- 浏览: 38644 次
文章分类
最新评论
spring + redis 实现数据的缓存
http://www.cnblogs.com/0201zcr/p/4987561.html
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...
style="background-color: #0098dd; color: white; font-size: 17px; font-weight: bold;"3、redis简介
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
复制代码
redis.hostName=127.0.0.1
redis.port=6379
redis.timeout=15000
redis.usePool=true
redis.maxIdle=6
redis.minEvictableIdleTimeMillis=300000
redis.numTestsPerEvictionRun=3
redis.timeBetweenEvictionRunsMillis=60000
复制代码
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
复制代码
<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>
</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>
复制代码
3)、applicationContext.xml
spring的总配置文件,在里面假如一下的代码
复制代码
<bean class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer">
<property name="systemPropertiesModeName" value="SYSTEM_PROPERTIES_MODE_OVERRIDE" />
<property name="ignoreResourceNotFound" value="true" />
<property name="locations">
<list>
<value>classpath*:/META-INF/config/redis.properties</value>
</list>
</property>
</bean>
<import resource="spring-redis.xml" />
复制代码
4)、web。xml
设置spring的总配置文件在项目启动时加载
<context-param>
<param-name>contextConfigLocation</param-name>
<param-value>classpath*:/META-INF/applicationContext.xml</param-value><!-- -->
</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
复制代码
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
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.context.support.ClassPathXmlApplicationContext;
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.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.stereotype.Service;
@Service
public 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;
}
}
复制代码
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
复制代码
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);
}
}
}
复制代码
6.2 获取缓存数据
复制代码
@Autowired
private RedisCacheUtil<User> redisCache;
@RequestMapping("testGetCache")
public void testGetCache()
{
/*Map<String,Country> countryMap = redisCacheUtil1.getCacheMap("country");
Map<String,City> cityMap = redisCacheUtil.getCacheMap("city");*/
Map<Integer,Country> countryMap = redisCacheUtil1.getCacheIntegerMap("countryMap");
Map<Integer,City> cityMap = redisCacheUtil.getCacheIntegerMap("cityMap");
for(int key : countryMap.keySet())
{
System.out.println("key = " + key + ",value=" + countryMap.get(key));
}
System.out.println("------------city");
for(int key : cityMap.keySet())
{
System.out.println("key = " + key + ",value=" + cityMap.get(key));
}
}
复制代码
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。
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...
style="background-color: #0098dd; color: white; font-size: 17px; font-weight: bold;"3、redis简介
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
复制代码
redis.hostName=127.0.0.1
redis.port=6379
redis.timeout=15000
redis.usePool=true
redis.maxIdle=6
redis.minEvictableIdleTimeMillis=300000
redis.numTestsPerEvictionRun=3
redis.timeBetweenEvictionRunsMillis=60000
复制代码
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
复制代码
<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>
</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>
复制代码
3)、applicationContext.xml
spring的总配置文件,在里面假如一下的代码
复制代码
<bean class="org.springframework.beans.factory.config.PropertyPlaceholderConfigurer">
<property name="systemPropertiesModeName" value="SYSTEM_PROPERTIES_MODE_OVERRIDE" />
<property name="ignoreResourceNotFound" value="true" />
<property name="locations">
<list>
<value>classpath*:/META-INF/config/redis.properties</value>
</list>
</property>
</bean>
<import resource="spring-redis.xml" />
复制代码
4)、web。xml
设置spring的总配置文件在项目启动时加载
<context-param>
<param-name>contextConfigLocation</param-name>
<param-value>classpath*:/META-INF/applicationContext.xml</param-value><!-- -->
</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
复制代码
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
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.context.support.ClassPathXmlApplicationContext;
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.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.stereotype.Service;
@Service
public 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;
}
}
复制代码
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
复制代码
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);
}
}
}
复制代码
6.2 获取缓存数据
复制代码
@Autowired
private RedisCacheUtil<User> redisCache;
@RequestMapping("testGetCache")
public void testGetCache()
{
/*Map<String,Country> countryMap = redisCacheUtil1.getCacheMap("country");
Map<String,City> cityMap = redisCacheUtil.getCacheMap("city");*/
Map<Integer,Country> countryMap = redisCacheUtil1.getCacheIntegerMap("countryMap");
Map<Integer,City> cityMap = redisCacheUtil.getCacheIntegerMap("cityMap");
for(int key : countryMap.keySet())
{
System.out.println("key = " + key + ",value=" + countryMap.get(key));
}
System.out.println("------------city");
for(int key : cityMap.keySet())
{
System.out.println("key = " + key + ",value=" + cityMap.get(key));
}
}
复制代码
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。
相关推荐
spring + ehcache + redis两级缓存
spring+mybatis+redis,mybatis作为缓存,仅仅是入门的配置,我找了好多的教程才最终配置好,资源绝对没问题。请放心下载
mybatis二级缓存 + reads做第三级缓存
SpringMVC+Redis+MyBatis项目,主要实现Redis注释缓存
这是Maven项目,Spring集成Redis来实现注解缓存,代码配置方面都有详细代码,并在相关配置文件里添加了相关参考文档地址,都是博主自己一手敲出来的,如果觉得资源还可以,请五星好评哦,亲(づ ̄3 ̄)づ╭❤~
完整的spring +springmvc+hibernate+shiro项目实例,详细的shiro配置介绍,通过redis管理用户session缓存。。。。。。。。
spring+redis作为缓存,带springTest配置,导入resource下的数据库文件,配置数据库地址和redis地址,点击test文件夹下的测试方法即可运行,也可完善页面运行。
存储过程等),用Redis做中间缓存,缓存数据 实现异步处理,定时任务,整合Quartz Job以及Spring Task 邮件管理功能, 整合spring-boot-starter-mail发送邮件等, 数据源:druid 用户管理,菜单管理,角色管理,代码...
Spring+Redis集成,实现缓存存储。
系统缓存管理 将redis的操作可视化,提供对redis的基本操作 Sql监控 采用 druid 监控数据库访问性能 技术栈 基础框架:Spring Boot 2.1.0.RELEASE 持久层框架:Spring boot Jpa 安全框架:Spring Security 缓存框架...
springboot+mybatis+druid+redis实现数据库读写分离和缓存
springMVC+spring+mybatis+redis整合的maven demo,redis作为二级缓存
SpringCache+Redis实现高可用缓存解决方案.docx
java Web现代化开发:Spring Boot + Mybatis + Redis二级缓存
Oracle关系型数据库以及非关系型数据库(Redis),Oracle 性能调优(PL/SQL语言,SQL查询优化,存储过程等),用Redis做中间缓存,缓存数据 实现异步处理,定时任务,整合Quartz Job以及Spring Task 邮件管理功能...
spring框架下整合mybatis和缓存redis
内容概要:面试自我概要介绍+java基础八股文+jvm详解+锁分类+线程池简要+map数据结构+缓存简要+redis简要+数据库(mysql详解)+spring概要+网络高频+linux简要 适用人群:适用java后端找工作的人群,工作经验三年内...
spring-session spring session+redis实现分布式缓存
使用maven简单搭建Spring mvc + redis缓存 个人实验成功