• springMVC 缓存(入门 spring+mybaties+redis一)


      使用redis之前需要咋电脑上安装redis;

      使用spring+mybaties+redis的本质是扩展类   org.apache.ibatis.cache.Cache;在我们自己扩展的Cache里面使用redis的api;

    一:需要引入的依赖:

    <dependency>
    <groupId>org.springframework.data</groupId>
    <artifactId>spring-data-redis</artifactId>
    <version>1.7.2.RELEASE</version>
    </dependency>
    <dependency>
      <groupId>redis.clients</groupId>
      <artifactId>jedis</artifactId>
      <version>2.1.0</version>
    </dependency>

    二:在mybaties-config.xml配置文件中开启缓存:
    <settings>
      <!-- 这个配置使全局的映射器启用或禁用缓存 -->  
    <setting name="cacheEnabled" value="true"/>
      <!-- 全局启用或禁用延迟加载。当禁用时,所有关联对象都会即时加载。 -->  
    <setting name="lazyLoadingEnabled" value="false"/>
    <setting name="aggressiveLazyLoading" value="true"/>
    </settings>
    此处需要注意的是:
    属性延迟加载和关联对象加载(lazyLoadingEnabled)给关闭了,不然放进redis中的cglib代理对象,在对数据发生更改的时候,会出错。

     三:写属于自己的扩展类(org.apache.ibatis.cache.Cache类的扩展类):

    类一如下:

    package com.rayeye.law.app.utils.redis;

    import org.apache.commons.logging.Log;
    import org.apache.commons.logging.LogFactory;
    import org.apache.ibatis.cache.Cache;
    import redis.clients.jedis.Jedis;
    import redis.clients.jedis.JedisPool;
    import redis.clients.jedis.JedisPoolConfig;

    import java.io.ByteArrayInputStream;
    import java.io.ByteArrayOutputStream;
    import java.io.ObjectInputStream;
    import java.io.ObjectOutputStream;
    import java.util.concurrent.locks.ReadWriteLock;
    import java.util.concurrent.locks.ReentrantReadWriteLock;

    /**
    * Created by Sean on 2016/9/13.
    */
    public class RedisCache implements Cache {

    private static Log logger = LogFactory.getLog(RedisCache.class);
    private Jedis redisClient = createClient();
    /** The ReadWriteLock. */
    private final ReadWriteLock readWriteLock = new ReentrantReadWriteLock();

    private String id;
    public RedisCache(final String id) {
    if (id == null) {
    throw new IllegalArgumentException("Cache instances require an ID");
    }
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>MybatisRedisCache:id=" + id);
    this.id = id;
    }

    @Override
    public String getId() {
    return this.id;
    }

    @Override
    public int getSize() {
    return Integer.valueOf(redisClient.dbSize().toString());
    }

    @Override
    public void putObject(Object key, Object value) {
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>putObject:" + key + "=" + value);
    redisClient.set(SerializeUtil.serialize(key.toString()), SerializeUtil.serialize(value));
    }

    @Override
    public Object getObject(Object key) {
    Object value = SerializeUtil.unserialize(redisClient.get(SerializeUtil.serialize(key.toString())));
    logger.debug(">>>>>>>>>>>>>>>>>>>>>>>>getObject:" + key + "=" + value);
    return value;
    }

    @Override
    public Object removeObject(Object key) {
    return redisClient.expire(SerializeUtil.serialize(key.toString()), 0);
    }

    @Override
    public void clear() {
    redisClient.flushDB();
    }

    @Override
    public ReadWriteLock getReadWriteLock() {
    return readWriteLock;
    }

    protected static Jedis createClient() {
    try {
    JedisPool pool = new JedisPool(new JedisPoolConfig(), "localhost");
    return pool.getResource();
    } catch (Exception e) {
    e.printStackTrace();
    }
    throw new RuntimeException("初始化连接池错误");
    }



    }


    class SerializeUtil {
    public static byte[] serialize(Object object) {
    ObjectOutputStream oos = null;
    ByteArrayOutputStream baos = null;
    try {
    // 序列化
    baos = new ByteArrayOutputStream();
    oos = new ObjectOutputStream(baos);
    oos.writeObject(object);
    byte[] bytes = baos.toByteArray();
    return bytes;
    } catch (Exception e) {
    e.printStackTrace();
    }
    return null;
    }

    public static Object unserialize(byte[] bytes) {
    if(bytes == null)return null;
    ByteArrayInputStream bais = null;
    try {
    // 反序列化
    bais = new ByteArrayInputStream(bytes);
    ObjectInputStream ois = new ObjectInputStream(bais);
    return ois.readObject();
    } catch (Exception e) {
    e.printStackTrace();
    }
    return null;
    }
    }
    类二如下:
    package com.rayeye.law.app.utils.redis;

    import org.apache.ibatis.cache.decorators.LoggingCache;

    /**
    * Created by Sean on 2016/9/13.
    */
    public class LoggingRedisCache extends LoggingCache {
    public LoggingRedisCache(String id) {
    super(new RedisCache(id));
    }
    }

    四:在mapper.xml文件中直接引用缓存
    1. <!-- 启用缓存 -->  
    2.     <cache type="cn.seafood.cache.LoggingRedisCache" />   

    如下:

    <?xml version="1.0" encoding="UTF-8"?>
    <!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
    "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
    <mapper namespace="com.rayeye.law.app.dao.LawAssistantMapper">
    <cache type="com.rayeye.law.app.utils.redis.LoggingRedisCache"/>
    <select id="getWFK" parameterType="java.util.Map" resultType="java.util.Map">
    select * from weifaku where entityStatus=0
    </select>
    </mapper>


    以上为spring+mybaties+redis简单整合的流程,
    redis的优势:
    1.性能极高,
    2.丰富的数据类型,
    3.操作具有原子性(联合的操作也具有原子性),

    缺点:
    1.收到物理内存的限制(redis是一个独立的模块,独占一定内存),不能适用于海量数据的读写(适用于较小数据量的高性能操作)。

    总结:Redis受限于特定的场景,专注于特定的领域之下,速度相当之快,目前还未找到能替代使用产品。




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  • 原文地址:https://www.cnblogs.com/zqsky/p/5870042.html
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