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起源:blog.csdn.net/qq_42105629/article/details/102589319
一、Jedis,Redisson,Lettuce 三者的区别
共同点:都提供了基于 Redis 操作的 Java API,只是封装水平,具体实现稍有不同。
不同点:
1.1、Jedis
是 Redis 的 Java 实现的客户端。反对根本的数据类型如:String、Hash、List、Set、Sorted Set。
特点:应用阻塞的 I /O,办法调用同步,程序流须要等到 socket 解决完 I / O 能力执行,不反对异步操作。Jedis 客户端实例不是线程平安的,须要通过连接池来应用 Jedis。
1.2、Redisson
长处点:分布式锁,分布式汇合,可通过 Redis 反对提早队列。
1.3、Lettuce
用于线程平安同步,异步和响应应用,反对集群,Sentinel,管道和编码器。
基于 Netty 框架的事件驱动的通信层,其办法调用是异步的。Lettuce 的 API 是线程平安的,所以能够操作单个 Lettuce 连贯来实现各种操作。
二、RedisTemplate
2.1、应用配置
maven 配置引入,(要加上版本号,我这里是因为 Parent 已申明)
<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)
Spring Boot 根底就不介绍了,举荐下这个实战教程:
https://github.com/javastacks…
2.2、应用示例
@Resource
private StringRedisTemplate stringRedisTemplate;
@Override
public CustomersEntity findById(Integer id) {
// 须要缓存
// 所有波及的缓存都须要删除,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, 而后缓存 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;
}
2.3、扩大
2.3.1、spring-boot-starter-data-redis 的依赖包
3.3.2、stringRedisTemplate API(局部展现)
- opsForHash –> hash 操作
- opsForList –> list 操作
- opsForSet –> set 操作
- opsForValue –> string 操作
- opsForZSet –> Zset 操作
3.3.3 StringRedisTemplate 默认序列化机制
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);
}
}
三、RedissonClient 操作示例
3.1 根本配置
3.1.1、Maven pom 引入
<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>
3.1.2、增加配置文件 Yaml 或者 json 格局
redisson-config.yml
# Redisson 配置
singleServerConfig:
address: "redis://192.168.1.140:6379"
password: null
clientName: null
database: 15 #抉择应用哪个数据库 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
}
3.1.3、读取配置
新建读取配置类
@Configuration
public class RedissonConfig {
@Bean
public RedissonClient redisson() throws IOException {
// 两种读取形式,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
3.2 应用示例
@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);
// 寄存 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 查问
RMap<String, Ur> ss = redissonClient.getMap("UR");
Ur ur = ss.get(id);
return ur.toString();}
// 查问所有的 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("================ 线程已完结 ================================" + s);
return s;
}
}
4.3 扩大
4.3.1 丰盛的 jar 反对,尤其是对 Netty NIO 框架
4.3.2 丰盛的配置机制抉择,这里是具体的配置阐明
https://github.com/redisson/r…
对于序列化机制中,就有很多
4.3.3 API 反对(局部展现),具体的 Redis –> RedissonClient , 可查看这里
https://github.com/redisson/r…
4.3.4 轻便的丰盛的锁机制的实现
- Lock
- Fair Lock
- MultiLock
- RedLock
- ReadWriteLock
- Semaphore
- PermitExpirableSemaphore
- CountDownLatch
四、基于注解实现的 Redis 缓存
4.1 Maven 和 YML 配置
参考 RedisTemplate 配置。另外,还须要额定的配置类
// 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);
// 解决查问缓存转换异样的问题
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;
}
}
4.2 应用示例
@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";
// ===================================================================== 应用 Spring cahce 注解形式实现缓存
// ================================== 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(加了很多本义符 \,),不是 Json 格局
@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,不乱码已解决好, 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 先查问缓存,再校验是否统一,而后更新操作,比拟实用,要分明缓存的数据格式(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;
}
}
4.3 扩大
基于 spring 缓存实现
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