李福春 · 2020年01月21日

0121 spring-boot-redis的使用

redis是什么呢?redis,属于NoSQL的一种,在互联网时代,起到加速系统的作用。

redis是一种内存数据库,支持7种数据类型的存储,性能1S 10w次读写;
redis提供的简单的事务保证了高并发场景下数的一致性。
redis在2.6版本之后增加了lua支持,命令是原子性的;

本篇文章主要基于springboot的redis-starter。
HELLO, 性能利器Redis.

spring-boot-starter-redis


这个是springboot提供的redis操作工具包,底层的redis驱动使用的是lettus,而不是jedis;

依赖

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>

序列化

主要通过RedisTemplate来操作redis;
 

当然也支持自定义序列化器,比如效率比较高的kyto序列化器;
StringRedisTemplate:key,value都是按照字符串存储的。
TypedTuple 保存集合中的有序元素;
可以查看一下StringRedisTemplate的源码:
public StringRedisTemplate() {
    setKeySerializer(RedisSerializer.string());
    setValueSerializer(RedisSerializer.string());
    setHashKeySerializer(RedisSerializer.string());
    setHashValueSerializer(RedisSerializer.string());
}

数据类型操作接口

功能单个操作接口批量操作接口
有序集合ZSetOperationsBoundZsetOperations
字符串ValueOperationsBoundValueOpetations
集合SetOperationsBoundSetOperations
列表ListOperationsBoundListOperations
散列HashOperationsBoundHashOperations
基数HyperLogLogOperationsBoundHyperLogLogOperaions
地理位置GeoOperationsBoundGeoOperations

使用代码

 @Autowired
    private RedisTemplate redisTemplate;

    @Test
    void stringRedisTest() {
        final ValueOperations valueOperations = redisTemplate.opsForValue();
        valueOperations
                .set("key1", "value1", Duration.ofMinutes(1));

        final Object value = valueOperations.get("key1");

        Assert.isTrue(Objects.equals("value1", value), "set失败");

        final HashOperations hashOperations = redisTemplate.opsForHash();

        hashOperations.put("hash1", "f1", "v1");
        hashOperations.put("hash1", "f2", "v2");

        hashOperations.values("hash1").forEach(System.out::println);
    }

在同一条连接中进行多次操作

  1. SessionCallback 高级操作对象
  2. RedisCallback   低级操作对象

代码中直接使用的java8的lambda表达式。

使用代码

@Test
void redisCallbackTest() {
    redisTemplate.execute((RedisCallback) connection -> {
        connection.set("rkey1".getBytes(), "rv1".getBytes());
        connection.set("rkey2".getBytes(), "rv2".getBytes());
        return null;
    });
}

@Test
void sessionCallbackTest() {
    redisTemplate.execute(new SessionCallback() {
        @Override
        public Object execute(RedisOperations operations) throws DataAccessException {
            final ListOperations listOperations = operations.opsForList();
            listOperations.leftPush("sk1", "sv1");
            listOperations.leftPush("sk1", "sv2");
            listOperations.getOperations().expire("sk1", 1, TimeUnit.MINUTES);

            listOperations.range("sk1", 0, 2).forEach(System.out::println);
            return 1;
        }
    });
}

字符串操作

最为常用的数据类型
实际情况使用的不多,现实的场景一般是放一个对象或者对象列表 转换为字符串 进行存储,取出的时候再转换为对象;

代码:

 @Test
    void stringTest() {
        redisTemplate.opsForValue().set("stringKey1", "value1", 5, TimeUnit.MINUTES);

        //字符串类型的整数,不能进行数字运算;
        redisTemplate.opsForValue().set("stringKey2", "1", 5, TimeUnit.MINUTES);

        //进行数字运算,增加,减少
        redisTemplate.opsForValue().set("stringKey3", 1, 5, TimeUnit.MINUTES);
        redisTemplate.opsForValue().increment("stringKey3",1);
        redisTemplate.opsForValue().decrement("stringKey3",1);

        //其它操作方法
        final Long keySize = redisTemplate.opsForValue().size("stringKey1");
        System.out.println(keySize);
        
        //批量设置
        Map<String,Long> map = new HashMap<>(4);
        map.put("sk1",1L);
        map.put("sk2",2L);
        map.put("sk3",3L);
        map.put("sk4",4L);
        redisTemplate.opsForValue().multiSet(map);
        redisTemplate.opsForValue().multiSetIfAbsent(map);
        //批量获取
        redisTemplate.opsForValue().multiGet(map.keySet()).forEach(System.out::println);


        //getAndSet
        final Object sk5Value = redisTemplate.opsForValue().getAndSet("sk5", 100);
        System.out.println("sk5Value:"+sk5Value);
        
        redisTemplate.opsForValue().append("sk5","hello redis");
        System.out.println("sk5Value2:"+redisTemplate.opsForValue().get("sk5"));
        
