How to use @Cacheable in the integration of springboot and redis
First we need to configure a cache manager, and then we can use cache annotations to manage the cache.
package com.cherish.servicebase.handler; import com.fasterxml.jackson.annotation.JsonAutoDetect; import com.fasterxml.jackson.annotation.PropertyAccessor; import com.fasterxml.jackson.databind.ObjectMapper; import org.springframework.cache.CacheManager; import org.springframework.cache.annotation.CachingConfigurerSupport; import org.springframework.cache.annotation.EnableCaching; 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.connection.RedisConnectionFactory; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.serializer.Jackson2JsonRedisSerializer; import org.springframework.data.redis.serializer.RedisSerializationContext; import org.springframework.data.redis.serializer.RedisSerializer; import org.springframework.data.redis.serializer.StringRedisSerializer; import java.time.Duration; @Configuration @EnableCaching public class RedisConfig extends CachingConfigurerSupport { @Bean public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) { RedisTemplate<String, Object> template = new RedisTemplate<>(); RedisSerializer<String> redisSerializer = new StringRedisSerializer(); 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.setConnectionFactory(factory); //key序列化方式 template.setKeySerializer(redisSerializer); //value序列化 template.setValueSerializer(jackson2JsonRedisSerializer); //value hashmap序列化 template.setHashValueSerializer(jackson2JsonRedisSerializer); return template; } @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),过期时间600秒 RedisCacheConfiguration config = RedisCacheConfiguration .defaultCacheConfig() .entryTtl(Duration.ofSeconds(600)) .serializeKeysWith(RedisSerializationContext.SerializationPair.fromSerializer(redisSerializer)) .serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(jackson2JsonRedisSerializer)) .disableCachingNullValues(); RedisCacheManager cacheManager = RedisCacheManager.builder(factory) .cacheDefaults(config) // 可以给每个cacheName不同的RedisCacheConfiguration 设置不同的过期时间 //.withCacheConfiguration("Users",config.entryTtl(Duration.ofSeconds(100))) .transactionAware() .build(); return cacheManager; } }
1. @Cacheable
is marked on a method or class to identify that the method or class supports it. cache. After Spring calls the annotation identification method, the return value will be cached in redis to ensure that the next time the method is called with the same conditions, the return value will be obtained directly from the cache. In this way, there is no need to re-execute the business processing process of this method, which improves efficiency.
@Cacheable The three commonly used parameters are as follows:
cacheNames Cache name
key The cached key, you need to pay attention to how the key is written
condition The condition for cache execution, when true is returned Execution
Example
//查询所有用户,缓存到redis中 @GetMapping("/selectFromRedis") @Cacheable(cacheNames = "Users",key = "'user'") public ResultData getUserRedis(){ List<User> list = userService.list(null); return ResultData.ok().data("User",list); }
The first query is queried from the database and then cached into redis. Use the redis visualization tool to view the cached information
The second query goes to the cache console and there is no output, so the redis cache is to get the results in redis and return them directly.
@CacheEvict
is marked on the method. After the method is executed, the corresponding cache will be deleted based on the condition or key. Commonly used attributes:
allEntries boolean type, indicating whether all elements in the cache need to be cleared
key The key of the cache that needs to be deleted
//调用这个接口结束后,删除指定的Redis缓存 @PostMapping("updateUser") @CacheEvict(cacheNames ="Users",key = "'user'") public ResultData updateUser(@RequestBody User user){ String id = user.getId(); QueryWrapper<User> wrapper=new QueryWrapper<>(); wrapper.eq("id",id); boolean b = userService.update(user, wrapper); return ResultData.ok().data("flag",b); }
//不删除redis缓存 @PostMapping("updateUser2") public ResultData updateUser2(@RequestBody User user){ String id = user.getId(); QueryWrapper<User> wrapper=new QueryWrapper<>(); wrapper.eq("id",id); boolean b = userService.update(user, wrapper); return ResultData.ok().data("flag",b); }
When we update the data in the database, we need to clear the redis cache. Otherwise, the data we query is the data in the redis cache, which will cause inconsistency between the database and cached data.
Example: Call the interface without @CacheEvict annotation to modify the data. The data obtained in the query is before modification.
So when we call the interface to modify the data, we need to clear the cache
Add the @CacheEvict annotation to clear the corresponding cache. At this time, the data is discovered during the query. It is the latest and consistent with the database.
Expiration time
We have implemented the basic functions of Spring Cache and integrated Redis as RedisCacheManger
, but as we all know, we are When using the @Cacheable
annotation, you cannot give the cache an expiration time. But sometimes in some scenarios we really need to give the cache an expiration time! This is the default expiration time
Data validity period
Custom expiration time
Use the new redis configuration and query the cached data again to see the data validity period
The above is the detailed content of How to use @Cacheable in the integration of springboot and redis. For more information, please follow other related articles on the PHP Chinese website!

RedisofferssuperiorspeedfordataoperationsbutrequiressignificantRAMandinvolvestrade-offsindatapersistenceandscalability.1)Itsin-memorynatureprovidesultra-fastread/writeoperations,idealforreal-timeapplications.2)However,largedatasetsmaynecessitatedatae

Redisoutperformstraditionaldatabasesinspeedforread/writeoperationsduetoitsin-memorynature,whiletraditionaldatabasesexcelincomplexqueriesanddataintegrity.1)Redisisidealforreal-timeanalyticsandcaching,offeringphenomenalperformance.2)Traditionaldatabase

UseRedisinsteadofatraditionaldatabasewhenyourapplicationrequiresspeedandreal-timedataprocessing,suchasforcaching,sessionmanagement,orreal-timeanalytics.Redisexcelsin:1)Caching,reducingloadonprimarydatabases;2)Sessionmanagement,simplifyingdatahandling

Redis goes beyond SQL databases because of its high performance and flexibility. 1) Redis achieves extremely fast read and write speed through memory storage. 2) It supports a variety of data structures, such as lists and collections, suitable for complex data processing. 3) Single-threaded model simplifies development, but high concurrency may become a bottleneck.

Redis is superior to traditional databases in high concurrency and low latency scenarios, but is not suitable for complex queries and transaction processing. 1.Redis uses memory storage, fast read and write speed, suitable for high concurrency and low latency requirements. 2. Traditional databases are based on disk, support complex queries and transaction processing, and have strong data consistency and persistence. 3. Redis is suitable as a supplement or substitute for traditional databases, but it needs to be selected according to specific business needs.

Redisisahigh-performancein-memorydatastructurestorethatexcelsinspeedandversatility.1)Itsupportsvariousdatastructureslikestrings,lists,andsets.2)Redisisanin-memorydatabasewithpersistenceoptions,ensuringfastperformanceanddatasafety.3)Itoffersatomicoper

Redis is primarily a database, but it is more than just a database. 1. As a database, Redis supports persistence and is suitable for high-performance needs. 2. As a cache, Redis improves application response speed. 3. As a message broker, Redis supports publish-subscribe mode, suitable for real-time communication.

Redisisamultifacetedtoolthatservesasadatabase,server,andmore.Itfunctionsasanin-memorydatastructurestore,supportsvariousdatastructures,andcanbeusedasacache,messagebroker,sessionstorage,andfordistributedlocking.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Dreamweaver CS6
Visual web development tools

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

SublimeText3 Linux new version
SublimeText3 Linux latest version

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft
