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spring結(jié)合redis如何實(shí)現(xiàn)數(shù)據(jù)的緩存

更新時(shí)間：2015年12月01日 15:53:08 作者：WhyWin

這篇文章主要介紹了spring結(jié)合redis如何實(shí)現(xiàn)數(shù)據(jù)的緩存，實(shí)現(xiàn)的目的目的不是加快查詢的速度，而是減少數(shù)據(jù)庫的負(fù)擔(dān)，需要的朋友可以參考下

1、實(shí)現(xiàn)目標(biāo)

　　通過redis緩存數(shù)據(jù)。（目的不是加快查詢的速度，而是減少數(shù)據(jù)庫的負(fù)擔(dān)）　　

2、所需jar包

　　注意：jdies和commons-pool兩個(gè)jar的版本是有對(duì)應(yīng)關(guān)系的，注意引入jar包是要配對(duì)使用，否則將會(huì)報(bào)錯(cuò)。因?yàn)閏ommons-pooljar的目錄根據(jù)版本的變化，目錄結(jié)構(gòu)會(huì)變。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簡介

　　redis是一個(gè)key-value存儲(chǔ)系統(tǒng)。和Memcached類似，它支持存儲(chǔ)的value類型相對(duì)更多，包括string(字符串)、list(鏈表)、set(集合)、zset(sorted set --有序集合)和hash（哈希類型）。這些數(shù)據(jù)類型都支持push/pop、add/remove及取交集并集和差集及更豐富的操作，而且這些操作都是原子性的。在此基礎(chǔ)上，redis支持各種不同方式的排序。與memcached一樣，為了保證效率，數(shù)據(jù)都是緩存在內(nèi)存中。區(qū)別的是redis會(huì)周期性的把更新的數(shù)據(jù)寫入磁盤或者把修改操作寫入追加的記錄文件，并且在此基礎(chǔ)上實(shí)現(xiàn)了master-slave(主從)

3、編碼實(shí)現(xiàn)

1）、配置的文件（properties）

　　將那些經(jīng)常要變化的參數(shù)配置成獨(dú)立的propertis，方便以后的修改redis.properties

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

2)、spring-redis.xml

　　redis的相關(guān)參數(shù)配置設(shè)置。參數(shù)的值來自上面的properties文件

<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>

3）、applicationContext.xml

　　spring的總配置文件，在里面假如一下的代碼

<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" />

4）、web.xml

　　設(shè)置spring的總配置文件在項(xiàng)目啟動(dòng)時(shí)加載

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

5）、redis緩存工具類

ValueOperations　　——基本數(shù)據(jù)類型和實(shí)體類的緩存
ListOperations　　 ——list的緩存
SetOperations　　 ——set的緩存

HashOperations　　Map的緩存

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;
 

 
 /**
  * 緩存基本的對(duì)象，Integer、String、實(shí)體類等
  * @param key 緩存的鍵值
  * @param value 緩存的值
  * @return  緩存的對(duì)象
  */
 public <T> ValueOperations<String,T> setCacheObject(String key,T value)
 {
  
  ValueOperations<String,T> operation = redisTemplate.opsForValue(); 
  operation.set(key,value);
  return operation;
 }
 
 /**
  * 獲得緩存的基本對(duì)象。
  * @param key  緩存鍵值
  * @param operation
  * @return   緩存鍵值對(duì)應(yīng)的數(shù)據(jù)
  */
 public <T> T getCacheObject(String key/*,ValueOperations<String,T> operation*/)
 {
  ValueOperations<String,T> operation = redisTemplate.opsForValue(); 
  return operation.get(key);
 }
 
 /**
  * 緩存List數(shù)據(jù)
  * @param key  緩存的鍵值
  * @param dataList 待緩存的List數(shù)據(jù)
  * @return   緩存的對(duì)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;
 }
 
 /**
  * 獲得緩存的list對(duì)象
  * @param key 緩存的鍵值
  * @return  緩存鍵值對(duì)應(yīng)的數(shù)據(jù)
  */
 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;
 }
 
 /**
  * 緩存Set
  * @param key  緩存鍵值
  * @param dataSet 緩存的數(shù)據(jù)
  * @return   緩存數(shù)據(jù)的對(duì)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;
 }
 
 /**
  * 獲得緩存的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;
 }
 
 /**
  * 緩存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;
 }
 
 /**
  * 獲得緩存的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;
 }
 
 
 
 
 
 
 
 /**
  * 緩存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;
 }
 
 /**
  * 獲得緩存的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;
 }
}

6）、測試

　　這里測試我是在項(xiàng)目啟動(dòng)的時(shí)候到數(shù)據(jù)庫中查找出國家和城市的數(shù)據(jù)，進(jìn)行緩存，之后將數(shù)據(jù)去除。

6.1 項(xiàng)目啟動(dòng)時(shí)緩存數(shù)據(jù)

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;

/*
 * 監(jiān)聽器，用于項(xiàng)目啟動(dòng)的時(shí)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 啟動(dòng)的時(shí)候緩存城市和國家等信息
  if(event.getApplicationContext().getDisplayName().equals("Root WebApplicationContext"))
  {
   System.out.println("\n\n\n_________\n\n緩存數(shù)據(jù) \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 獲取緩存數(shù)據(jù)

 @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));
  }
 }

由于Spring在配置文件中配置的bean默認(rèn)是單例的，所以只需要通過Autowired注入，即可得到原先的緩存類。

以上就是spring+redis實(shí)現(xiàn)數(shù)據(jù)緩存的方法，希望對(duì)大家的學(xué)習(xí)有所幫助。

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