Combined with Redis using Java caching technology

With the rapid development of the Internet, the amount of data and requests for applications has also shown an exponential growth trend. In order to ensure high performance and high availability of applications, caching technology has become an indispensable part. For Java applications, Redis is an excellent caching solution. This article will introduce how to implement efficient caching technology using Java and Redis, and explore some common caching usage scenarios.

1. Introduction to Redis caching technology
Redis is a high-performance in-memory data structure storage system that supports a variety of data structures such as strings, hash tables, lists, sets, etc., and supports rich Operations, such as self-increment, self-decrement, expiration, etc. Redis has been widely used in many scenarios, such as caching, message queues, distributed locks, etc.

2. Introduction to Java caching technology
There are also many caching solutions in Java applications, such as Ehcache, Caffeine, Guava, ConcurrentHashMap, etc. These solutions provide different caching strategies and data structures to adapt to different application scenarios.

3. Combination of Redis and Java cache
Redis and Java cache technologies can be combined with each other to form a more complete cache solution. This combination can be divided into two ways: one is to use Redis as the backend of the Java cache solution, and the other is to use Redis cache directly in the Java application.

1. Redis as a backend for Java caching solution
   In this way, the Java application writes data to the Redis cache instead of writing to the local cache. When a Java application performs data query, it first queries the Redis cache. If there is data in Redis, it returns the data directly. Otherwise, it queries the database and writes the query results to the Redis cache. The advantage of this is that Redis can save more data and has better scalability and reliability.
2. Use Redis cache directly
   In this way, the Java application uses the Redis cache to cache data instead of using the local cache. When a Java application performs data query, it directly queries the Redis cache. If there is data in Redis, it returns the data directly. Otherwise, it queries the database and writes the query results to the Redis cache. In this way, Java applications do not have to worry about the cleaning and invalidation of local caches, and it is easier to implement distributed caching.

4. Usage scenarios of Redis cache
Redis cache technology is widely used in many scenarios. Some common usage scenarios are listed below.

1. Session Cache
   In web applications, session is a very important concept. To reduce database access, you can use Redis cache to save session data. The advantage of this is that session data can be shared by multiple application nodes and distributed session management can be achieved.
2. Database Query Cache
   When querying in an application, the database often needs to be queried frequently, which puts pressure on the database. Using Redis cache to save query results can reduce the pressure on the database and improve query efficiency. It should be noted that the cache expiration time should be set according to business needs to ensure timely updating of data.
3. Distributed lock
   In a distributed system, in order to prevent multiple nodes from modifying the same data at the same time, it is often necessary to use distributed locks for control. Redis's SETNX command can implement distributed locks and occupy lock resources by writing a certain value to the Redis cache. It should be noted that when releasing the lock, you need to use the Redis atomic command correctly to avoid deadlock.

5. Summary
This article briefly introduces Redis and Java cache technology, and discusses the combination of Redis and Java cache. At the same time, this article also lists some common Redis cache usage scenarios. Using Redis cache can improve the performance and availability of applications, and also provides a very valuable solution for the design of distributed applications.

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