        //按照情况设置,可以省去了之前查询出来之后判断是否存在再操作的代码;
        redisTemplate.opsForValue().setIfAbsent("sk6",1000,5,TimeUnit.MINUTES);
        redisTemplate.opsForValue().setIfPresent("sk6",100,5,TimeUnit.MINUTES);

    }

其它方法:

更多提供的方法需要在业务场景中多使用

列表操作

 @Test
    void listTest() {

        stringRedisTemplate.opsForList().leftPush("lk1","lkv1");
        stringRedisTemplate.opsForList().leftPushAll("lk2","lk2v1","lk2v2");
        stringRedisTemplate.opsForList().leftPushAll("lk2",Arrays.asList("lk2v3","lk2v4"));
        stringRedisTemplate.opsForList().leftPushIfPresent("lk3","lk3v1");

        final List<String> lk2ValuesList = stringRedisTemplate.opsForList().range("lk2", 0, 3);
        System.out.println(lk2ValuesList);
    }

集合操作

@Test
    void setTest() {
        stringRedisTemplate.opsForSet().add("sk1","sk1v1","sk1v2","sk1v3");
        stringRedisTemplate.opsForSet().add("sk2","sk1v1","sk2v2","sk2v3");

        final Set<String> sk1 = stringRedisTemplate.opsForSet().members("sk1");
        final Set<String> sk2 = stringRedisTemplate.opsForSet().members("sk2");

        System.out.println("sk1: "+sk1);
        System.out.println("sk2: "+sk2);

        final Set<String> intersect = stringRedisTemplate.opsForSet().intersect("sk1", "sk2");
        System.out.println("交集是:" + intersect);

        final Set<String> union = stringRedisTemplate.opsForSet().union("sk1", "sk2");
        System.out.println("并集:" + union);

        final Set<String> difference = stringRedisTemplate.opsForSet().difference("sk1", "sk2");
        System.out.println("差集:"+ difference);

        final Long size = stringRedisTemplate.opsForSet().size("sk1");

        System.out.println("size for sk1 : " + size);

        stringRedisTemplate.delete("sk1");
        stringRedisTemplate.delete("sk2");

    }

有序集合操作

 @Test
    void zsetTest() {
        IntStream.rangeClosed(1,100).forEach(i->{
            stringRedisTemplate.opsForZSet().add("zsk1",String.valueOf(i),i*10);
        });
        final Set<ZSetOperations.TypedTuple<String>> typedTupleSet = IntStream.rangeClosed(1, 100).mapToObj(i -> new DefaultTypedTuple<String>(String.valueOf(i), (double) i * 11)).collect(Collectors.toSet());
        stringRedisTemplate.opsForZSet().add("zsk2",typedTupleSet);

        final Set<String> zsk1 = stringRedisTemplate.opsForZSet().rangeByLex("zsk1", RedisZSetCommands.Range.range().gte(20).lte(100));
        System.out.println("范围内的集合:" + zsk1);

    }

散列表操作

 @Test
    void hashTest() {
        stringRedisTemplate.opsForHash().put("hashk1","k1","v1");
        stringRedisTemplate.opsForHash().put("hashk1","k2","v1");
        stringRedisTemplate.opsForHash().put("hashk1","k3","v1");

        stringRedisTemplate.opsForHash().putIfAbsent("hashk1","k4","new V1");

        final List<Object> multiGet = stringRedisTemplate.opsForHash().multiGet("hashk1", Arrays.asList("k1", "k2"));
        System.out.println("一次获取多个:" + multiGet);

 }

springboot中redis的配置

配置分两个部分,连接池和连接信息;下表列出必须给出的配置:
spring.redis.port=6379
spring.redis.host=localhost
spring.redis.password=
spring.redis.timeout=1000

#最小空闲连接数
spring.redis.lettuce.pool.min-idle=2
#最大空闲连接数
spring.redis.lettuce.pool.max-idle=4
#最大活跃连接数
spring.redis.lettuce.pool.max-active=8
#连接最长分配等待时间
spring.redis.lettuce.pool.max-wait=2000
#回收线程间隔毫秒数
spring.redis.lettuce.pool.time-between-eviction-runs=100

注解操作redis

配置CacheManager
spring.redis.cache.type=redis
spring.redis.cache.name=redisCache
通过注解@EnableCaching启用;
[@CachePut ]() 更新缓存
[@CacheEvicat ]() 清除缓存
[@CacheAble ]() 使用查询缓存

