Redis学习

1：redis可以干什么?

1、商品基本信息（与库存分开）、商品分类 是基本不变的，这些信息全部可以一次性加载到 redis 中，作为只读信息，直接从 redis 中查询。或者不使用 redis，而是加数据库只读从库（MySQL中可以配置memcached作为数据缓存），从从库中读取数据。

2、用户登录信息（集中式 session）

3、未登录的购物车信息（设置过期时间，key 保存在客户端 cookie，取回的时候注意校验，防止攻击）

4、用户的收货地址、各种评论信息等等（登录时加载）

5、用户经常浏览的商品分类

等等，根据业务不同，只要是业务中  读取比例超过 7:3 的，都可以加载到 redis 中。低于 7:3 的根据并发等情况选择。

 

2：redis资料下载

https://github.com/dmajkic/redis/downloads 

 

3：环境搭建

3.1：window

3.1.1：参考资料
http://www.redis.io/

3.1.2：目录结构
  略
3.1.3：redis.conf配置文件说明
# Redis configuration file example

# Note on units: when memory size is needed, it is possible to specifiy
# 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.

# 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
Redis默认不是以守护进程的方式运行，可以通过该配置项修改，使用yes启用守护进程

# 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
当Redis以守护进程方式运行时，Redis默认会把pid写入/var/run/redis.pid文件，可以通过pidfile指定
# Accept connections on the specified port, default is 6379.
# If port 0 is specified Redis will not listen on a TCP socket.
port 6379
指定Redis监听端口，默认端口为6379
# If you want you can bind a single interface, if the bind option is not
# specified all the interfaces will listen for incoming connections.
#
# bind 127.0.0.1
绑定的主机地址
# 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 755

# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
当 客户端闲置多长时间后关闭连接，如果指定为0，表示关闭该功能
# Set server verbosity to 'debug'
# it 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 verbose
指定日志记录级别，Redis总共支持四个级别：debug、verbose、notice、warning，默认为verbose
# Specify the log file name. Also 'stdout' 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 stdout
日志记录方式，默认为标准输出，如果配置Redis为守护进程方式运行，而这里又配置为日志记录方式为标准输出，则日志将会发送给/dev/null
# 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
设置数据库的数量，默认数据库为0，可以使用SELECT <dbid>命令在连接上指定数据库id
################################ 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 at all commenting all the "save" lines.

save 900 1
save 300 10
save 60 10000
分别表示900秒（15分钟）内有1个更改，300秒（5分钟）内有10个更改以及60秒内有10000个更改。
指定在多长时间内，有多少次更新操作，就将数据同步到数据文件，可以多个条件配合
# 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
指定存储至本地数据库时是否压缩数据，默认为yes，Redis采用LZF压缩，如果为了节省CPU时间，可以关闭该选项，但会导致数据库文件变的巨大
# The filename where to dump the DB
dbfilename dump.rdb
指定本地数据库文件名，默认值为dump.rdb
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the 'dbfilename' configuration directive.
#
# Also the Append Only File will be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir ./
指定本地数据库存放目录
################################# REPLICATION #################################

# Master-Slave replication. Use slaveof to make a Redis instance a copy of
# another Redis server. Note that the configuration is local to the slave
# so for example it is possible to configure the slave to save the DB with a
# different interval, or to listen to another port, and so on.
#
# slaveof <masterip> <masterport>
slaveof <masterip> <masterport> 设置当本机为slav服务时，设置master服务的IP地址及端口，在Redis启动时，它会自动从master进行数据同步
# 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>
masterauth <master-password> 当master服务设置了密码保护时，slav服务连接master的密码
# When a slave lost the 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 data 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

# 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 a timeout for both Bulk transfer I/O timeout and
# master data or ping response timeout. The default value is 60 seconds.
#
# 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

