redis整合spring mybatis --缓存方案

上一篇总结了redis sentinel（哨兵方案）的配置流程，本篇就redis整合ssm框架进行说明。目前，大多数公司用redis主要做缓存用，对于那些不常变动的数据来说，我们将其缓存在redis中，可以大大减少数据库的压力。

一、Spring集成redis

1.在resource目录下创建spring-redis.xml文件，内容如下：

<?xml version="1.0" encoding="UTF-8"?><beans xmlns="http://www.springframework.org/schema/beans"    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context"    xmlns:p="http://www.springframework.org/schema/p"    xsi:schemaLocation="http://www.springframework.org/schema/aop http://www.springframework.org/schema/aop/spring-aop-4.1.xsd        http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-4.1.xsd        http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-4.1.xsd">    <bean id="jedisPoolConfig" class="redis.clients.jedis.JedisPoolConfig">        <property name="maxIdle" value="2000" />        <property name="maxTotal" value="20000" />        <property name="minEvictableIdleTimeMillis" value="300000"></property>        <property name="numTestsPerEvictionRun" value="3"></property>        <property name="timeBetweenEvictionRunsMillis" value="60000"></property>        <property name="maxWaitMillis" value="20000" />        <property name="testOnBorrow" value="false" />    </bean>    <bean id="sentinelConfig"        class="org.springframework.data.redis.connection.RedisSentinelConfiguration">        <property name="master">            <bean class="org.springframework.data.redis.connection.RedisNode">                <property name="name" value="mymaster"></property>            </bean>        </property>        <property name="sentinels">            <set>                <bean class="org.springframework.data.redis.connection.RedisNode">                    <constructor-arg name="host" value="192.168.12.90" />                    <constructor-arg name="port" value="7505" />                </bean>                <bean class="org.springframework.data.redis.connection.RedisNode">                    <constructor-arg name="host" value="192.168.12.90" />                    <constructor-arg name="port" value="7506" />                </bean>            </set>        </property>    </bean>    <!-- 在此将sentinel配置集成到redis连接池中 -->    <bean id="jedisConnectionFactory"        class="org.springframework.data.redis.connection.jedis.JedisConnectionFactory">        <property name="timeout" value="20000"></property>        <property name="poolConfig" ref="jedisPoolConfig"></property>        <constructor-arg name="sentinelConfig" ref="sentinelConfig"></constructor-arg>    </bean>    <bean id="stringRedisTemplate" class="org.springframework.data.redis.core.StringRedisTemplate">        <property name="connectionFactory" ref="jedisConnectionFactory" />    </bean></beans>
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在上述配置中，我们用jedis 池化管理方案，将sentinel纳入配置中去，这样就不用代码中用JedisSentinelPool了，直接用JedisPool就ok了。别忘了，将此文件加入web.xml中：

<context-param>        <param-name>contextConfigLocation</param-name>        <param-value>classpath:spring-mybatis.xml,classpath:spring-redis.xml</param-value></context-param>
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2.测试