缓存在一个类中互相调用失效 : 基于AOP的动态代理,没有生成代理类;

package com.springbootpractice.demo.redis.config;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheConfiguration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.cache.RedisCacheWriter;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.serializer.JdkSerializationRedisSerializer;
import org.springframework.data.redis.serializer.RedisSerializationContext;

import java.time.Duration;

/**
 * 说明:代码方式配置缓存管理器
 * @author carter
 * 创建时间: 2020年01月21日 7:00 下午
 **/
@Configuration
public class RedisConfig {

    @Autowired private RedisTemplate redisTemplate;


    @Bean
    public RedisCacheManager redisCacheManager(){
        RedisCacheWriter redisWrite = RedisCacheWriter.lockingRedisCacheWriter(redisTemplate.getConnectionFactory());

        RedisCacheConfiguration configuration = RedisCacheConfiguration.defaultCacheConfig();

        configuration.prefixKeysWith("_demo_redis_");
        configuration.entryTtl(Duration.ofMinutes(10));
        configuration.serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(new JdkSerializationRedisSerializer()));

        RedisCacheManager redisCacheManager = new RedisCacheManager(redisWrite,configuration);

        return redisCacheManager;
    }
}

用法

package com.springbootpractice.demo.redis.biz;

import com.springbootpractice.demo.redis.dao.entity.UserLoginExtEntity;
import com.springbootpractice.demo.redis.dao.mapper.UserLoginExtEntityMapper;
import org.springframework.cache.annotation.CacheEvict;
import org.springframework.cache.annotation.CachePut;
import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;

/**
 * 说明:操作user的数据增强层
 * @author carter
 * 创建时间: 2020年01月21日 6:40 下午
 **/
@Service
public class UserLoginExtBiz {

    private final UserLoginExtEntityMapper userLoginExtEntityMapper;

    public UserLoginExtBiz(UserLoginExtEntityMapper userLoginExtEntityMapper) {
        this.userLoginExtEntityMapper = userLoginExtEntityMapper;
    }

    @Cacheable(value = "redisCache",key = "'getById:'+#id")
    public UserLoginExtEntity getById(Integer id){
        return userLoginExtEntityMapper.selectByPrimaryKey(id);
    }

    @CachePut(value = "redisCache",key = "'getById:'+#param.id")
    public UserLoginExtEntity updateUserLoginExt(UserLoginExtEntity param){
        userLoginExtEntityMapper.updateByPrimaryKeySelective(param);
        return param;
    }

    @CacheEvict(value = "redisCache",key = "'getById:'+#id")
    public int deleteUserLoginExt(Integer id){
       return userLoginExtEntityMapper.logicalDeleteByPrimaryKey(id);
    }

}

redis的特殊用法

redis中事务的用法

利用的是SessionCallback的RedisOperations 的 watch-multi-exec 连环操作;
watch: 监控某些key;
multi:开始事务;
exec: 执行事务
如果watch的key对应的值发生变化(设置为原值也是发生了变化),则会回滚事务;否则,正常的执行事务 ;
redis在执行事务的时候,要么全部执行,要么全部失败,不会被其它的redis客户端打断,保证了redis事务下数据的一致性;
 @Test
    void transactionTest() {
        final String ttk1 = "ttk1";
        stringRedisTemplate.opsForValue().set(ttk1,"ttk1v1");
        final List list = stringRedisTemplate.execute(new SessionCallback<List>() {
            @Override
            public List execute(RedisOperations operations) throws DataAccessException {
                System.out.println("监听"+ttk1);
                //如果ttk1的值发生了变化,重新set一样的值也是发生了变化,则回滚事务,否则正常执行
                operations.watch(ttk1);

                //开启事务
                System.out.println("开启事务");
                operations.multi();
                operations.opsForList().leftPushAll("xxx_lk1", "v1", "v2", "v3");
                final List xxx_lk1 = operations.opsForList().range("xxx_lk1", 0, 2);
                System.out.println(xxx_lk1);

                operations.opsForSet().add("xxx_sk1", "v1", "v2", "v3");
                final Set xxx_sk1 = operations.opsForSet().members("xxx_sk1");
                System.out.println(xxx_sk1);
                //提交事务
                final List list = operations.exec();
                System.out.println("提交事务");
                return list;
            }
        });

        System.out.println("执行结果:"+list);


    }

批量执行redis操作

redisTemplate.executePipelined();
 @Test
    void pipelineTest() {

        StopWatch stopWatch = new StopWatch("pipelineTest");
        stopWatch.start();
        final List<Object> objectList = stringRedisTemplate.executePipelined(new SessionCallback<Object>() {
            @Override
            public Object execute(RedisOperations operations) throws DataAccessException {

                for (int i = 1; i <= 10000; i++) {
                    operations.opsForValue().set("pk" + i, "pkv" + i, 5, TimeUnit.MINUTES);
                }

                return null;
            }
        });

        stopWatch.stop();
        System.out.println(stopWatch.prettyPrint());
    }

消息队列

需要定义一个一个RedisMessageListenerContainer,配置topic和监听器; 作为消费者;
通过redisTemplate.convertAndSend方法发送消息;