################################## 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
requirepass foobared 设置Redis连接密码，如果配置了连接密码，客户端在连接Redis时需要通过AUTH <password>命令提供密码，默认关闭
# Command renaming.
#
# It is possilbe to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# of hard to guess so that it will be still available for internal-use
# tools but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possilbe to completely kill a command renaming it into
# an empty string:
#
# rename-command CONFIG ""

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

# Set the max number of connected clients at the same time. By default there
# is no limit, and it's up to the number of file descriptors the Redis process
# is able to open. The special value '0' means no limits.
# Once the limit is reached Redis will close all the new connections sending
# an error 'max number of clients reached'.
#
# maxclients 128
maxclients 128 设置同一时间最大客户端连接数，默认无限制，Redis可以同时打开的客户端连接数为Redis进程可以打开的最大文件描述符数，如果设置 maxclients 0，表示不作限制。当客户端连接数到达限制时，Redis会关闭新的连接并向客户端返回max number of clients reached错误信息
# Don't use more memory than the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys with an
# EXPIRE set. It will try to start freeing keys that are going to expire
# in little time and preserve keys with a longer time to live.
# Redis will also try to remove objects from free lists if possible.
#
# If all this fails, Redis will start to reply with errors to commands
# that will use more memory, like SET, LPUSH, and so on, and will continue
# to reply to most read-only commands like GET.
#
# WARNING: maxmemory can be a good idea mainly if you want to use Redis as a
# 'state' server or cache, not as a real DB. When Redis is used as a real
# database the memory usage will grow over the weeks, it will be obvious if
# it is going to use too much memory in the long run, and you'll have the time
# to upgrade. With maxmemory after the limit is reached you'll start to get
# errors for write operations, and this may even lead to DB inconsistency.
#
# maxmemory <bytes>
maxmemory <bytes>指定Redis最大内存限制，Redis在启动时会把数据加载到内存中，达到最大内存后，Redis会先尝试清除已到期或即将到期的Key，当此方法处理 后，仍然到达最大内存设置，将无法再进行写入操作，但仍然可以进行读取操作。Redis新的vm机制，会把Key存放内存，Value会存放在swap区
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached? You can select among five behavior:
#
# volatile-lru -> remove the key with an expire set using an LRU algorithm
# allkeys-lru -> remove any key accordingly 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 all the kind of policies, Redis will return an error on write
# operations, when there are not suitable keys for eviction.
#
# At the date of writing this commands are: set setnx setex append
# incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
# sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
# zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
# getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy 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. If you can live
# with the idea that the latest records will be lost if something like a crash
# happens this is the preferred way to run Redis. If instead you care a lot
# about your data and don't want to that a single record can get lost you should
# enable the append only mode: when this mode is enabled Redis will append
# every write operation received in the file appendonly.aof. This file will
# be read on startup in order to rebuild the full dataset in memory.
#
# Note that you can have both the async dumps and the append only file if you
# like (you have to comment the "save" statements above to disable the dumps).
# Still if append only mode is enabled Redis will load the data from the
# log file at startup ignoring the dump.rdb file.
#
# IMPORTANT: Check the BGREWRITEAOF to check how to rewrite the append
# log file in background when it gets too big.

appendonly no
appendonly no指定是否在每次更新操作后进行日志记录，Redis在默认情况下是异步的把数据写入磁盘，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。默认为no
# The name of the append only file (default: "appendonly.aof")
# appendfilename appendonly.aof
appendfilename appendonly.aof指定更新日志文件名，默认为appendonly.aof
# The fsync() call tells the Operating System to actually write data on disk
# instead to wait for more data in the output buffer. Some OS will really flush
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log . Slow, Safest.
# everysec: fsync only if one second passed since the last fsync. Compromise.
#
# The default is "everysec" 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 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.
#
# If unsure, use "everysec".

