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共同点:都提供了基于Redis操作的Java API,只是封装程度,具体实现稍有不同。
不同点:
是Redis的Java实现的客户端。支持基本的数据类型如:String、Hash、List、Set、Sorted Set。
特点:使用阻塞的I/O,方法调用同步,程序流需要等到socket处理完I/O才能执行,不支持异步操作。Jedis客户端实例不是线程安全的,需要通过连接池来使用Jedis。
优点点: 分布式锁,分布式集合,可通过Redis支持延迟队列。
用于线程安全同步,异步和响应使用,支持集群,Sentinel,管道和编码器。
基于Netty框架的事件驱动的通信层,其方法调用是异步的。Lettuce的API是线程安全的,所以可以操作单个Lettuce连接来完成各种操作。
maven配置引入,(要加上版本号,我这里是因为Parent已声明)
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
application-dev.yml
spring:
redis:
host: 192.168.1.140
port: 6379
password:
database: 15 # 指定redis的分库(共16个0到15)
@Resource private StringRedisTemplate stringRedisTemplate; @Override public CustomersEntity findById(Integer id) { // 需要缓存 // 所有涉及的缓存都需要删除,或者更新 try { String toString = stringRedisTemplate.opsForHash().get(REDIS_CUSTOMERS_ONE, id + "").toString(); if (toString != null) { return JSONUtil.toBean(toString, CustomersEntity.class); } } catch (Exception e) { e.printStackTrace(); } // 缓存为空的时候,先查,然后缓存redis Optional<CustomersEntity> byId = customerRepo.findById(id); if (byId.isPresent()) { CustomersEntity customersEntity = byId.get(); try { stringRedisTemplate.opsForHash().put(REDIS_CUSTOMERS_ONE, id + "", JSONUtil.toJsonStr(customersEntity)); } catch (Exception e) { e.printStackTrace(); } return customersEntity; } return null; }
opsForHash --> hash操作
opsForList --> list操作
opsForSet --> set操作
opsForValue --> string操作
opsForZSet --> Zset操作
public class StringRedisTemplate extends RedisTemplate<String, String> {
/**
* Constructs a new <code>StringRedisTemplate</code> instance. {@link #setConnectionFactory(RedisConnectionFactory)}
* and {@link #afterPropertiesSet()} still need to be called.
*/
public StringRedisTemplate() {
RedisSerializer<String> stringSerializer = new StringRedisSerializer();
setKeySerializer(stringSerializer);
setValueSerializer(stringSerializer);
setHashKeySerializer(stringSerializer);
setHashValueSerializer(stringSerializer);
}
}
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
<groupId>org.redisson</groupId>
<artifactId>redisson</artifactId>
<version>3.8.2</version>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.redisson</groupId>
<artifactId>redisson-spring-boot-starter</artifactId>
<version>LATEST</version>
</dependency>
redisson-config.yml
# Redisson 配置 singleServerConfig: address: "redis://192.168.1.140:6379" password: null clientName: null database: 15 #选择使用哪个数据库0~15 idleConnectionTimeout: 10000 pingTimeout: 1000 connectTimeout: 10000 timeout: 3000 retryAttempts: 3 retryInterval: 1500 reconnectionTimeout: 3000 failedAttempts: 3 subscriptionsPerConnection: 5 subscriptionConnectionMinimumIdleSize: 1 subscriptionConnectionPoolSize: 50 connectionMinimumIdleSize: 32 connectionPoolSize: 64 dnsMonitoringInterval: 5000 #dnsMonitoring: false threads: 0 nettyThreads: 0 codec: class: "org.redisson.codec.JsonJacksonCodec" transportMode: "NIO"
或者,配置 redisson-config.json
{ "singleServerConfig": { "idleConnectionTimeout": 10000, "pingTimeout": 1000, "connectTimeout": 10000, "timeout": 3000, "retryAttempts": 3, "retryInterval": 1500, "reconnectionTimeout": 3000, "failedAttempts": 3, "password": null, "subscriptionsPerConnection": 5, "clientName": null, "address": "redis://192.168.1.140:6379", "subscriptionConnectionMinimumIdleSize": 1, "subscriptionConnectionPoolSize": 50, "connectionMinimumIdleSize": 10, "connectionPoolSize": 64, "database": 0, "dnsMonitoring": false, "dnsMonitoringInterval": 5000 }, "threads": 0, "nettyThreads": 0, "codec": null, "useLinuxNativeEpoll": false }
新建读取配置类
@Configuration
public class RedissonConfig {
