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.
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
org.springframework.boot
spring-boot-starter-data-redis
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());
}
| 功能 | 单个操作接口 | 批量操作接口 |
|---|---|---|
| 有序集合 | ZSetOperations | BoundZsetOperations |
| 字符串 | ValueOperations | BoundValueOpetations |
| 集合 | SetOperations | BoundSetOperations |
| 列表 | ListOperations | BoundListOperations |
| 散列 | HashOperations | BoundHashOperations |
| 基数 | HyperLogLogOperations | BoundHyperLogLogOperaions |
| 地理位置 | GeoOperations | BoundGeoOperations |
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);
}
- SessionCallback 高级操作对象
- 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;
}
});
}
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 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：
列表操作更多提供的方法需要在业务场景中多使用
@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 lk2ValuesList = stringRedisTemplate.opsForList().range("lk2", 0, 3);
System.out.println(lk2ValuesList);
}
@Test
void setTest() {
stringRedisTemplate.opsForSet().add("sk1","sk1v1","sk1v2","sk1v3");
stringRedisTemplate.opsForSet().add("sk2","sk1v1","sk2v2","sk2v3");
final Set sk1 = stringRedisTemplate.opsForSet().members("sk1");
final Set sk2 = stringRedisTemplate.opsForSet().members("sk2");
System.out.println("sk1: "+sk1);
System.out.println("sk2: "+sk2);
final Set intersect = stringRedisTemplate.opsForSet().intersect("sk1", "sk2");
System.out.println("交集是：" + intersect);
final Set union = stringRedisTemplate.opsForSet().union("sk1", "sk2");
System.out.println("并集：" + union);
final Set 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");
}
@Test
void zsetTest() {
IntStream.rangeClosed(1,100).forEach(i->{
stringRedisTemplate.opsForZSet().add("zsk1",String.valueOf(i),i*10);
});
final Set> typedTupleSet = IntStream.rangeClosed(1, 100).mapToObj(i -> new DefaultTypedTuple(String.valueOf(i), (double) i * 11)).collect(Collectors.toSet());
stringRedisTemplate.opsForZSet().add("zsk2",typedTupleSet);
final Set zsk1 = stringRedisTemplate.opsForZSet().rangeByLex("zsk1", RedisZSetCommands.Range.range().gte(20).lte(100));
System.out.println("范围内的集合：" + zsk1);
}
@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
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;
@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;
@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() {
@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;
@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;
@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
- publish myChannel helloworld
- 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;
@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 redisscript = new DefaultRedisscript<>();
redisscript.setscriptText(Luascript.lua1);
redisscript.setResultType(Long.class);
return stringRedisTemplate.execute(redisscript, Arrays.asList(k1, k2), v1, v2);
}
通过本篇文章，你可以学会：
- 学会使用spring-boot-redis-starter熟练的进行各种数据类型的操作；
- 学会了使用注解的方式使用redis缓存；
- 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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