Caching and distributed caching technology in Java

With the continuous development of modern Internet applications, the performance requirements of applications are becoming higher and higher. To meet these needs, caching technology is becoming increasingly important. Caching is a technique for storing data in a location that is quickly accessible and can make an application more responsive. Java provides a variety of caching technologies and also supports storing cached data in a distributed environment. This article will introduce caching technology and distributed caching technology in Java.

Caching technology in Java

Java provides a variety of caching technologies, several of which will be introduced below.

HashMap and ConcurrentHashMap

HashMap is a commonly used data structure in the Java collection framework. It can store key-value pairs in memory and supports O(1) complexity reading. write operation. HashMap is suitable for scenarios where the number of key-value pairs does not exceed a few thousand, but its performance will decrease when the number increases.

ConcurrentHashMap is a thread-safe hash table implementation that supports multiple threads to perform read and write operations at the same time without data inconsistency. In concurrent access scenarios, ConcurrentHashMap performs better than HashMap.

Ehcache

Ehcache is one of the Java caching frameworks, which provides basic functions such as storage, retrieval and update of cached data. Unlike HashMap, Ehcache can configure the expiration time of cached data and set the maximum number of cached objects. When the cached data exceeds the set limit, some expired or infrequently accessed data will be automatically deleted to free up space.

Guava Cache

Guava Cache is Google's open source Java caching framework. It supports storing cache data in memory and provides cache expiration effects and maximum cache object configuration. Guava Cache also supports functions such as manual clearing and preloading of cache data.

Caffeine

Caffeine is a high-performance Java caching framework. It is similar to Guava Cache and provides the basic function of caching data in memory. However, in comparison, Caffeine is inferior in performance. Even better. In concurrent access scenarios, Caffeine's performance is often more than 10 times that of other Java caching frameworks.

Distributed caching technology in Java

In addition to the local caching technology introduced above, Java also supports storing cached data in a distributed environment. Distributed caching refers to spreading cache data across multiple computers to improve cache performance and scalability. Several commonly used Java distributed cache technologies will be introduced below.

Memcached

Memcached is an open source distributed memory object caching system that can distribute cached data across multiple computers and supports automatic data sharding and automatic load balancing. Memcached can run as an independent daemon and can be used on multiple platforms.

Redis

Redis is a high-performance key-value storage system that can store cached data in memory or persist data to disk. Redis supports a variety of data structures, including strings, hash tables, lists, sets, ordered sets, etc., and provides a variety of advanced functions, such as publish/subscribe, Lua scripts, expiration monitoring, etc.

Hazelcast

Hazelcast is an open source data grid technology that provides distributed caching, distributed data structure and distributed computing functions. Hazelcast supports storing cached data in memory and enables automatic data replication and load balancing across multiple computers. Hazelcast also provides full support for the JCache specification, allowing it to work seamlessly with other Java caching frameworks.

Conclusion

Caching technology is an important means to improve application performance and response speed. Java provides a variety of local caching technologies and distributed caching technologies. Choosing a caching technology that suits your application scenario can improve application performance and effectively reduce server load. However, when using caching technology, you must also pay attention to the consistency and update strategy of cached data.

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