This article will introduce to you how to use springBoot to integrate redis. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to everyone.
REmote DIctionary Server (Redis) is a key-value storage system written by Salvatore Sanfilippo.
Redis is an open source log-type Key-Value database written in ANSI C language, abides by the BSD protocol, supports the network, can be memory-based and persistent, and provides APIs in multiple languages. [Related recommendations: Redis Video Tutorial]
It is often called a data structure server because the value (value) can be a string (String), a hash (Map), a list ( list), sets and ordered sets (sorted sets) and other types.
Advantages of reids
Here are some advantages of Redis:
Exceptionally fast - Redis is very fast, with Performs approximately 110,000 set (SET) operations and approximately 81,000 read/get (GET) operations per second.
Support rich data types - Redis supports most data types commonly used by developers, such as lists, sets, sorted sets, hashes, and more. This makes it easy for Redis to be used to solve various problems, because we know which problems can be better solved using which data types.
Operations are atomic - All Redis operations are atomic, which ensures that the Redis server can receive updated values if two clients access it concurrently.
Multi-utility tool - Redis is a multi-utility tool that can be used for multiple use cases such as: caching, message queues (Redis natively supports publish/subscribe), any short-term Data, for example, sessions in web applications, web page hit counts, etc.
Installation under Window
Download address: https:/ /github.com/MSOpenTech/redis/releases.
Redis supports 32-bit and 64-bit. This needs to be selected according to the actual situation of your system platform. Here we download the Redis-x64-xxx.zip compressed package to the C drive. After decompression, rename the folder to redis.
Open a cmd window and use the cd command to switch directories to C:\redis
Run redis-server.exe redis.windows.conf
If you want convenience, you can add the redis path to the system environment variable, so that you don't have to enter the path again. The following redis.windows.conf can be omitted. If omitted, the default one will be enabled. After input, the following interface will be displayed:
We still use the project from the previous chapter: Springboot integrates springcloud-config to implement hot deployment of dataSource
1. Add dependencies
<!--集成redis-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-redis</artifactId>
<version>1.4.1.RELEASE</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.3</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
</dependency>2. Add redis configuration in the configuration center
spring.redis.host=127.0.0.1 #Redis服务器连接端口 spring.redis.port=6379 #Redis服务器连接密码（默认为空） spring.redis.password= #连接池最大连接数（使用负值表示没有限制） spring.redis.pool.max-active=8 #连接池最大阻塞等待时间（使用负值表示没有限制） spring.redis.pool.max-wait=-1 #连接池中的最大空闲连接 spring.redis.pool.max-idle=8 #连接池中的最小空闲连接 spring.redis.pool.min-idle=0 #连接超时时间（毫秒） spring.redis.timeout=30000
3. Configuration class RedisConfig
import java.lang.reflect.Method;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.cache.CacheManager;
import org.springframework.cache.annotation.CachingConfigurerSupport;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.cache.interceptor.KeyGenerator;
import org.springframework.cloud.context.config.annotation.RefreshScope;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.connection.RedisConnectionFactory;
import org.springframework.data.redis.connection.jedis.JedisConnectionFactory;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer;
import com.fasterxml.jackson.annotation.PropertyAccessor;
import com.fasterxml.jackson.annotation.JsonAutoDetect;
import com.fasterxml.jackson.databind.ObjectMapper;
@Configuration
@EnableCaching
@RefreshScope
public class RedisConfig extends CachingConfigurerSupport{
@Value("${spring.redis.host}")
private String host;
@Value("${spring.redis.port}")
private int port;
@Value("${spring.redis.timeout}")
private int timeout;
@Value("${spring.redis.password}")
private String password;
@Value("${spring.redis.pool.max-active}")
private int maxActive;
@Value("${spring.redis.pool.max-wait}")
private int maxWait;
@Value("${spring.redis.pool.max-idle}")
private int maxIdle;
@Value("${spring.redis.pool.min-idle}")
private int minIdle;
@RefreshScope
@Bean
public KeyGenerator wiselyKeyGenerator(){
return new KeyGenerator() {
@Override
public Object generate(Object target, Method method, Object... params) {
StringBuilder sb = new StringBuilder();
sb.append(target.getClass().getName());
sb.append(method.getName());
for (Object obj : params) {
sb.append(obj.toString());
}
return sb.toString();
}
};
}
@RefreshScope
@Bean
public JedisConnectionFactory redisConnectionFactory() {
JedisConnectionFactory factory = new JedisConnectionFactory();
factory.setHostName(host);
factory.setPort(port);
factory.setTimeout(timeout); //设置连接超时时间
factory.setPassword(password);
factory.getPoolConfig().setMaxIdle(maxIdle);
factory.getPoolConfig().setMinIdle(minIdle);
factory.getPoolConfig().setMaxTotal(maxActive);
factory.getPoolConfig().setMaxWaitMillis(maxWait);
return factory;
}
@RefreshScope
@Bean
public CacheManager cacheManager(RedisTemplate redisTemplate) {
RedisCacheManager cacheManager = new RedisCacheManager(redisTemplate);
// Number of seconds before expiration. Defaults to unlimited (0)
cacheManager.setDefaultExpiration(10); //设置key-value超时时间
return cacheManager;
}
@RefreshScope
@Bean
public RedisTemplate<String, String> redisTemplate(RedisConnectionFactory factory) {
