In the current Internet environment of high concurrency and big data, caching technology has become one of the important means to improve system performance. In Java caching technology, distributed caching is a very important technology. So what is distributed cache? This article will take an in-depth look at distributed caching in Java caching technology.

1. The basic concept of distributed cache

Distributed cache refers to a cache system that stores cache data on multiple nodes. Each node contains a complete copy of cached data and can back up each other. When one node fails, other nodes can continue to provide cache services.

In distributed cache, we usually use consistent hashing algorithm. The consistent hashing algorithm can hash the cached data onto the hash ring and distribute the nodes on the hash ring. When a cached data is requested, it is first hashed to obtain its position on the hash ring. Next, find the first node in a clockwise direction, and then get the cache data from that node. If the node fails, the search is performed in a clockwise direction until an available node is found.

2. Advantages of distributed cache

1. High availability: Distributed cache backs up cache data on multiple nodes and can provide high availability services. When one of the nodes fails, the other nodes can continue to provide services.
2. High scalability: In distributed cache, we can add or delete nodes as needed to meet business needs. This makes the distributed cache highly scalable.
3. High performance: Distributed cache can disperse data across multiple nodes, avoiding the performance bottleneck of a single node and improving the overall performance of the cache system.

3. Usage scenarios of distributed cache

1. High-concurrency read and write scenarios: Distributed cache is suitable for handling some high-concurrency read and write scenarios, such as websites and mobile applications. , e-commerce platforms, etc.
2. Big data environment: In a big data environment, distributed cache can help us quickly process massive amounts of data.
3. Distributed system: In a distributed system, distributed cache can be used as a distributed lock to ensure data consistency.

4. Commonly used distributed caches

1. Redis: Redis is a high-performance, non-relational key-value database. Redis provides a wealth of data structures and commands to meet the needs of various scenarios. Redis supports distributed cache and master-slave backup.
2. Memcached: Memcached is a high-performance distributed caching tool. Memcached supports multi-node caching services, can be extended to hundreds of servers, and supports caching of multiple data types such as strings, arrays, and objects.
3. Hazelcast: Hazelcast is an open source distributed caching tool. Hazelcast is implemented in Java and provides a distributed cluster that can handle large-scale cached data.

5. Precautions for distributed caching

1. Cache penetration: Cache penetration refers to an attack method. The attacker makes malicious requests to make the cache in the cache Data that doesn't exist keeps being requested. To avoid cache penetration, we can pre-populate some default data.
2. Cache avalanche: Cache avalanche refers to a large amount of data in the cache that expires at the same time within a period of time, resulting in a large number of requests directly accessing the database, causing excessive pressure on the database. In order to avoid cache avalanche, methods such as cache preheating, setting random expiration time, and adding a circuit breaker mechanism can be used.
3. Cache persistence: In a distributed cache, since the cache data is stored in memory, the cache data will be lost when the node restarts or crashes. Therefore, some key data need to be persisted to improve the reliability of the cache.

6. Summary

Distributed cache is an important part of Java cache technology, which can greatly improve the performance and availability of the system. However, when using distributed cache, you need to pay attention to cache penetration, cache avalanche, cache persistence and other issues. Only by deeply understanding the principles and precautions of distributed cache can we better apply it in actual projects and improve the performance and reliability of the system.

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