# appendfsync always
appendfsync everysec
# appendfsync no
指定更新日志条件，共有3个可选值：
no：表示等操作系统进行数据缓存同步到磁盘（快）
always：表示每次更新操作后手动调用fsync()将数据写到磁盘（慢，安全）
everysec：表示每秒同步一次（折衷，默认值）
# 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", that in pratical terms means that it is
# possible to lost 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 will growth by the specified percentage.
#
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (or if no rewrite 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 precentage of zero in order to disable the automatic AOF
# rewrite feature.

auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb

################################## 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 1024

################################ VIRTUAL MEMORY ###############################

### WARNING! Virtual Memory is deprecated in Redis 2.4
### The use of Virtual Memory is strongly discouraged.

### WARNING! Virtual Memory is deprecated in Redis 2.4
### The use of Virtual Memory is strongly discouraged.

# Virtual Memory allows Redis to work with datasets bigger than the actual
# amount of RAM needed to hold the whole dataset in memory.
# In order to do so very used keys are taken in memory while the other keys
# are swapped into a swap file, similarly to what operating systems do
# with memory pages.
#
# To enable VM just set 'vm-enabled' to yes, and set the following three
# VM parameters accordingly to your needs.

vm-enabled no
指定是否启用虚拟内存机制，默认值为no，简单的介绍一下，VM机制将数据分页存放，由Redis将访问量较少的页即冷数据swap到磁盘上，访问多的页面由磁盘自动换出到内存中（在后面的文章我会仔细分析Redis的VM机制）
# vm-enabled yes

# This is the path of the Redis swap file. As you can guess, swap files
# can't be shared by different Redis instances, so make sure to use a swap
# file for every redis process you are running. Redis will complain if the
# swap file is already in use.
#
# The best kind of storage for the Redis swap file (that's accessed at random)
# is a Solid State Disk (SSD).
#
# *** WARNING *** if you are using a shared hosting the default of putting
# the swap file under /tmp is not secure. Create a dir with access granted
# only to Redis user and configure Redis to create the swap file there.
vm-swap-file /tmp/redis.swap
虚拟内存文件路径，默认值为/tmp/redis.swap，不可多个Redis实例共享
# vm-max-memory configures the VM to use at max the specified amount of
# RAM. Everything that deos not fit will be swapped on disk *if* possible, that
# is, if there is still enough contiguous space in the swap file.
#
# With vm-max-memory 0 the system will swap everything it can. Not a good
# default, just specify the max amount of RAM you can in bytes, but it's
# better to leave some margin. For instance specify an amount of RAM
# that's more or less between 60 and 80% of your free RAM.
vm-max-memory 0
将所有大于vm-max-memory的数据存入虚拟内存,无论vm-max-memory设置多小,所有索引数据都是内存存储的(Redis的索引数据 就是keys),也就是说,当vm-max-memory设置为0的时候,其实是所有value都存在于磁盘。默认值为0
# Redis swap files is split into pages. An object can be saved using multiple
# contiguous pages, but pages can't be shared between different objects.
# So if your page is too big, small objects swapped out on disk will waste
# a lot of space. If you page is too small, there is less space in the swap
# file (assuming you configured the same number of total swap file pages).
#
# If you use a lot of small objects, use a page size of 64 or 32 bytes.
# If you use a lot of big objects, use a bigger page size.
# If unsure, use the default :)
vm-page-size 32
Redis swap文件分成了很多的page，一个对象可以保存在多个page上面，但一个page上不能被多个对象共享，vm-page-size是要根据存储的 数据大小来设定的，作者建议如果存储很多小对象，page大小最好设置为32或者64bytes；如果存储很大大对象，则可以使用更大的page，如果不 确定，就使用默认值
# Number of total memory pages in the swap file.
# Given that the page table (a bitmap of free/used pages) is taken in memory,
# every 8 pages on disk will consume 1 byte of RAM.
#
# The total swap size is vm-page-size * vm-pages
#
# With the default of 32-bytes memory pages and 134217728 pages Redis will
# use a 4 GB swap file, that will use 16 MB of RAM for the page table.
#
# It's better to use the smallest acceptable value for your application,
# but the default is large in order to work in most conditions.
vm-pages 134217728
设置swap文件中的page数量，由于页表（一种表示页面空闲或使用的bitmap）是在放在内存中的，，在磁盘上每8个pages将消耗1byte的内存。
# Max number of VM I/O threads running at the same time.
# This threads are used to read/write data from/to swap file, since they
# also encode and decode objects from disk to memory or the reverse, a bigger
# number of threads can help with big objects even if they can't help with
# I/O itself as the physical device may not be able to couple with many
# reads/writes operations at the same time.
#
# The special value of 0 turn off threaded I/O and enables the blocking
# Virtual Memory implementation.
vm-max-threads 4
设置访问swap文件的线程数,最好不要超过机器的核数,如果设置为0,那么所有对swap文件的操作都是串行的，可能会造成比较长时间的延迟。默认值为4
############################### ADVANCED CONFIG ###############################