定义监听器

package com.springbootpractice.demo.redis.listener;

import org.springframework.data.redis.connection.Message;
import org.springframework.stereotype.Component;

/**
 * 说明:redis的监听器
 * @author carter
 * 创建时间: 2020年01月21日 5:51 下午
 **/
@Component
public class MyRedisMessageListener implements org.springframework.data.redis.connection.MessageListener {
    
    @Override
    public void onMessage(Message message, byte[] pattern) {

        System.out.println("MyRedisMessageListener topic:"+new String(pattern) +" 消息:"+ new String(message.getBody()));

    }
}

注册监听器容器

package com.springbootpractice.demo.redis.listener;

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.listener.ChannelTopic;
import org.springframework.data.redis.listener.RedisMessageListenerContainer;
import org.springframework.data.redis.listener.Topic;

import java.util.concurrent.ExecutorService;
import java.util.concurrent.LinkedBlockingDeque;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;

/**
 * 说明:配置队列监听器,对应的主题
 * @author carter
 * 创建时间: 2020年01月21日 5:55 下午
 **/
@Configuration
public class RedisListenerConfig {

    public static final String MY_CHANNEL = "myChannel";
    private final MyRedisMessageListener myRedisMessageListener;
    private final MyRedisMessageListener2 myRedisMessageListener2;
    private final RedisTemplate redisTemplate;

    public RedisListenerConfig(MyRedisMessageListener myRedisMessageListener, MyRedisMessageListener2 myRedisMessageListener2, RedisTemplate redisTemplate) {
        this.myRedisMessageListener = myRedisMessageListener;
        this.myRedisMessageListener2 = myRedisMessageListener2;
        this.redisTemplate = redisTemplate;
    }

    @Bean
    public RedisMessageListenerContainer redisMessageListenerContainer() {
        RedisMessageListenerContainer redisMessageListenerContainer = new RedisMessageListenerContainer();

        redisMessageListenerContainer.setConnectionFactory(redisTemplate.getConnectionFactory());
        final ExecutorService taskExecutor = new ThreadPoolExecutor(1,
                2, 30, TimeUnit.SECONDS, new LinkedBlockingDeque<>(2000));
        redisMessageListenerContainer.setTaskExecutor(taskExecutor);

        final Topic myChannel = new ChannelTopic(MY_CHANNEL);

        redisMessageListenerContainer.addMessageListener(myRedisMessageListener, myChannel);
        redisMessageListenerContainer.addMessageListener(myRedisMessageListener2, myChannel);

        System.out.println("注册redis的消息队列成功!");
        return redisMessageListenerContainer;
    }

}

测试代码

  1. publish myChannel helloworld 
  2. redisTemplate.convertAndSend(channel,message);
package com.springbootpractice.demo.redis.web;

import com.springbootpractice.demo.redis.listener.RedisListenerConfig;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RestController;

/**
 * 说明:TODO
 * @author carter
 * 创建时间: 2020年01月21日 6:22 下午
 **/
@RestController
public class TestController {

    private final StringRedisTemplate stringRedisTemplate;

    public TestController(StringRedisTemplate stringRedisTemplate) {
        this.stringRedisTemplate = stringRedisTemplate;
    }

    @GetMapping(path = "/send/{message}")
    public void publishMessage(@PathVariable("message") String message){
        stringRedisTemplate.convertAndSend(RedisListenerConfig.MY_CHANNEL,message);
    }
}

使用lua脚本

使用的redisTemplate.execute(RedisScript,List,List);
@GetMapping(path = "/lua/{k1}/{v1}/{k2}/{v2}")
    public Long publishMessage(@PathVariable("k1") String k1,@PathVariable("k2") String k2,@PathVariable("v1") String v1,@PathVariable("v2") String v2){
        DefaultRedisScript<Long> redisScript = new DefaultRedisScript<>();
        redisScript.setScriptText(LuaScript.lua1);
        redisScript.setResultType(Long.class);

        return stringRedisTemplate.execute(redisScript, Arrays.asList(k1, k2), v1, v2);
    }

小结

通过本篇文章,你可以学会:

  1. 学会使用spring-boot-redis-starter熟练的进行各种数据类型的操作;
  2. 学会了使用注解的方式使用redis缓存;
  3. redis的特殊用法,事务,消息队列,批量操作,lua脚本支持;

代码点我获取!

美女还是要给看的。
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