@Bean
public RedissonClient redisson() throws IOException {
// 两种读取方式,Config.fromYAML 和 Config.fromJSON
// Config config = Config.fromJSON(RedissonConfig.class.getClassLoader().getResource("redisson-config.json"));
Config config = Config.fromYAML(RedissonConfig.class.getClassLoader().getResource("redisson-config.yml"));
return Redisson.create(config);
}
}
或者,在 application.yml中配置如下
spring:
redis:
redisson:
config: classpath:redisson-config.yaml
@RestController @RequestMapping("/") public class TeController { @Autowired private RedissonClient redissonClient; static long i = 20; static long sum = 300; // ========================== String ======================= @GetMapping("/set/{key}") public String s1(@PathVariable String key) { // 设置字符串 RBucket<String> keyObj = redissonClient.getBucket(key); keyObj.set(key + "1-v1"); return key; } @GetMapping("/get/{key}") public String g1(@PathVariable String key) { // 设置字符串 RBucket<String> keyObj = redissonClient.getBucket(key); String s = keyObj.get(); return s; } // ========================== hash =======================-= @GetMapping("/hset/{key}") public String h1(@PathVariable String key) { Ur ur = new Ur(); ur.setId(MathUtil.randomLong(1,20)); ur.setName(key); // 存放 Hash RMap<String, Ur> ss = redissonClient.getMap("UR"); ss.put(ur.getId().toString(), ur); return ur.toString(); } @GetMapping("/hget/{id}") public String h2(@PathVariable String id) { // hash 查询 RMap<String, Ur> ss = redissonClient.getMap("UR"); Ur ur = ss.get(id); return ur.toString(); } // 查询所有的 keys @GetMapping("/all") public String all(){ RKeys keys = redissonClient.getKeys(); Iterable<String> keys1 = keys.getKeys(); keys1.forEach(System.out::println); return keys.toString(); } // ================== ==============读写锁测试 ============================= @GetMapping("/rw/set/{key}") public void rw_set(){ // RedissonLock. RBucket<String> ls_count = redissonClient.getBucket("LS_COUNT"); ls_count.set("300",360000000l, TimeUnit.SECONDS); } // 减法运算 @GetMapping("/jf") public void jf(){ String key = "S_COUNT"; // RAtomicLong atomicLong = redissonClient.getAtomicLong(key); // atomicLong.set(sum); // long l = atomicLong.decrementAndGet(); // System.out.println(l); RAtomicLong atomicLong = redissonClient.getAtomicLong(key); if (!atomicLong.isExists()) { atomicLong.set(300l); } while (i == 0) { if (atomicLong.get() > 0) { long l = atomicLong.getAndDecrement(); try { Thread.sleep(1000l); } catch (InterruptedException e) { e.printStackTrace(); } i --; System.out.println(Thread.currentThread().getName() + "->" + i + "->" + l); } } } @GetMapping("/rw/get") public String rw_get(){ String key = "S_COUNT"; Runnable r = new Runnable() { @Override public void run() { RAtomicLong atomicLong = redissonClient.getAtomicLong(key); if (!atomicLong.isExists()) { atomicLong.set(300l); } if (atomicLong.get() > 0) { long l = atomicLong.getAndDecrement(); i --; System.out.println(Thread.currentThread().getName() + "->" + i + "->" + l); } } }; while (i != 0) { new Thread(r).start(); // new Thread(r).run(); // new Thread(r).run(); // new Thread(r).run(); // new Thread(r).run(); } RBucket<String> bucket = redissonClient.getBucket(key); String s = bucket.get(); System.out.println("================线程已结束================================" + s); return s; } }
关于序列化机制中,就有很多
参考 RedisTemplate 配置
另外,还需要额外的配置类
