volatile-lru：从设置了过期时间的key中使用LRU算法进行淘汰

allkeys-random：从所有key中随机淘汰数据

volatile-random：从设置了过期时间的key中随机淘汰

volatile-ttl：在设置了过期时间的key中，根据key的过期时间进行淘汰，越早过期的越优先被淘汰

当使用volatile-lru、volatile-random、volatile-ttl这三种策略时，如果没有key可以被淘汰，则和noeviction一样返回错误

如何获取及设置内存淘汰策略

获取当前内存淘汰策略：

127.0.0.1:6379> config get maxmemory-policy
复制代码

通过配置文件设置淘汰策略（修改redis.conf文件）：

maxmemory-policy allkeys-lru
复制代码

通过命令修改淘汰策略：

127.0.0.1:6379> config set maxmemory-policy allkeys-lru
复制代码

LRU算法

什么是LRU?

上面说到了Redis可使用最大内存使用完了，是可以使用LRU算法进行内存淘汰的，那么什么是LRU算法呢？

LRU(Least Recently Used)，即最近最少使用，是一种缓存置换算法。在使用内存作为缓存的时候，缓存的大小一般是固定的。当缓存被占满，这个时候继续往缓存里面添加数据，就需要淘汰一部分老的数据，释放内存空间用来存储新的数据。这个时候就可以使用LRU算法了。其核心思想是：如果一个数据在最近一段时间没有被用到，那么将来被使用到的可能性也很小，所以就可以被淘汰掉。

使用java实现一个简单的LRU算法

public class LRUCache<k, v> {
    //容量
    private int capacity;
    //当前有多少节点的统计
    private int count;
    //缓存节点
    private Map<k, Node<k, v>> nodeMap;
    private Node<k, v> head;
    private Node<k, v> tail;

    public LRUCache(int capacity) {
        if (capacity < 1) {
            throw new IllegalArgumentException(String.valueOf(capacity));
        }
        this.capacity = capacity;
        this.nodeMap = new HashMap<>();
        //初始化头节点和尾节点，利用哨兵模式减少判断头结点和尾节点为空的代码
        Node headNode = new Node(null, null);
        Node tailNode = new Node(null, null);
        headNode.next = tailNode;
        tailNode.pre = headNode;
        this.head = headNode;
        this.tail = tailNode;
    }

    public void put(k key, v value) {
        Node<k, v> node = nodeMap.get(key);
        if (node == null) {
            if (count >= capacity) {
                //先移除一个节点
                removeNode();
            }
            node = new Node<>(key, value);
            //添加节点
            addNode(node);
        } else {
            //移动节点到头节点
            moveNodeToHead(node);
        }
    }

    public Node<k, v> get(k key) {
        Node<k, v> node = nodeMap.get(key);
        if (node != null) {
            moveNodeToHead(node);
        }
        return node;
    }

    private void removeNode() {
        Node node = tail.pre;
        //从链表里面移除
        removeFromList(node);
        nodeMap.remove(node.key);
        count--;
    }

    private void removeFromList(Node<k, v> node) {
        Node pre = node.pre;
        Node next = node.next;

        pre.next = next;
        next.pre = pre;

        node.next = null;
        node.pre = null;
    }

    private void addNode(Node<k, v> node) {
        //添加节点到头部
        addToHead(node);
        nodeMap.put(node.key, node);
        count++;
    }

    private void addToHead(Node<k, v> node) {
        Node next = head.next;
        next.pre = node;
        node.next = next;
        node.pre = head;
        head.next = node;
    }

    public void moveNodeToHead(Node<k, v> node) {
        //从链表里面移除
        removeFromList(node);
        //添加节点到头部
        addToHead(node);
    }

    class Node<k, v> {
        k key;
        v value;
        Node pre;
        Node next;

        public Node(k key, v value) {
            this.key = key;
            this.value = value;
        }
    }
}

复制代码

上面这段代码实现了一个简单的LUR算法，代码很简单，也加了注释，仔细看一下很容易就看懂。

LRU在Redis中的实现

近似LRU算法

Redis使用的是近似LRU算法，它跟常规的LRU算法还不太一样。近似LRU算法通过随机采样法淘汰数据，每次随机出5（默认）个key，从里面淘汰掉最近最少使用的key。

可以通过maxmemory-samples参数修改采样数量： 例：maxmemory-samples 10 maxmenory-samples配置的越大，淘汰的结果越接近于严格的LRU算法

Redis为了实现近似LRU算法，给每个key增加了一个额外增加了一个24bit的字段，用来存储该key最后一次被访问的时间。

Redis3.0对近似LRU的优化

Redis3.0对近似LRU算法进行了一些优化。新算法会维护一个候选池（大小为16），池中的数据根据访问时间进行排序，第一次随机选取的key都会放入池中，随后每次随机选取的key只有在访问时间小于池中最小的时间才会放入池中，直到候选池被放满。当放满后，如果有新的key需要放入，则将池中最后访问时间最大（最近被访问）的移除。

当需要淘汰的时候，则直接从池中选取最近访问时间最小（最久没被访问）的key淘汰掉就行。

LRU算法的对比

我们可以通过一个实验对比各LRU算法的准确率，先往Redis里面添加一定数量的数据n，使Redis可用内存用完，再往Redis里面添加n/2的新数据，这个时候就需要淘汰掉一部分的数据，如果按照严格的LRU算法，应该淘汰掉的是最先加入的n/2的数据。 生成如下各LRU算法的对比图（图片来源）：

你可以看到图中有三种不同颜色的点：

• 浅灰色是被淘汰的数据
• 灰色是没有被淘汰掉的老数据
• 绿色是新加入的数据

我们能看到Redis3.0采样数是10生成的图最接近于严格的LRU。而同样使用5个采样数，Redis3.0也要优于Redis2.8。

LFU算法

LFU算法是Redis4.0里面新加的一种淘汰策略。它的全称是Least Frequently Used，它的核心思想是根据key的最近被访问的频率进行淘汰，很少被访问的优先被淘汰，被访问的多的则被留下来。

LFU算法能更好的表示一个key被访问的热度。假如你使用的是LRU算法，一个key很久没有被访问到，只刚刚是偶尔被访问了一次，那么它就被认为是热点数据，不会被淘汰，而有些key将来是很有可能被访问到的则被淘汰了。如果使用LFU算法则不会出现这种情况，因为使用一次并不会使一个key成为热点数据。

LFU一共有两种策略：

• volatile-lfu：在设置了过期时间的key中使用LFU算法淘汰key
• allkeys-lfu：在所有的key中使用LFU算法淘汰数据

设置使用这两种淘汰策略跟前面讲的一样，不过要注意的一点是这两周策略只能在Redis4.0及以上设置，如果在Redis4.0以下设置会报错

问题

最后留一个小问题，可能有的人注意到了，我在文中并没有解释为什么Redis使用近似LRU算法而不使用准确的LRU算法，可能是因为他这个实现起来比严格的简单,最终结果也差不了多少 还省内存所以没必要用严格吧。

原文地址：https://www.cnblogs.com/superlsj/p/11618694.html