spring4.0.9结合redis进行数据的缓存

一、今天将以前公司的由SpringMVC搭建的框架和redis整合。Spring版本为4.0.9  redis安装在linux(CentOS6.5)下面。数据库使用mysql。

由于redis，

 1、优异的读写性能

我在这里使用了Redis-benchmark这个自带的性能测试工具进行了测试，由于是学习的机子，性能一般所以测试结果

测试命令： redis-benchmark -h 192.168.100.131 -p 6379 -c 100 -n 100000

100个并发连接，100000个请求，检测host为localhost 端口为6379的redis服务器性能 

====== SET ======   

100000 requests completed in 5.15 seconds

19432.57 requests per second

====== GET ======
  100000 requests completed in 5.51 seconds

18162.01 requests per second

每秒钟可以set 或者get差不多2万条。

2 支持数据持久化，支持AOF和RDB两种持久化方式
3 支持主从复制，主机会自动将数据同步到从机，可以进行读写分离。
4 数据结构丰富：string(字符串)、list(链表)、set(集合)、zset(sorted set --有序集合)和hash（哈希类型）

该项目是一个作品投票的项目，是一个互联网项目的一个子项目，我们知道作品投票有个特点就是：作品这个表是经常被查询，数据基本不变，我们就没有必要每次用户进入页面的时候就进行数据库查询，我们只要在redis中直接读取就可以了,下面我通过这个项目进行spring和redis进行整合。

1、项目的POM.xml文件加入所需要的jar包

<dependency>    <groupId>org.apache.commons</groupId>    <artifactId>commons-pool2</artifactId>    <version>2.4.2</version></dependency> <dependency>    <groupId>redis.clients</groupId>    <artifactId>jedis</artifactId>    <version>2.8.0</version></dependency><dependency>        <groupId>org.springframework.data</groupId>        <artifactId>spring-data-redis</artifactId>        <version>1.6.6.RELEASE</version>    </dependency> 

2、为了便于redis配置的管理，我们把一些配置信息单独出来放入redis.properties

redis.hostName=192.168.100.131redis.port=6379redis.timeout=15000redis.usePool=trueredis.maxIdle=6redis.minEvictableIdleTimeMillis=300000redis.numTestsPerEvictionRun=3redis.timeBetweenEvictionRunsMillis=60000

3、需要加入redis-context.xml 配置如下

<beans xmlns="http://www.springframework.org/schema/beans" 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.xsd" default-autowire="byName">  <bean id="jedisPoolConfig" class="redis.clients.jedis.JedisPoolConfig">   <!-- <property name="maxIdle" value="6"></property>   <property name="minEvictableIdleTimeMillis" value="300000"></property>   <property name="numTestsPerEvictionRun" value="3"></property>   <property name="timeBetweenEvictionRunsMillis" value="60000"></property> -->    <property name="maxIdle" value="${redis.maxIdle}"></property>   <property name="minEvictableIdleTimeMillis" value="${redis.minEvictableIdleTimeMillis}"></property>   <property name="numTestsPerEvictionRun" value="${redis.numTestsPerEvictionRun}"></property>   <property name="timeBetweenEvictionRunsMillis" value="${redis.timeBetweenEvictionRunsMillis}"></property> </bean>  <bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" destroy-method="destroy">   <property name="poolConfig" ref="jedisPoolConfig"></property>   <property name="hostName" value="${redis.hostName}"></property>   <property name="port" value="${redis.port}"></property>   <property name="timeout" value="${redis.timeout}"></property>   <property name="usePool" value="${redis.usePool}"></property>  <property name="password" value="${redis.password}"></property>   </bean>  <bean id="jedisTemplate" class="org.springframework.data.redis.core.RedisTemplate">   <property name="connectionFactory" ref="jedisConnectionFactory"></property>   <property name="keySerializer">    <bean class="org.springframework.data.redis.serializer.StringRedisSerializer"/>   </property>   <property name="valueSerializer">    <bean class="org.springframework.data.redis.serializer.JdkSerializationRedisSerializer"/>   </property>  </bean> </beans> 

