spring + redis 实现数据的缓存

Posted 明志健致远

tags:

篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了spring + redis 实现数据的缓存相关的知识,希望对你有一定的参考价值。

1、实现目标

通过redis缓存数据。(目的不是加快查询的速度,而是减少数据库的负担)

2、所需Jar包

注意:jdies和commons-pool两个jar的版本是有对应关系的,注意引入jar包是要配对使用,否则将会报错。因为commons-pooljar的目录根据版本的变化,目录结构会变。前面的版本是org.apache.pool,而后面的版本是org.apache.pool2...

3、Redis介绍

redis是一个key-value存储系统。和Memcached类似,它支持存储的value类型相对更多,包括string(字符串)、list(链表)、set(集合)、zset(sorted set --有序集合)和hash(哈希类型)。这些数据类型都支持push/pop、add/remove及取交集并集和差集及更丰富的操作,而且这些操作都是原子性的。在此基础上,redis支持各种不同方式的排序。与memcached一样,为了保证效率,数据都是缓存在内存中。区别的是redis会周期性的把更新的数据写入磁盘或者把修改操作写入追加的记录文件,并且在此基础上实现了master-slave(主从)

4、编码实现

1)、配置的文件(properties)

  将那些经常要变化的参数配置成独立的propertis,方便以后的修改

  redis.properties

1 redis.hostName=127.0.0.1
2 redis.port=6379
3 redis.timeout=15000
4 redis.usePool=true
5 
6 redis.maxIdle=6
7 redis.minEvictableIdleTimeMillis=300000
8 redis.numTestsPerEvictionRun=3
9 redis.timeBetweenEvictionRunsMillis=60000

 

2)、spring-redis.xml

redis的相关参数配置设置。参数的值来自上面的properties文件

 1 <beans xmlns="http://www.springframework.org/schema/beans"  
 2 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" 
 3 xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd" default-autowire="byName">  
 4     <bean id="jedisPoolConfig" class="redis.clients.jedis.JedisPoolConfig">  
 5         <!-- <property name="maxIdle" value="6"></property>  
 6         <property name="minEvictableIdleTimeMillis" value="300000"></property>  
 7         <property name="numTestsPerEvictionRun" value="3"></property>  
 8         <property name="timeBetweenEvictionRunsMillis" value="60000"></property>   -->
 9  
10         <property name="maxIdle" value="${redis.maxIdle}"></property>  
11         <property name="minEvictableIdleTimeMillis" value="${redis.minEvictableIdleTimeMillis}"></property>  
12         <property name="numTestsPerEvictionRun" value="${redis.numTestsPerEvictionRun}"></property>  
13         <property name="timeBetweenEvictionRunsMillis" value="${redis.timeBetweenEvictionRunsMillis}"></property>
14     </bean>  
15     <bean id="jedisConnectionFactory" class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory" destroy-method="destroy">  
16         <property name="poolConfig" ref="jedisPoolConfig"></property>  
17         <property name="hostName" value="${redis.hostName}"></property>  
18         <property name="port" value="${redis.port}"></property>  
19         <property name="timeout" value="${redis.timeout}"></property>  
20         <property name="usePool" value="${redis.usePool}"></property>  
21     </bean>  
22     <bean id="jedisTemplate" class="org.springframework.data.redis.core.RedisTemplate">  
23         <property name="connectionFactory" ref="jedisConnectionFactory"></property>  
24         <property name="keySerializer">  
25             <bean class="org.springframework.data.redis.serializer.StringRedisSerializer"/>  
26         </property>  
27         <property name="valueSerializer">  
28             <bean class="org.springframework.data.redis.serializer.JdkSerializationRedisSerializer"/>  
29         </property>  
30     </bean>  
31 </beans>

 

3)、applicationContext.xml

spring的总配置文件,在里面假如一下的代码

 1 <bean class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer">
 2         <property name="systemPropertiesModeName" value="SYSTEM_PROPERTIES_MODE_OVERRIDE" />
 3         <property name="ignoreResourceNotFound" value="true" />
 4         <property name="locations">
 5             <list>
 6  
 7                 <value>classpath*:/META-INF/config/redis.properties</value>
 8             </list>
 9         </property>
10     </bean>
11  
12 <import resource="spring-redis.xml" />

 

4)、web.xml

设置spring的总配置文件在项目启动时加载

1 <context-param>
2     <param-name>contextConfigLocation</param-name>
3     <param-value>classpath*:/META-INF/applicationContext.xml</param-value><!--  -->
4 </context-param>

 

5)、redis缓存工具类

ValueOperations  ——基本数据类型和实体类的缓存
ListOperations     ——list的缓存
SetOperations    ——set的缓存