# Hashes are encoded in a special way (much more memory efficient) when they
# have at max a given numer of elements, and the biggest element does not
# exceed a given threshold. You can configure this limits with the following
# configuration directives.
hash-max-zipmap-entries 512
hash-max-zipmap-value 64
指定在超过一定的数量或者最大的元素超过某一临界值时，采用一种特殊的哈希算法
# Similarly to hashes, small lists are also encoded in a special way in order
# to save a lot of space. The special representation is only used when
# you are under the following limits:
list-max-ziplist-entries 512
list-max-ziplist-value 64

# Sets have a special encoding in just one case: when a set is composed
# of just strings that happens to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512

# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64

# 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 an hash table
# that is rhashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
#
# The default is to use this millisecond 10 times every second in order to
# active rehashing the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply form time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes

################################## INCLUDES ###################################

# Include one or more other config files here. This is useful if you
# have a standard template that goes to all redis server but also need
# to customize a few per-server settings. Include files can include
# other files, so use this wisely.
#
# include /path/to/local.conf
# include /path/to/other.conf
指定包含其它的配置文件，可以在同一主机上多个Redis实例之间使用同一份配置文件，而同时各个实例又拥有自己的特定配置文件

4：简单使用jedis

需导入JsonMyUtil.java

package SimpleDemo1;

import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;

import org.junit.Before;
import org.junit.Test;

import redis.clients.jedis.Jedis;

import com.xyzh.utils.JsonMyUtil;
import com.xyzh.utils.Users;

public class Demo1 {
Jedis jedis;
@Before
public void main() {
//创建jedis对象(参数1:ip;参数2:端口;参数3:多少时间将内存的数据写入硬盘)
jedis = new Jedis("127.0.0.1", 6379,100000);
}
/**
* Redis存储初级的字符串 CRUD
*/
@Test
public void testBasicString() {
//添加数据
jedis.set("name", "Hello");
System.out.println(jedis.get("name"));//name=Hello

//追加数据
jedis.append("name", "Word");
System.out.println(jedis.get("name"));//name=HelloWord

//直接覆盖原来的数据
jedis.set("name", "tony");
System.out.println(jedis.get("name"));//name=tony

//删除key对应的记录
jedis.del("name");
System.out.println(jedis.get("name"));//name=null

//批量添加数据
jedis.mset("name", "minxr", "jarorwar", "tony");//mset(key1,value1,key2,value2,...)
System.out.println(jedis.mget("name", "jarorwar"));//mget(key1,key2,...);返回list
}

/**
* jedis操作Map
* 1:本案例只演示 :操作 string类型
*/
@Test
public void testMap() {
//添加数据
Map<String, String> userMap = new HashMap<String, String>();
userMap.put("name", "张三");
userMap.put("pwd", "123456");
jedis.hmset("userMap", userMap);

//根据key获取value
List<String> rsmap = jedis.hmget("userMap", "name","pwd");//hmget(缓存中标识名称,userMap中的key1,userMap中的key2,...)
System.out.println(rsmap);//输出[张三, 123456]

