Cache data obfuscation in Java caching technology

With the continuous development of Internet technology, more and more applications use caching technology to improve data access speed and reduce database pressure. As a popular programming language, Java also provides a variety of caching frameworks, such as Ehcache, Guava Cache, Redis, etc. However, in the process of using caching technology, we often encounter a problem: cache data confusion. This article will introduce the causes, effects and how to solve cached data obfuscation.

1. Reasons for cached data confusion

Cache data confusion refers to the conflict problem that occurs when the data stored in the cache is accessed by different applications or threads at the same time. The main reasons are as follows:

1. Concurrent access: When multiple applications or threads access data in the same cache at the same time, it is easy to cause data confusion.
2. Same name key: When multiple applications or threads use the same key to store data, the cache framework may overwrite the previously stored data, causing data confusion.
3. Cache invalidation: When the data in the cache becomes invalid, multiple applications or threads may re-obtain data from the database at the same time, resulting in a large number of database requests and reducing system performance.

2. The impact of cached data confusion

Cache data confusion will cause the following problems:

1. Data errors: When cached data is confused, reading The received data may be wrong, causing business logic errors.
2. Data loss: When cached data is accidentally deleted or overwritten, the data originally stored in the cache may be lost, affecting the normal operation of the business.
3. System exception: When the cached data is seriously confused, it will cause the system to crash or the interface to become unresponsive, affecting the user experience.

3. Methods to solve cache data confusion

1. Lock mechanism: The lock mechanism is used to ensure that only one thread can operate the cache at the same time to avoid concurrent access problems. However, the lock mechanism will reduce system concurrency performance and is not suitable for high concurrency scenarios.
2. Distributed lock: In a distributed environment, distributed locks can be used to ensure the consistency of cached data. However, the implementation complexity of distributed locks is high and problems such as deadlocks are prone to occur.
3. Cache namespace: Set different cache namespaces for different applications or threads to avoid the problem of overwriting keys with the same name. However, the setting of the cache namespace requires negotiation between each application and is not flexible enough.
4. TTL randomization: Set a random expiration time for the cache to avoid database request storms caused by simultaneous cache failures, but it may cause a decrease in cache hit rate.
5. Increase cache levels: Add cache levels to multi-level caches, store cache data in a distributed manner, and reduce the probability of cache access conflicts. However, increasing the cache level will bring additional system overhead.

4. Conclusion

Caching technology is widely used in Internet applications and is an important means to improve system performance. Understanding and solving the problem of cached data confusion is very important to ensure data consistency and improve system performance. In actual development, the appropriate caching solution should be selected based on specific business conditions.

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