StringRedisTemplate template = new StringRedisTemplate(factory);
setSerializer(template); //设置序列化工具，这样ReportBean不需要实现Serializable接口
template.afterPropertiesSet();
return template;
}
@RefreshScope
private void setSerializer(StringRedisTemplate template) {
Jackson2JsonRedisSerializer jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer(Object.class);
ObjectMapper om = new ObjectMapper();
om.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
om.enableDefaultTyping(ObjectMapper.DefaultTyping.NON_FINAL);
jackson2JsonRedisSerializer.setObjectMapper(om);
template.setValueSerializer(jackson2JsonRedisSerializer);
}
}4. RedisUtils class
import java.io.Serializable;
import java.util.List;
import java.util.Set;
import java.util.concurrent.TimeUnit;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.HashOperations;
import org.springframework.data.redis.core.ListOperations;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.SetOperations;
import org.springframework.data.redis.core.ValueOperations;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.stereotype.Service;
@Service
public class RedisUtils {
@Autowired
private RedisTemplate redisTemplate;
/**
* 写入缓存
* @param key
* @param value
* @return
*/
public boolean set(final String key, Object value) {
boolean result = false;
try {
ValueOperations<serializable> operations = redisTemplate.opsForValue();
operations.set(key, value);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
/**
* 写入缓存设置时效时间
* @param key
* @param value
* @return
*/
public boolean set(final String key, Object value, Long expireTime ,TimeUnit timeUnit) {
boolean result = false;
try {
ValueOperations<serializable> operations = redisTemplate.opsForValue();
operations.set(key, value);
redisTemplate.expire(key, expireTime, timeUnit);
result = true;
} catch (Exception e) {
e.printStackTrace();
}
return result;
}
/**
* 批量删除对应的value
* @param keys
*/
public void remove(final String... keys) {
for (String key : keys) {
remove(key);
}
}
/**
* 批量删除key
* @param pattern
*/
public void removePattern(final String pattern) {
Set<serializable> keys = redisTemplate.keys(pattern);
if (keys.size() > 0){
redisTemplate.delete(keys);
}
}
/**
* 删除对应的value
* @param key
*/
public void remove(final String key) {
if (exists(key)) {
redisTemplate.delete(key);
}
}
/**
* 判断缓存中是否有对应的value
* @param key
* @return
*/
public boolean exists(final String key) {
return redisTemplate.hasKey(key);
}
/**
* 读取缓存
* @param key
* @return
*/
public Object get(final String key) {
Object result = null;
ValueOperations<serializable> operations = redisTemplate.opsForValue();
result = operations.get(key);
return result;
}
/**
* 哈希 添加
* @param key
* @param hashKey
* @param value
*/
public void hmSet(String key, Object hashKey, Object value){
HashOperations<string> hash = redisTemplate.opsForHash();
hash.put(key,hashKey,value);
}
/**
* 哈希获取数据
* @param key
* @param hashKey
* @return
*/
public Object hmGet(String key, Object hashKey){
HashOperations<string> hash = redisTemplate.opsForHash();
return hash.get(key,hashKey);
}
/**
* 列表添加
* @param k
* @param v
*/
public void lPush(String k,Object v){
ListOperations<string> list = redisTemplate.opsForList();
list.rightPush(k,v);
}
/**
* 列表获取
* @param k
* @param l
* @param l1
* @return
*/
public List<object> lRange(String k, long l, long l1){
ListOperations<string> list = redisTemplate.opsForList();
return list.range(k,l,l1);
}
/**
* 集合添加
* @param key
* @param value
*/
public void add(String key,Object value){
SetOperations<string> set = redisTemplate.opsForSet();
set.add(key,value);
}
/**
* 集合获取
* @param key
* @return
*/
public Set<object> setMembers(String key){
SetOperations<string> set = redisTemplate.opsForSet();
return set.members(key);
}
/**
* 有序集合添加
* @param key
* @param value
* @param scoure
*/
public void zAdd(String key,Object value,double scoure){
ZSetOperations<string> zset = redisTemplate.opsForZSet();
zset.add(key,value,scoure);
}
/**
* 有序集合获取
* @param key
* @param scoure
* @param scoure1
* @return
*/
public Set<object> rangeByScore(String key,double scoure,double scoure1){
ZSetOperations<string> zset = redisTemplate.opsForZSet();
return zset.rangeByScore(key, scoure, scoure1);
}</string></object></string></string></object></string></string></object></string></string></string></serializable></serializable></serializable></serializable>
5. Test and modify controller
import java.util.concurrent.TimeUnit;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import com.chenqi.springboot.redis.RedisUtils;
import com.chenqi.springboot.service.TestService;
@RestController
public class SpringBootController {
public static final Logger log = LoggerFactory.getLogger(SpringBootController.class);
@Autowired
TestService testService;
@Autowired
private RedisUtils redisUtils;
@RequestMapping(value = "/hello/{id}")
public String hello(@PathVariable(value = "id") String id){
//查询缓存中是否存在
boolean hasKey = redisUtils.exists(id);
String str = "";
if(hasKey){
//获取缓存
Object object = redisUtils.get(id);
log.info("从缓存获取的数据"+ object);
str = object.toString();
}else{
//从数据库中获取信息
log.info("从数据库中获取数据");
str = testService.test();
//数据插入缓存（set中的参数含义：key值，user对象，缓存存在时间10（long类型），时间单位）
redisUtils.set(id,str,10L,TimeUnit.MINUTES);
log.info("数据插入缓存" + str);
}
return str;
}
}
Start the project, visit for the first time: http://localhost:8002/hello/111
# # Through the console output, we can see that the data is obtained from the database and stored in the redis cache.
You can see that the second time it is read from the cache, let’s try to refresh the browser continuously
As you can see, everything is obtained from the cache afterwards.
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