//删除map中的某个键值
jedis.hdel("userMap","pwd");
System.out.println(jedis.hget("userMap", "pwd"));//输出null

//返回在缓存中标记为userMap的中存放的个数
System.out.println(jedis.hlen("userMap"));

//是否存在key为user的记录 返回true
System.out.println(jedis.exists("userMap"));

//返回map对象中的所有key
System.out.println(jedis.hkeys("userMap"));

//返回map对象中的所有value
System.out.println(jedis.hvals("userMap"));

//遍历map
Iterator<String> iter = jedis.hkeys("userMap").iterator();
while (iter.hasNext()) {
String key = iter.next();
System.out.println(key + ":" + jedis.mget("userMap", key)); //输出:name=[张三]
}
}

/**
* jedis操作List
* 没找到移除list中单个值的数据
*/
@Test
public void testList() {
//删除数据（清空）
jedis.del("titleList");

//添加数据
jedis.lpush("titleList", "今天是什么日子");
jedis.lpush("titleList", "下周五要考科二了");
jedis.lpush("titleList", "明天开始自由啦");

//获取数据示例1：返回list
System.out.println(jedis.lrange("titleList", 0, -1));//-1表示取得所有
System.out.println("********************************");

//获取数据示例2：根据索引获取
Long llen = jedis.llen("titleList");
for (int i = 0; i < llen; i++) {
String lindex = jedis.lindex("titleList", i);
System.out.println(lindex);
}
}

/**
* jedis操作Set
*/
@Test
public void testSet() {
//删除数据（清空）
jedis.del("titleSet");

//添加数据
jedis.sadd("titleSet", "今天是什么日子");
jedis.sadd("titleSet", "下周五要考科二了");
jedis.sadd("titleSet", "明天开始自由啦");

// 移除(标记名,值1,值2)
//jedis.srem("titleSet", "明天开始自由啦");

//获取集合的所有元素
Set<String> sunion = jedis.sunion("titleSet");
Iterator<String> iterator = sunion.iterator();
while(iterator.hasNext())
{
System.out.println(iterator.next());
}

//获取所有加入的value
System.out.println(jedis.smembers("titleSet"));
System.out.println(jedis.sinter("titleSet"));

//判断集合中存在某个元素 （true/flase)
System.out.println(jedis.sismember("titleSet", "明天开始自由啦"));//不是值包含，而是equest!

//返回一个随机元素从一组,没有删除的元素。
System.out.println(jedis.srandmember("titleSet"));

//返回集合的元素个数
System.out.println(jedis.scard("titleSet"));
}

/**
* Redis操作javabean
* redis中没有直接操作对象的，如果非要存储，我们可采用将对象转json后以字符串保存
*/
@Test
public void testObject()
{
//存储数据
Users us1 = new Users("张三",19);
String userJson = JsonMyUtil.object2json(us1);
jedis.set("user", userJson);

//取数据
userJson = jedis.get("user");
Users us2 = JsonMyUtil.jsonToObject(userJson,Users.class);
System.out.println(us2.getName());
}

/**
* redis 超时设置
*/
@Test
public void testTime()
{
//设置某个key的存活时间
Long expireAt = jedis.expireAt("titleSet", 3000);
System.out.println("expireAt="+expireAt);

//获取此key的存储有有效时间;-1表示永久
Long ttl = jedis.ttl("titleSet");
System.out.println(ttl);
try {
Thread.sleep(3000);
} catch (InterruptedException e) {
e.printStackTrace();
}
Boolean exists = jedis.exists("titleSet");
System.out.println("exists="+exists);//false
}
}

 