// todo 定义序列化,解决乱码问题 @EnableCaching @Configuration @ConfigurationProperties(prefix = "spring.cache.redis") public class RedisCacheConfig { private Duration timeToLive = Duration.ZERO; public void setTimeToLive(Duration timeToLive) { this.timeToLive = timeToLive; } @Bean public CacheManager cacheManager(RedisConnectionFactory factory) { RedisSerializer<String> redisSerializer = new StringRedisSerializer(); Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class); // 解决查询缓存转换异常的问题 ObjectMapper om = new ObjectMapper(); om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY); om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL); jackson2JsonRedisSerializer.setObjectMapper(om); // 配置序列化(解决乱码的问题) RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig() .entryTtl(timeToLive) .serializeKeysWith(RedisSerializationContext.SerializationPair.fromSerializer(redisSerializer)) .serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(jackson2JsonRedisSerializer)) .disableCachingNullValues(); RedisCacheManager cacheManager = RedisCacheManager.builder(factory) .cacheDefaults(config) .build(); return cacheManager; } }
@Transactional @Service public class ReImpl implements RedisService { @Resource private CustomerRepo customerRepo; @Resource private StringRedisTemplate stringRedisTemplate; public static final String REDIS_CUSTOMERS_ONE = "Customers"; public static final String REDIS_CUSTOMERS_ALL = "allList"; // =====================================================================使用Spring cahce 注解方式实现缓存 // ==================================单个操作 @Override @Cacheable(value = "cache:customer", unless = "null == #result",key = "#id") public CustomersEntity cacheOne(Integer id) { final Optional<CustomersEntity> byId = customerRepo.findById(id); return byId.isPresent() ? byId.get() : null; } @Override @Cacheable(value = "cache:customer", unless = "null == #result", key = "#id") public CustomersEntity cacheOne2(Integer id) { final Optional<CustomersEntity> byId = customerRepo.findById(id); return byId.isPresent() ? byId.get() : null; } // todo 自定义redis缓存的key, @Override @Cacheable(value = "cache:customer", unless = "null == #result", key = "#root.methodName + '.' + #id") public CustomersEntity cacheOne3(Integer id) { final Optional<CustomersEntity> byId = customerRepo.findById(id); return byId.isPresent() ? byId.get() : null; } // todo 这里缓存到redis,还有响应页面是String(加了很多转义符\,),不是Json格式 @Override @Cacheable(value = "cache:customer", unless = "null == #result", key = "#root.methodName + '.' + #id") public String cacheOne4(Integer id) { final Optional<CustomersEntity> byId = customerRepo.findById(id); return byId.map(JSONUtil::toJsonStr).orElse(null); } // todo 缓存json,不乱码已处理好,调整序列化和反序列化 @Override @Cacheable(value = "cache:customer", unless = "null == #result", key = "#root.methodName + '.' + #id") public CustomersEntity cacheOne5(Integer id) { Optional<CustomersEntity> byId = customerRepo.findById(id); return byId.filter(obj -> !StrUtil.isBlankIfStr(obj)).orElse(null); } // ==================================删除缓存 @Override @CacheEvict(value = "cache:customer", key = "'cacheOne5' + '.' + #id") public Object del(Integer id) { // 删除缓存后的逻辑 return null; } @Override @CacheEvict(value = "cache:customer",allEntries = true) public void del() { } @CacheEvict(value = "cache:all",allEntries = true) public void delall() { } // ==================List操作 @Override @Cacheable(value = "cache:all") public List<CustomersEntity> cacheList() { List<CustomersEntity> all = customerRepo.findAll(); return all; } // todo 先查询缓存,再校验是否一致,然后更新操作,比较实用,要清楚缓存的数据格式(明确业务和缓存模型数据) @Override @CachePut(value = "cache:all",unless = "null == #result",key = "#root.methodName") public List<CustomersEntity> cacheList2() { List<CustomersEntity> all = customerRepo.findAll(); return all; } }
基于spring缓存实现
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