HashOperations  Map的缓存

 
  1 import java.io.Serializable;
  2 import java.util.ArrayList;
  3 import java.util.HashMap;
  4 import java.util.HashSet;
  5 import java.util.Iterator;
  6 import java.util.List;
  7 import java.util.Map;
  8 import java.util.Set;
  9  
 10 import org.springframework.beans.factory.annotation.Autowired;
 11 import org.springframework.beans.factory.annotation.Qualifier;
 12 import org.springframework.context.support.ClassPathXmlApplicationContext;
 13 import org.springframework.data.redis.core.BoundSetOperations;
 14 import org.springframework.data.redis.core.HashOperations;
 15 import org.springframework.data.redis.core.ListOperations;
 16 import org.springframework.data.redis.core.RedisTemplate;
 17 import org.springframework.data.redis.core.SetOperations;
 18 import org.springframework.data.redis.core.ValueOperations;
 19 import org.springframework.stereotype.Service;
 20  
 21 @Service
 22 public class RedisCacheUtil<T>
 23 {
 24  
 25     @Autowired @Qualifier("jedisTemplate")
 26     public RedisTemplate redisTemplate;
 27  
 28     /**
 29      * 缓存基本的对象,Integer、String、实体类等
 30      * @param key    缓存的键值
 31      * @param value    缓存的值
 32      * @return        缓存的对象
 33      */
 34     public <T> ValueOperations<String,T> setCacheObject(String key,T value)
 35     {
 36  
 37         ValueOperations<String,T> operation = redisTemplate.opsForValue(); 
 38         operation.set(key,value);
 39         return operation;
 40     }
 41  
 42     /**
 43      * 获得缓存的基本对象。
 44      * @param key        缓存键值
 45      * @param operation
 46      * @return            缓存键值对应的数据
 47      */
 48     public <T> T getCacheObject(String key/*,ValueOperations<String,T> operation*/)
 49     {
 50         ValueOperations<String,T> operation = redisTemplate.opsForValue(); 
 51         return operation.get(key);
 52     }
 53  
 54     /**
 55      * 缓存List数据
 56      * @param key        缓存的键值
 57      * @param dataList    待缓存的List数据
 58      * @return            缓存的对象
 59      */
 60     public <T> ListOperations<String, T> setCacheList(String key,List<T> dataList)
 61     {
 62         ListOperations listOperation = redisTemplate.opsForList();
 63         if(null != dataList)
 64         {
 65             int size = dataList.size();
 66             for(int i = 0; i < size ; i ++)
 67             {
 68  
 69                 listOperation.rightPush(key,dataList.get(i));
 70             }
 71         }
 72  
 73         return listOperation;
 74     }
 75  
 76     /**
 77      * 获得缓存的list对象
 78      * @param key    缓存的键值
 79      * @return        缓存键值对应的数据
 80      */
 81     public <T> List<T> getCacheList(String key)
 82     {
 83         List<T> dataList = new ArrayList<T>();
 84         ListOperations<String,T> listOperation = redisTemplate.opsForList();
 85         Long size = listOperation.size(key);
 86  
 87         for(int i = 0 ; i < size ; i ++)
 88         {
 89             dataList.add((T) listOperation.leftPop(key));
 90         }
 91  
 92         return dataList;
 93     }
 94  
 95     /**
 96      * 缓存Set
 97      * @param key        缓存键值
 98      * @param dataSet    缓存的数据
 99      * @return            缓存数据的对象
100      */
101     public <T> BoundSetOperations<String,T> setCacheSet(String key,Set<T> dataSet)
102     {
103         BoundSetOperations<String,T> setOperation = redisTemplate.boundSetOps(key);    
104         /*T[] t = (T[]) dataSet.toArray();
105              setOperation.add(t);*/
106  
107         Iterator<T> it = dataSet.iterator();
108         while(it.hasNext())
109         {
110             setOperation.add(it.next());
111         }
112  
113         return setOperation;
114     }
115  
116     /**
117      * 获得缓存的set
118      * @param key
119      * @param operation
120      * @return
121      */
122     public Set<T> getCacheSet(String key/*,BoundSetOperations<String,T> operation*/)
123     {
124         Set<T> dataSet = new HashSet<T>();
125         BoundSetOperations<String,T> operation = redisTemplate.boundSetOps(key);    
126  
127         Long size = operation.size();
128         for(int i = 0 ; i < size ; i++)
129         {
130             dataSet.add(operation.pop());
131         }
132         return dataSet;
133     }
134  
135     /**
136      * 缓存Map
137      * @param key
138      * @param dataMap
139      * @return
140      */
141     public <T> HashOperations<String,String,T> setCacheMap(String key,Map<String,T> dataMap)
142     {
143  
144         HashOperations hashOperations = redisTemplate.opsForHash();
145         if(null != dataMap)
146         {
147  
148             for (Map.Entry<String, T> entry : dataMap.entrySet()) {  
149  
150                 /*System.out.println("Key = " + entry.getKey() + ", Value = " + entry.getValue());  */
151                 hashOperations.put(key,entry.getKey(),entry.getValue());
152             } 
153  
154         }
155  
156         return hashOperations;
157     }
158  
159     /**
160      * 获得缓存的Map
161      * @param key
162      * @param hashOperation
163      * @return
164      */
165     public <T> Map<String,T> getCacheMap(String key/*,HashOperations<String,String,T> hashOperation*/)
166     {
167         Map<String, T> map = redisTemplate.opsForHash().entries(key);
168         /*Map<String, T> map = hashOperation.entries(key);*/
169         return map;
170     }
171  
172     /**
173      * 缓存Map
174      * @param key
175      * @param dataMap
176      * @return
177      */
178     public <T> HashOperations<String,Integer,T> setCacheIntegerMap(String key,Map<Integer,T> dataMap)
179     {
180         HashOperations hashOperations = redisTemplate.opsForHash();
181         if(null != dataMap)
182         {
183  
184             for (Map.Entry<Integer, T> entry : dataMap.entrySet()) {  
185  
186                 /*System.out.println("Key = " + entry.getKey() + ", Value = " + entry.getValue());  */
187                 hashOperations.put(key,entry.getKey(),entry.getValue());
188             } 
189  
190         }
191  
192         return hashOperations;
193     }
194  
195     /**
196      * 获得缓存的Map
197      * @param key
198      * @param hashOperation
199      * @return
200      */
201     public <T> Map<Integer,T> getCacheIntegerMap(String key/*,HashOperations<String,String,T> hashOperation*/)
202     {
203         Map<Integer, T> map = redisTemplate.opsForHash().entries(key);
204         /*Map<String, T> map = hashOperation.entries(key);*/
205         return map;
206     }
207 }