新建测试类，内容如下：

package com.dg;import java.util.Collection;import java.util.List;import java.util.Map;import java.util.Set;import javax.annotation.Resource;import org.junit.Test;import org.junit.runner.RunWith;import org.springframework.data.redis.connection.RedisSentinelConnection;import org.springframework.data.redis.connection.RedisServer;import org.springframework.data.redis.core.StringRedisTemplate;import org.springframework.test.context.ContextConfiguration;import org.springframework.test.context.junit4.SpringJUnit4ClassRunner;import com.alibaba.fastjson.JSONObject;import com.dg.bean.User;@RunWith(SpringJUnit4ClassRunner.class)@ContextConfiguration(locations = { "classpath:spring-redis.xml" })public class SpringRedis {    @Resource(name = "stringRedisTemplate")    private StringRedisTemplate stringRedisTemplate;    /**     * redis 读写测试     */    @Test    public void testSpringRedis() {        try {            // ApplicationContext context = new            // ClassPathXmlApplicationContext("spring-redis.xml");            // StringRedisTemplate stringRedisTemplate =            // context.getBean("stringRedisTemplate",            // StringRedisTemplate.class);            // String读写            stringRedisTemplate.delete("myStr");            stringRedisTemplate.opsForValue().set("myStr", "http://yjmyzz.cnblogs.com/");            System.out.println(stringRedisTemplate.opsForValue().get("myStr"));            System.out.println("---------------");            // List读写            stringRedisTemplate.delete("myList");            stringRedisTemplate.opsForList().rightPush("myList", "A");            stringRedisTemplate.opsForList().rightPush("myList", "B");            stringRedisTemplate.opsForList().leftPush("myList", "0");            List<String> listCache = stringRedisTemplate.opsForList().range("myList", 0, -1);            for (String s : listCache) {                System.out.println(s);            }            System.out.println("---------------");            // Set读写            stringRedisTemplate.delete("mySet");            stringRedisTemplate.opsForSet().add("mySet", "A");            stringRedisTemplate.opsForSet().add("mySet", "B");            stringRedisTemplate.opsForSet().add("mySet", "C");            Set<String> setCache = stringRedisTemplate.opsForSet().members("mySet");            for (String s : setCache) {                System.out.println(s);            }            System.out.println("---------------");            // Hash读写            stringRedisTemplate.delete("myHash");            stringRedisTemplate.opsForHash().put("myHash", "PEK", "北京");            stringRedisTemplate.opsForHash().put("myHash", "SHA", "上海虹桥");            stringRedisTemplate.opsForHash().put("myHash", "PVG", "浦东");            Map<Object, Object> hashCache = stringRedisTemplate.opsForHash().entries("myHash");            for (Map.Entry<Object, Object> entry : hashCache.entrySet()) {                System.out.println(entry.getKey() + " - " + entry.getValue());            }            System.out.println("---------------");        } catch (Exception e) {            e.printStackTrace();        }    }    /**     * redis 得到所有的master and slave 信息     */    @Test    public void testGetAllMasterAndSlave() {        RedisSentinelConnection conn = stringRedisTemplate.getConnectionFactory().getSentinelConnection();        for (RedisServer master : conn.masters()) {            System.out.println("master => " + master);// 打印master信息            Collection<RedisServer> slaves = conn.slaves(master);            // 打印该master下的所有slave信息            for (RedisServer slave : slaves) {                System.out.println("slaves of " + master + " => " + slave);            }            System.out.println("--------------");        }    }    /*     * 测试redis 缓存object 和 list 类型数据(方案：用json将object和list序列化)     */    @Test    public void testRedisCacheObjectAndList() {        User user1 = new User("zhangsan", "123456", "[e-mail]", "15824812342", 'M', 22);//      // fastJson 序列化//      String jsonStr = JSONObject.toJSONString(user1);//      System.out.println(">>>>>>>>>>>>>>>>" + jsonStr);//      // fastJson 反序列化//      user1 = JSONObject.parseObject(jsonStr, User.class);//      System.out.println(">>>>>>>>>>>>>>>>>>" + user1);        stringRedisTemplate.delete("user1");        // 将object 用 json 序列化后保存redis        stringRedisTemplate.opsForValue().set("user1", JSONObject.toJSONString(user1));        user1 = JSONObject.parseObject(stringRedisTemplate.opsForValue().get("user1"), User.class);        System.out.println("-----------------------" + user1);    }}    /**测试redis客户端*/    @Test    public void testRedis(){        Jedis jedis = new Jedis("192.168.12.90", 6379);        jedis.set("name", "mrdg");        jedis.set("age", "24");        System.out.println("name:"+jedis.get("name"));        System.out.println("age:"+jedis.get("age"));        System.out.println("tel:"+jedis.get("Tel"));        System.out.println("no:"+jedis.get("No"));    }    /**测试redis集群方案*/    @Test    public void testCluster(){        Set<HostAndPort> jedisClusterNodes = new HashSet<HostAndPort>();        //Jedis Cluster will attempt to discover cluster nodes automatically        jedisClusterNodes.add(new HostAndPort("192.168.12.90", 7001));        JedisCluster jc = new JedisCluster(jedisClusterNodes);        jc.set("foo", "bar");        String value = jc.get("foo");        System.out.println(value);        try {            jc.close();        } catch (Exception e) {            e.printStackTrace();        }    }
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上面的测试类，cluster方案集群环境为(详见http://blog.csdn.net/donggang1992/article/details/50981954):

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sentinel方案环境为（详见http://blog.csdn.net/donggang1992/article/details/50981341）：