4、在Spring配置文件中加入读取redis.properties 和redis-context.xml代码

<beanclass="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer"><property name="locations"><list><value>classpath:/config/redis.properties</value> </list></property></bean>

<import resource="classpath*:modules/redis-context.xml" />

这样以上环境就配置好了。下面我们加入代码进行测试

5、这里需要加入监听器，这个监听器的作用是我们启动项目的时候会把数据库中的数据（这些数据基本不变），放入redis中，下次们去拿的数据，可以直接总redis中获得，无需进入数据库中读取。

import java.util.HashMap;import java.util.List;import java.util.Map;import org.apache.log4j.Logger;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.context.ApplicationListener;import org.springframework.context.event.ContextRefreshedEvent;import org.springframework.stereotype.Service;@Servicepublic class StartAddCacheListener implements ApplicationListener<ContextRefreshedEvent> {// 日志private final Logger log = Logger.getLogger(StartAddCacheListener.class);@Autowiredprivate RedisCacheUtil<Object> redisCache;@Autowiredprivate VoteService voteService;@Overridepublic void onApplicationEvent(ContextRefreshedEvent event) {if (event.getApplicationContext().getDisplayName().equals("Root WebApplicationContext")) {System.out.println("-------------缓存数据-------------");List<VoteProject> voteProjectList = voteService.getAllProject();Map<Integer, VoteProject> voteProjectMap = new HashMap<Integer, VoteProject>();int cityListSize = voteProjectList.size();for (int i = 0; i < cityListSize; i++) {voteProjectMap.put(voteProjectList.get(i).getId(), voteProjectList.get(i));}redisCache.setCacheIntegerMap("voteProjectMap", voteProjectMap);}}}

6、将该监听器放入spring配置文件中

<bean id="startAddCacheListener" class="com.eshine.vote.redis.listener.StartAddCacheListener"></bean>