5：带数据源使用jedis

5.1：导入JedisPoolUtils

package com.xyzh.utils;

import java.util.ResourceBundle;

import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.JedisPoolConfig;
/**
*
* 初始化redis连接池
* 1:要求在src导入redis.properties文件
* 2:调用getJedis();
*
* @author hb
* @date 2015年5月15日 下午4:06:59
*/
public class JedisPoolUtils {
private static JedisPool jedisPool;
/**
* 初始化Redis连接池
*/
static {
ResourceBundle bundle = ResourceBundle.getBundle("redis");
if (bundle == null) {
throw new IllegalArgumentException(
"[redis.properties] is not found!");
}
JedisPoolConfig config = new JedisPoolConfig();
config.setMaxActive(Integer.valueOf(bundle
.getString("redis.pool.maxActive")));
config.setMaxIdle(Integer.valueOf(bundle
.getString("redis.pool.maxIdle")));
config.setMaxWait(Long.valueOf(bundle.getString("redis.pool.maxWait")));
config.setTestOnBorrow(Boolean.valueOf(bundle
.getString("redis.pool.testOnBorrow")));
config.setTestOnReturn(Boolean.valueOf(bundle
.getString("redis.pool.testOnReturn")));
if(bundle.containsKey("redis.password"))
jedisPool = new JedisPool(config, bundle.getString("redis.ip"),Integer.valueOf(bundle.getString("redis.port")),Integer.valueOf(bundle.getString("redis.pool.outtime")),bundle.getString("redis.password"));
else
jedisPool = new JedisPool(config, bundle.getString("redis.ip"),Integer.valueOf(bundle.getString("redis.port")),Integer.valueOf(bundle.getString("redis.pool.outtime")));
}

/**
* 获取Jedis实例
* @return
*/
public synchronized static Jedis getJedis() {
try {
if (jedisPool != null) {
Jedis resource = jedisPool.getResource();
return resource;
} else {
return null;
}
} catch (Exception e) {
e.printStackTrace();
return null;
}
}

/**
* 释放jedis资源
* @param jedis
*/
public static void returnResource(final Jedis jedis) {
if (jedis != null) {
jedisPool.returnResource(jedis);
}
}

/**
* 获取连接池
* @return 连接池对象
*/
public static JedisPool getJedisPool() {
return jedisPool;
}
}

5.2：调用示例

/**
* 带数据源使用jedis
*
* @Author hubiao
* @CreateDate 2015-5-17 下午1:13:25
*/
public class Demo2 {
Jedis jedis;
@Before
public void main() {
jedis = JedisPoolUtils.getJedis();
}
@Test
public void test()
{
//添加数据
jedis.set("name","Hello");
//追加数据
jedis.append("name", "Word2");
//获取数据
String name = jedis.get("name");
System.out.println(name);//name=HelloWord2
//删除数据
jedis.del("name");
name = jedis.get("name");
System.out.println(name);//name=null
}
}

6：spring整合redis

6.1：导入jar包
 

6.2：配置文件
Ø redis.properties
#最大分配的对象数
redis.pool.maxActive=1024
#最大能够保持idel状态的对象数
redis.pool.maxIdle=200
#当池内没有返回对象时，最大等待时间
redis.pool.maxWait=1000
#当调用borrow Object方法时，是否进行有效性检查
redis.pool.testOnBorrow=true
#当调用return Object方法时，是否进行有效性检查
redis.pool.testOnReturn=true
#输出时间
redis.pool.outtime=10000
#IP
redis.ip=127.0.0.1
#Port
redis.port=6379
#password
redis.password=admin
Ø bean.xml
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:context="http://www.springframework.org/schema/context"
xmlns:aop="http://www.springframework.org/schema/aop" xmlns:tx="http://www.springframework.org/schema/tx"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.0.xsd http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring-tx-3.0.xsd http://www.springframework.org/schema/aop http://www.springframework.org/schema/aop/spring-aop-3.0.xsd">
<context:annotation-config />
<context:component-scan base-package="com.abin.lee.spring.redis"></context:component-scan>