 

6)、测试

这里测试我是在项目启动的时候到数据库中查找出国家和城市的数据,进行缓存,之后将数据去出

6.1  项目启动时缓存数据

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;
 
import com.test.model.City;
import com.test.model.Country;
import com.zcr.test.User;
 
/*
 * 监听器,用于项目启动的时候初始化信息
 */
@Service
public class StartAddCacheListener implements ApplicationListener<ContextRefreshedEvent>
{
    //日志
    private final Logger log= Logger.getLogger(StartAddCacheListener.class);
 
    @Autowired
    private RedisCacheUtil<Object> redisCache;
 
    @Autowired
    private BrandStoreService brandStoreService;
 
    @Override
    public void onApplicationEvent(ContextRefreshedEvent  event) 
    {
        //spring 启动的时候缓存城市和国家等信息
        if(event.getApplicationContext().getDisplayName().equals("Root WebApplicationContext"))
        {
            System.out.println("\\n\\n\\n_________\\n\\n缓存数据 \\n\\n ________\\n\\n\\n\\n");
            List<City> cityList = brandStoreService.selectAllCityMessage();
            List<Country> countryList = brandStoreService.selectAllCountryMessage();
 
            Map<Integer,City> cityMap = new HashMap<Integer,City>();
 
            Map<Integer,Country> countryMap = new HashMap<Integer, Country>();
 
            int cityListSize = cityList.size();
            int countryListSize = countryList.size();
 
            for(int i = 0 ; i < cityListSize ; i ++ )
            {
                cityMap.put(cityList.get(i).getCity_id(), cityList.get(i));
            }
 
            for(int i = 0 ; i < countryListSize ; i ++ )
            {
                countryMap.put(countryList.get(i).getCountry_id(), countryList.get(i));
            }
 
            redisCache.setCacheIntegerMap("cityMap", cityMap);
            redisCache.setCacheIntegerMap("countryMap", countryMap);
        }
    }
 
}

 

6.2  获取缓存数据

 1 @Autowired
 2     private RedisCacheUtil<User> redisCache;
 3  
 4     @RequestMapping("testGetCache")
 5     public void testGetCache()
 6     {
 7         /*Map<String,Country> countryMap = redisCacheUtil1.getCacheMap("country");
 8         Map<String,City> cityMap = redisCacheUtil.getCacheMap("city");*/
 9         Map<Integer,Country> countryMap = redisCacheUtil1.getCacheIntegerMap("countryMap");
10         Map<Integer,City> cityMap = redisCacheUtil.getCacheIntegerMap("cityMap");
11  
12         for(int key : countryMap.keySet())
13         {
14             System.out.println("key = " + key + ",value=" + countryMap.get(key));
15         }
16  
17         System.out.println("------------city");
18         for(int key : cityMap.keySet())
19         {
20             System.out.println("key = " + key + ",value=" + cityMap.get(key));
21         }
22     }

由于Spring在配置文件中配置的bean默认是单例的,所以只需要通过Autowired注入,即可得到原先的缓存类。

 

原文:http://www.cnblogs.com/0201zcr/p/4987561.html

 

以上是关于spring + redis 实现数据的缓存的主要内容,如果未能解决你的问题,请参考以下文章

spring + redis 实现数据的缓存

spring + redis 实现数据的缓存

Spring Boot 整合Redis 实现缓存

Spring Boot集成Redis实现缓存

Spring Boot集成Redis实现缓存

SpringBoot 结合 Spring Cache 操作 Redis 实现数据缓存