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二、mybatis集成redis进行缓存配置

1.mybatis开启缓存支持

在spring-mabatis.xml中添加下列内容：

<!-- spring和MyBatis完美整合，不需要mybatis的配置映射文件 -->    <bean id="sqlSessionFactory" class="org.mybatis.spring.SqlSessionFactoryBean">        <property name="dataSource" ref="dataSource" />        <!-- 自动扫描mapping.xml文件 -->        <property name="mapperLocations" value="classpath:com/dg/mapping/*.xml"></property>        <!-- 开启缓存支持 -->        <property name="configurationProperties">            <props>                <prop key="cacheEnabled">true</prop>                <!-- 查询时，关闭关联对象即时加载以提高性能 -->                <prop key="lazyLoadingEnabled">false</prop>                <!-- 设置关联对象加载的形态，此处为按需加载字段(加载字段由SQL指定)，不会加载关联表的所有字段，以提高性能 -->                <prop key="aggressiveLazyLoading">true</prop>                <!-- 对于未知的SQL查询，允许返回不同的结果集以达到通用的效果 -->                <prop key="multipleResultSetsEnabled">true</prop>                <!-- 允许使用列标签代替列名 -->                <prop key="useColumnLabel">true</prop>                <!-- 允许使用自定义的主键值(比如由程序生成的UUID 32位编码作为键值)，数据表的PK生成策略将被覆盖 -->                <prop key="useGeneratedKeys">true</prop>                <!-- 给予被嵌套的resultMap以字段-属性的映射支持 -->                <prop key="autoMappingBehavior">FULL</prop>                <!-- 对于批量更新操作缓存SQL以提高性能 -->                <prop key="defaultExecutorType">BATCH</prop>                <!-- 数据库超过25000秒仍未响应则超时 -->                <prop key="defaultStatementTimeout">25000</prop>            </props>        </property>    </bean>
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2.新建cache包，并创建RedisCache类

