spring + redis 实现数据的缓存
2017-05-23 21:25
344 查看
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
内容来自用户分享和网络整理，不保证内容的准确性，如有侵权内容，可联系管理员处理 
相关文章推荐
- spring + redis 实现数据的缓存
- spring结合redis如何实现数据的缓存
- spring结合redis如何实现数据的缓存
- spring + redis 实现数据的缓存
- spring整合redis实现数据缓存的实例代码
- redis整合spring实现对数据的缓存
- springboot+redis实现缓存数据
- spring + redis 实现数据的缓存
- spring + redis 实现数据的缓存
- spring + redis 实现数据的缓存
- spring结合redis如何实现数据的缓存
- spring+springmvc+mybatis+redis 实现两重数据缓存
- spring结合redis如何实现数据的缓存
- spring + redis 实现数据的缓存
- spring + redis 实现数据的缓存
- 11、Spring技术栈-整合Redis，通过Redis的Master-Slave实现缓存数据读写分离
- 10、Spring技术栈-整合Redis，使用RedisTemplate实现数据缓存实战
- spring + redis 实现数据的缓存
- spring + redis 实现数据的缓存
- spring + redis 实现数据的缓存