SpringBoot integrates using redis
Jedis is a Java-oriented client officially launched by Redis, which provides many interfaces for Java language calls. It can be downloaded from the Redis official website. Spring-data-redis is part of the spring family. It provides access to the redis service through simple configuration in the srping application, and highly encapsulates the reids underlying development package (Jedis, JRedis, and RJC). RedisTemplate provides various redis operations
spring-data-redis provides the following functions for jedis:
The connection pool automatically manages and provides a highly encapsulated "RedisTemplate "Class.
Classifies and encapsulates a large number of APIs in the jedis client, and encapsulates the same type of operations into operation interfaces.
ValueOperations : Simple K-V operation
SetOperations: set type data operation
ZSetOperations: zset type data operation
HashOperations: for map type data operation
ListOperations: For list type data operations
3. Encapsulate transaction operations and have container control.
4. A variety of optional strategies (RedisSerializer) are provided for the "serialization/deserialization" of data
JdkSerializationRedisSerializer: access scenarios for POJO objects, using JDK itself for serialization Mechanism.
StringRedisSerializer: When the Key or value is a string, the byte sequence of the data is encoded into a string according to the specified charset, which is "new String(bytes, charset)" and "string.getBytes(charset) )" direct encapsulation. is the most lightweight and efficient strategy.
JacksonJsonRedisSerializer: The jackson-json tool provides conversion capabilities between javabean and json. It can serialize pojo instances into json format and store them in redis, and can also convert json format data into pojo instances.
Build
1. Import the jar package
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis</artifactId> </dependency>
2. Configure the connection redis
spring: redis: host: 192.168.31.100 port: 6379 password: 111 database: 0 pool: max-active: 8 # 连接池最大连接数(使用负值表示没有限制) max-wait: -1ms # 连接池最大阻塞等待时间(使用负值表示没有限制) max-idle: 8 # 连接池中的最大空闲连接 min-idle: 0 # 连接池中的最小空闲连接 timeout: 5000ms # 连接超时时间(毫秒)
Add the above configuration under spring in the application.yml file
3. Add the configuration class RedisConfig
package com.ffyc.back.demo.config; import com.fasterxml.jackson.annotation.JsonAutoDetect; import com.fasterxml.jackson.annotation.JsonTypeInfo; import com.fasterxml.jackson.annotation.PropertyAccessor; import com.fasterxml.jackson.databind.DeserializationFeature; import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.jsontype.impl.LaissezFaireSubTypeValidator; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; 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.StringRedisSerializer; @Configuration public class RedisConfig { /** * 序列化键,值 * @param connectionFactory * @return */ @Bean public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory connectionFactory) { RedisTemplate<String, Object> redisTemplate = new RedisTemplate<>(); redisTemplate.setConnectionFactory(connectionFactory); Jackson2JsonRedisSerializer<Object> jackson2JsonRedisSerializer = new Jackson2JsonRedisSerializer<Object>(Object.class); StringRedisSerializer redisSerializer = new StringRedisSerializer(); redisTemplate.setKeySerializer(redisSerializer); redisTemplate.setHashKeySerializer(redisSerializer); redisTemplate.setValueSerializer(jackson2JsonRedisSerializer); redisTemplate.setHashValueSerializer(jackson2JsonRedisSerializer); return redisTemplate; } }
Add this configuration in the configuration package
The function of this configuration class is to serialize the data to be passed by the backend to json. If there is no such configuration, the backend If the passed format does not match the redis side, garbled characters will appear
4. Inject RedisTemplate
Inject it where you need to use it and you can use it
5. Test and use
Usage examples:
(1)
(2)
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Redis's data model and structure include five main types: 1. String: used to store text or binary data, and supports atomic operations. 2. List: Ordered elements collection, suitable for queues and stacks. 3. Set: Unordered unique elements set, supporting set operation. 4. Ordered Set (SortedSet): A unique set of elements with scores, suitable for rankings. 5. Hash table (Hash): a collection of key-value pairs, suitable for storing objects.

Redis's database methods include in-memory databases and key-value storage. 1) Redis stores data in memory, and reads and writes fast. 2) It uses key-value pairs to store data, supports complex data structures such as lists, collections, hash tables and ordered collections, suitable for caches and NoSQL databases.

Redis is a powerful database solution because it provides fast performance, rich data structures, high availability and scalability, persistence capabilities, and a wide range of ecosystem support. 1) Extremely fast performance: Redis's data is stored in memory and has extremely fast read and write speeds, suitable for high concurrency and low latency applications. 2) Rich data structure: supports multiple data types, such as lists, collections, etc., which are suitable for a variety of scenarios. 3) High availability and scalability: supports master-slave replication and cluster mode to achieve high availability and horizontal scalability. 4) Persistence and data security: Data persistence is achieved through RDB and AOF to ensure data integrity and reliability. 5) Wide ecosystem and community support: with a huge ecosystem and active community,

Key features of Redis include speed, flexibility and rich data structure support. 1) Speed: Redis is an in-memory database, and read and write operations are almost instantaneous, suitable for cache and session management. 2) Flexibility: Supports multiple data structures, such as strings, lists, collections, etc., which are suitable for complex data processing. 3) Data structure support: provides strings, lists, collections, hash tables, etc., which are suitable for different business needs.

The core function of Redis is a high-performance in-memory data storage and processing system. 1) High-speed data access: Redis stores data in memory and provides microsecond-level read and write speed. 2) Rich data structure: supports strings, lists, collections, etc., and adapts to a variety of application scenarios. 3) Persistence: Persist data to disk through RDB and AOF. 4) Publish subscription: Can be used in message queues or real-time communication systems.

Redis supports a variety of data structures, including: 1. String, suitable for storing single-value data; 2. List, suitable for queues and stacks; 3. Set, used for storing non-duplicate data; 4. Ordered Set, suitable for ranking lists and priority queues; 5. Hash table, suitable for storing object or structured data.

Redis counter is a mechanism that uses Redis key-value pair storage to implement counting operations, including the following steps: creating counter keys, increasing counts, decreasing counts, resetting counts, and obtaining counts. The advantages of Redis counters include fast speed, high concurrency, durability and simplicity and ease of use. It can be used in scenarios such as user access counting, real-time metric tracking, game scores and rankings, and order processing counting.


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