RedisCache类的内容为：

package com.dg.cache;import java.util.Set;import java.util.concurrent.locks.ReadWriteLock;import java.util.concurrent.locks.ReentrantReadWriteLock;import org.apache.commons.codec.digest.DigestUtils;import org.apache.ibatis.cache.Cache;import org.slf4j.Logger;import org.slf4j.LoggerFactory;import org.springframework.context.ApplicationContext;import org.springframework.context.support.ClassPathXmlApplicationContext;import com.dg.util.SerializeUtil;import redis.clients.jedis.Jedis;import redis.clients.jedis.JedisPool;import redis.clients.jedis.JedisPoolConfig;/* * 使用第三方缓存服务器，处理二级缓存 */public class RedisCache implements Cache {    private static Logger logger = LoggerFactory.getLogger(RedisCache.class);    /** The ReadWriteLock. */    private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock();    private String id;    private JedisPool jedisPool;    private static final int DB_INDEX = 1;    private final String COMMON_CACHE_KEY = "COM:";    private static final String UTF8 = "utf-8";    private ApplicationContext context;    /**     * 按照一定规则标识key     */    private String getKey(Object key) {        StringBuilder accum = new StringBuilder();        accum.append(COMMON_CACHE_KEY);        accum.append(this.id).append(":");        accum.append(DigestUtils.md5Hex(String.valueOf(key)));        return accum.toString();    }    /**     * redis key规则前缀     */    private String getKeys() {        return COMMON_CACHE_KEY + this.id + ":*";    }    public RedisCache() {    }    public RedisCache(final String id) {        if (id == null) {            throw new IllegalArgumentException("必须传入ID");        }        context = new ClassPathXmlApplicationContext("spring-redis.xml");        JedisPoolConfig jedisPoolConfig = (JedisPoolConfig) context.getBean("jedisPoolConfig");        jedisPool = new JedisPool(jedisPoolConfig, "192.168.12.90", 7504);        logger.debug(">>>>>>>>>>>>>>>>>>>>>MybatisRedisCache:id=" + id);        this.id = id;    }    @Override    public String getId() {        return this.id;    }    @Override    public int getSize() {        Jedis jedis = null;        int result = 0;        boolean borrowOrOprSuccess = true;        try {            jedis = jedisPool.getResource();            jedis.select(DB_INDEX);            Set<byte[]> keys = jedis.keys(getKeys().getBytes(UTF8));            if (null != keys && !keys.isEmpty()) {                result = keys.size();            }            logger.debug(this.id + "---->>>>总缓存数:" + result);        } catch (Exception e) {            borrowOrOprSuccess = false;            if (jedis != null)                jedisPool.returnBrokenResource(jedis);        } finally {            if (borrowOrOprSuccess)                jedisPool.returnResource(jedis);        }        return result;    }    @Override    public void putObject(Object key, Object value) {        Jedis jedis = null;        boolean borrowOrOprSuccess = true;        try {            jedis = jedisPool.getResource();            jedis.select(DB_INDEX);            byte[] keys = getKey(key).getBytes(UTF8);            jedis.set(keys, SerializeUtil.serialize(value));            logger.debug("添加缓存--------" + this.id);            // getSize();        } catch (Exception e) {            borrowOrOprSuccess = false;            if (jedis != null)                jedisPool.returnBrokenResource(jedis);        } finally {            if (borrowOrOprSuccess)                jedisPool.returnResource(jedis);        }    }    @Override    public Object getObject(Object key) {        Jedis jedis = null;        Object value = null;        boolean borrowOrOprSuccess = true;        try {            jedis = jedisPool.getResource();            jedis.select(DB_INDEX);            value = SerializeUtil.unserialize(jedis.get(getKey(key).getBytes(UTF8)));            logger.debug("从缓存中获取-----" + this.id);            // getSize();        } catch (Exception e) {            borrowOrOprSuccess = false;            if (jedis != null)                jedisPool.returnBrokenResource(jedis);        } finally {            if (borrowOrOprSuccess)                jedisPool.returnResource(jedis);        }        return value;    }    @Override    public Object removeObject(Object key) {        Jedis jedis = null;        Object value = null;        boolean borrowOrOprSuccess = true;        try {            jedis = jedisPool.getResource();            jedis.select(DB_INDEX);            value = jedis.del(getKey(key).getBytes(UTF8));            logger.debug("LRU算法从缓存中移除-----" + this.id);            // getSize();        } catch (Exception e) {            borrowOrOprSuccess = false;            if (jedis != null)                jedisPool.returnBrokenResource(jedis);        } finally {            if (borrowOrOprSuccess)                jedisPool.returnResource(jedis);        }        return value;    }    @Override    public void clear() {        Jedis jedis = null;        boolean borrowOrOprSuccess = true;        try {            jedis = jedisPool.getResource();            jedis.select(DB_INDEX);            // 如果有删除操作，会影响到整个表中的数据，因此要清空一个mapper的缓存（一个mapper的不同数据操作对应不同的key）            Set<byte[]> keys = jedis.keys(getKeys().getBytes(UTF8));            logger.debug("出现CUD操作，清空对应Mapper缓存======>" + keys.size());            for (byte[] key : keys) {                jedis.del(key);            }            // 下面是网上流传的方法，极大的降低系统性能，没起到加入缓存应有的作用，这是不可取的。            // jedis.flushDB();            // jedis.flushAll();        } catch (Exception e) {            borrowOrOprSuccess = false;            if (jedis != null)                jedisPool.returnBrokenResource(jedis);        } finally {            if (borrowOrOprSuccess)                jedisPool.returnResource(jedis);        }    }    @Override    public ReadWriteLock getReadWriteLock() {        return readWriteLock;    }}
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然后，在mapper文件中添加下列一行使对应的表添加缓存支持：

<cache eviction="LRU" type="com.dg.cache.RedisCache" />
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我是以订单表数据作为缓存目标的（通常我们只是对不常变动的数据进行缓存，如登陆用户信息、系统业务配置信息等，这里我用订单表只是作为范例），应用结构如下：

3.测试

测试缓存的话，我们建一个页面，然后查询日期范围的订单列表，如下效果： 

看输出的日志： 

可以看出，初次查询的时候，有sql语句，将订单列表查询出之后放入了缓存中去；返回来在执行刚才的查询动作时，只有下面的输出，说明第二次没再查库，而是直接从redis缓存中去取。

结果列表为：

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以上只是简单介绍了redis和ssm的整合过程，如果需要完整的代码，到http://download.csdn.net/detail/donggang1992/9481612 下载。

转载：http://blog.csdn.net/donggang1992/article/details/51064962