7、新建一个util缓存工具类

import java.util.ArrayList;import java.util.HashSet;import java.util.Iterator;import java.util.List;import java.util.Map;import java.util.Set;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.beans.factory.annotation.Qualifier;import org.springframework.data.redis.core.BoundSetOperations;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.ValueOperations;import org.springframework.stereotype.Service;@Servicepublic class RedisCacheUtil<T> {@Autowired@Qualifier("jedisTemplate")public RedisTemplate redisTemplate;/** * 缓存基本的对象，Integer、String、实体类等 *  * @param key *            缓存的键值 * @param value *            缓存的值 * @return 缓存的对象 */public <T> ValueOperations<String, T> setCacheObject(String key, T value) {ValueOperations<String, T> operation = redisTemplate.opsForValue();operation.set(key, value);return operation;}/** * 获得缓存的基本对象。 *  * @param key *            缓存键值 * @param operation * @return 缓存键值对应的数据 */public <T> T getCacheObject(String key/* ,ValueOperations<String,T> operation */) {ValueOperations<String, T> operation = redisTemplate.opsForValue();return operation.get(key);}/** * 缓存List数据 *  * @param key *            缓存的键值 * @param dataList *            待缓存的List数据 * @return 缓存的对象 */public <T> ListOperations<String, T> setCacheList(String key, List<T> dataList) {ListOperations listOperation = redisTemplate.opsForList();if (null != dataList) {int size = dataList.size();for (int i = 0; i < size; i++) {listOperation.rightPush(key, dataList.get(i));}}return listOperation;}/** * 获得缓存的list对象 *  * @param key *            缓存的键值 * @return 缓存键值对应的数据 */public <T> List<T> getCacheList(String key) {List<T> dataList = new ArrayList<T>();ListOperations<String, T> listOperation = redisTemplate.opsForList();Long size = listOperation.size(key);for (int i = 0; i < size; i++) {dataList.add((T) listOperation.leftPop(key));}return dataList;}/** * 缓存Set *  * @param key *            缓存键值 * @param dataSet *            缓存的数据 * @return 缓存数据的对象 */public <T> BoundSetOperations<String, T> setCacheSet(String key, Set<T> dataSet) {BoundSetOperations<String, T> setOperation = redisTemplate.boundSetOps(key);/* * T[] t = (T[]) dataSet.toArray(); setOperation.add(t); */Iterator<T> it = dataSet.iterator();while (it.hasNext()) {setOperation.add(it.next());}return setOperation;}/** * 获得缓存的set *  * @param key * @param operation * @return */public Set<T> getCacheSet(String key/* * ,BoundSetOperations<String,T> * operation */) {Set<T> dataSet = new HashSet<T>();BoundSetOperations<String, T> operation = redisTemplate.boundSetOps(key);Long size = operation.size();for (int i = 0; i < size; i++) {dataSet.add(operation.pop());}return dataSet;}/** * 缓存Map *  * @param key * @param dataMap * @return */public <T> HashOperations<String, String, T> setCacheMap(String key, Map<String, T> dataMap) {HashOperations hashOperations = redisTemplate.opsForHash();if (null != dataMap) {for (Map.Entry<String, T> entry : dataMap.entrySet()) {/* * System.out.println("Key = " + entry.getKey() + ", Value = " + * entry.getValue()); */hashOperations.put(key, entry.getKey(), entry.getValue());}}return hashOperations;}/** * 获得缓存的Map *  * @param key * @param hashOperation * @return */public <T> Map<String, T> getCacheMap(String key/* * ,HashOperations<String,String * ,T> hashOperation */) {Map<String, T> map = redisTemplate.opsForHash().entries(key);/* Map<String, T> map = hashOperation.entries(key); */return map;}/** * 缓存Map *  * @param key * @param dataMap * @return */public <T> HashOperations<String, Integer, T> setCacheIntegerMap(String key, Map<Integer, T> dataMap) {HashOperations hashOperations = redisTemplate.opsForHash();if (null != dataMap) {for (Map.Entry<Integer, T> entry : dataMap.entrySet()) {/* * System.out.println("Key = " + entry.getKey() + ", Value = " + * entry.getValue()); */hashOperations.put(key, entry.getKey(), entry.getValue());}}return hashOperations;}/** * 获得缓存的Map *  * @param key * @param hashOperation * @return */public <T> Map<Integer, T> getCacheIntegerMap(String key/* * ,HashOperations< * String,String,T> * hashOperation */) {Map<Integer, T> map = redisTemplate.opsForHash().entries(key);/* Map<String, T> map = hashOperation.entries(key); */return map;}}

8、测试类

import java.util.Map;import javax.servlet.http.HttpServletRequest;import javax.servlet.http.HttpServletResponse;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.stereotype.Controller;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.servlet.ModelAndView;@Controller("/RedisTest")@RequestMapping({ "/RedisTest*" })public class RedisTest {@Autowiredprivate RedisCacheUtil<Object> redisCache;@RequestMapping("/testGetCache")public ModelAndView testGetCache(HttpServletRequest req, HttpServletResponse rsp) {ModelAndView mav = new ModelAndView("html/website/index");Map<Integer, VoteProject> voteProjectMap = redisCache.getCacheIntegerMap("voteProjectMap");for (int key : voteProjectMap.keySet()) {System.out.println("key = " + key + ",value=" + voteProjectMap.get(key).getContent());}return mav;}}

以上我们已经将代码以及配置全部搭建好了，现在我数据库中一共有17条数据。如下图所示

下面我启动项目，日志提示将读取17条数据

 9、上面提到，有个测试工具类，我们触发它，查看控制台打印数据

我这里数据库并不多，只有十几条，如果数量达到几百万上千万的时候，我每次重启项目都去查询数据库的一千万条记录，显然不合理，所以，对这个项目整合只是一个开始，后面我会尝试在表中加入大量数据,并且对数据进行持久化，如果有时间和机会会在项目尝试redis的主从复制以及读写分离等等。