<!-- 加载propties -->
<context:property-placeholder location="classpath:redis.properties" />

<!-- 初始化连接池 -->
<bean id="jedisPoolConfig" class="redis.clients.jedis.JedisPoolConfig">
<property name="maxActive" value="${redis.pool.maxActive}"/>
<property name="maxIdle" value="${redis.pool.maxIdle}"/>
<property name="maxWait" value="${redis.pool.maxWait}"/>
<property name="testOnBorrow" value="${redis.pool.testOnBorrow}"/>
</bean>

<!-- 工厂实现-->
<bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory">
<property name="hostName" value="${redis.ip}" />
<property name="port" value="${redis.port}" />
<property name="password" value="${redis.password}" />
<property name="poolConfig" ref="jedisPoolConfig" />
</bean>
<!-- spring模版 -->
<bean id="redisTemplate" class="org.springframework.data.redis.core.RedisTemplate">
<property name="connectionFactory" ref="jedisConnectionFactory"></property>
</bean>
</beans>

 

6.3：示例

package SimpleDemo;

import java.util.Iterator;
import java.util.List;
import java.util.Set;

import org.junit.Before;
import org.junit.Test;
import org.springframework.context.ApplicationContext;
import org.springframework.context.support.ClassPathXmlApplicationContext;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.ListOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
/**
* spring+数据池+redis
*
* @Author hubiao
* @CreateDate 2015-5-17 下午1:47:39
*/
@SuppressWarnings("rawtypes")
public class Demo3 {
RedisTemplate redisTemplate;
@Before
public void main()
{
ApplicationContext application = new ClassPathXmlApplicationContext("bean.xml");
redisTemplate = (RedisTemplate) application.getBean("redisTemplate");
}
/**
* 操作属性
*/
@Test
public void testAttri()
{
redisTemplate.delete("name");
//添加
ValueOperations vo = redisTemplate.opsForValue();
vo.set("name", "张三22");
//追加(这里很费解，不知怎么追加失败)
Integer append = vo.append("name", "11111111111@");
System.out.println(append);
//获取
Object object = vo.get("name");
System.out.println(object);
}
/**
* 操作 Set
*/
@Test
public void testSet()
{
//添加数据
redisTemplate.delete("nameSet");
SetOperations set = redisTemplate.opsForSet();
set.add("nameSet", "值1");
set.add("nameSet", "值2");
set.add("nameSet", "值2");
//移除list中的值，
// set.remove("nameSet", "值2");//参数1：属性值,3:参数值
//遍历
Set members = set.members("nameSet");
System.out.println(members);
}
/**
* 操作list
*/
@Test
public void testList()
{
redisTemplate.delete("nameList");
//添加数据
ListOperations list = redisTemplate.opsForList();
list.leftPush("nameList", "值1");
list.leftPush("nameList", "值2");
list.leftPush("nameList", "值2");
//移除list中的值，
list.remove("nameList", 2, "值2");//参数1：属性值,参数2:值次数,3:参数值
//遍历
List range = list.range("nameList", 0, -1);
System.out.println(range);
}
/**
* 操作Map
*/
@Test
public void testMap()
{
//添加数据
HashOperations hash = redisTemplate.opsForHash();
hash.put("nameMap", "aaa","张三");
hash.put("nameMap", "bbb","王五");
hash.put("nameMap", "ccc","李四");
//根据key获取value
Object object2 = hash.get("nameMap", "aaa");//参数1:缓存中key,参数2:map中key
System.out.println(object2);
//移除key
//hash.delete("nameMap", "aaa");
//判断是否存在某个key
Boolean hasKey = hash.hasKey("nameMap", "aaa");
System.out.println(hasKey);
//遍历
Set keys = hash.keys("nameMap");
Iterator iterator = keys.iterator();
while(iterator.hasNext())
{
Object key = iterator.next();
Object value = hash.get("nameMap", key);
System.out.println(key+"="+value);
}
}
}